摘要:Purpose–The purpose of this paper is to design a robust control scheme to achieve robust tracking of velocity and altitude commands for a general hypersonic vehicle(HSV)in the presence of parameter variations and external disturbances.Design/methodology/approach–The robust control scheme is composed of nonsingular terminal sliding mode control(NTSMC),super twisting control algorithm(STC)and recurrent neural network(RNN).First,by combing a novel NTSMC and STC algorithm,a second order NTSMC approach for HSV is proposed to provide fast,continuous and high precision tracking control.Second to relax the requirements for the bounds of the lumped uncertainties in control design,a RNN disturbance observer is presented to increase the robustness of the control system.The weights of RNN are updated by adaptive laws based on Lyapunov theorem,thus the closed-loop stability can be guaranteed.Findings–Simulation results demonstrate that the proposed method is effective,leading to promising performance.Originality/value–The main contributions of this work are:first,both parameter variations and external disturbances are considered in control design for the longitudinal dynamic model of HSV;and second,the proposed controller can remove chattering and achieve more favorable tracking performances than conventional sliding mode control.
摘要:Purpose-The purpose of this paper is to improve the privacy in healthcare datasets that hold sensitive information.Putting a stop to privacy divulgence and bestowing relevant information to legitimate users are at the same time said to be of differing goals.Also,the swift evolution of big data has put forward considerable ease to all chores of life.As far as the big data era is concerned,propagation and information sharing are said to be the two main facets.Despite several research works performed on these aspects,with the incremental nature of data,the likelihood of privacy leakage is also substantially expanded through various benefits availed of big data.Hence,safeguarding data privacy in a complicated environment has become a major setback.Design/methodology/approach-In this study,a method called deep restricted additive homomorphic ElGamal privacy preservation(DR-AHEPP)to preserve the privacy of data even in case of incremental data is proposed.An entropy-based differential privacy quasi identification and DR-AHEPP algorithms are designed,respectively,for obtaining privacy-preserved minimum falsified quasi-identifier set and computationally efficient privacy-preserved data.Findings-Analysis results using Diabetes 130-US hospitals illustrate that the proposed DR-AHEPP method is more significant in preserving privacy on incremental data than existing methods.Acomparative analysis of state-of-the-art works with the objective to minimize information loss,false positive rate and execution time with higher accuracy is calibrated.Originality/value-The paper provides better performance using Diabetes 130-US hospitals for achieving high accuracy,low information loss and false positive rate.The result illustrates that the proposed method increases the accuracy by 4%and reduces the false positive rate and information loss by 25 and 35%,respectively,as compared to state-of-the-art works.
摘要:Purpose–The authors believe that people with cognitive and motor impairments may benefit from using of telepresence robots to engage in social activities.To date,these systems have not been designed for use by people with disabilities as the robot operators.The paper aims to discuss these issues.Design/methodology/approach–The authors conducted two formative evaluations using a participatory action design process.First,the authors conducted a focus group(n¼5)to investigate how members of the target audience would want to direct a telepresence robot in a remote environment using speech.The authors then conducted a follow-on experiment in which participants(n¼12)used a telepresence robot or directed a human in a scavenger hunt task.Findings–The authors collected a corpus of 312 utterances(first hand as opposed to speculative)relating to spatial navigation.Overall,the analysis of the corpus supported several speculations put forth during the focus group.Further,it showed few statistically significant differences between speech used in the human and robot agent conditions;thus,the authors believe that,for the task of directing a telepresence robot’s movements in a remote environment,people will speak to the robot in a manner similar to speaking to another person.Practical implications–Based upon the two formative evaluations,the authors present four guidelines for designing speech-based interfaces for telepresence robots.Originality/value–Robot systems designed for general use do not typically consider people with disabilities.The work is a first step towards having our target population take the active role of the telepresence robot operator.
摘要:Purpose-The application of the traditional failure mode and effects analysis(FMEA)technique has been widely questioned in evaluation information,risk factor weights and robustness of results.This paper develops a novel FMEA framework with extended MULTIMOORA method under interval-valued Pythagorean fuzzy environment to solve these problems.Design/methodology/approach-This paper introduces innovatively interval-value Pythagorean fuzzy weighted averaging(IVPFWA)operator,Tchebycheff metric distance and interval-value Pythagorean fuzzy weighted geometric(IVPFWG)operator into the MULTIMOORA submethods to obtain the risk ranking order for emergencies.Finally,an illustrative case is provided to demonstrate the practicality and feasibility of the novel fuzzy FMEA framework.Findings-The feasibility and validity of the proposed method are verified by comparing with the existing methods.The calculation results indicate that the proposed method is more consistent with the actual situation of project and has more reference value.Practical implications-The research results can provide supporting information for risk management decisions and offer decision-making basis for formulation of the follow-up emergency control and disposal scheme,which has certain guiding significance for the practical popularization and application of risk management strategies in the infrastructure projects.Originality/value–A novel approach using FMEA with extended MULTIMOORA method is developed under IVPF environment,which considers weights of risk factors and experts.The method proposed has significantly improved the integrity of information in expert evaluation and the robustness of results.
摘要:Purpose–In this paper,two popular multiple-criteria decision-making(MCDM)methods with hesitant fuzzy logic approach;hesitant fuzzy analytic hierarchy process(hesitant F-AHP)and hesitant fuzzy the technique for order preference by similarity to ideal solution(HF-TOPSIS)are integrated as HF-AHP-TOPSIS to evaluating a set of enterprise resource planning(ERP)alternatives and rank them by weight to reach to the ultimate one that satisfies the needs and expectations of a company.Design/methodology/approach–Selecting the best ERP software package among the rising number of the options in market has been a critical problem for most companies for a long time because of the reason that an improper ERP software package might lead to many issues(i.e.time loss,increased costs and a loss of market share).On the other hand,finding the best ERP alternative is a comprehensive MCDM problem in the presence of a set of alternatives and several potentially competing quantitative and qualitative criteria.Findings–In this integrated approach,the hesitant F-AHP is used to determine the criteria weights,as the hesitant F-TOPSIS is utilized to rank ERP package alternatives.The proposed approach was also validated in a numerical example that has five ERP package alternatives and 12 criteria by three decision-makers in order to show its applicability to potential readers and practitioners.Research limitations/implications–If the number of the alternatives and criteria are dramatically increased beyond reasonable numbers,the reaching to final solution will be so difficult because of the great deal of fuzzy based calculations.Therefore,the number of criteria and alternatives should be at reasonable numbers.Practical implications–The proposed approach was also validated in a illustrated example with the five ERP package options and 12 criteria by the three decision-makers in order to show its applicability to potential readers and practitioners.Originality/value–Furthermore,in literature,to the best of our knowledge,the authors did not come cross any work that integrates the HF-AHP with the HF-TOPSIS for ERP software package selection problem.
摘要:Purpose-English original movies played an important role in English learning and communication.In order to find the required movies for us from a large number of English original movies and reviews,this paper proposed an improved deep reinforcement learning algorithm for the recommendation of movies.In fact,although the conventional movies recommendation algorithms have solved the problem of information overload,they still have their limitations in the case of cold start-up and sparse data.Design/methodology/approach-To solve the aforementioned problems of conventional movies recommendation algorithms,this paper proposed a recommendation algorithm based on the theory of deep reinforcement learning,which uses the deep deterministic policy gradient(DDPG)algorithm to solve the cold starting and sparse data problems and uses Item2vec to transform discrete action space into a continuous one.Meanwhile,a reward function combining with cosine distance and Euclidean distance is proposed to ensure that the neural network does not converge to local optimum prematurely.Findings-In order to verify the feasibility and validity of the proposed algorithm,the state of the art and the proposed algorithm are compared in indexes of RMSE,recall rate and accuracy based on the MovieLens English original movie data set for the experiments.Experimental results have shown that the proposed algorithm is superior to the conventional algorithm in various indicators.Originality/value-Applying the proposed algorithm to recommend English original movies,DDPG policy produces better recommendation results and alleviates the impact of cold start and sparse data.
摘要:Purpose-The purpose of this study is to develop a hybrid algorithm for segmenting tumor from ultrasound images of the liver.Design/methodology/approach-After collecting the ultrasound images,contrast-limited adaptive histogram equalization approach(CLAHE)is applied as preprocessing,in order to enhance the visual quality of the images that helps in better segmentation.Then,adaptively regularized kernel-based fuzzy C means(ARKFCM)is used to segment tumor from the enhanced image along with local ternary pattern combined with selective level set approaches.Findings-The proposed segmentation algorithm precisely segments the tumor portions from the enhanced images with lower computation cost.The proposed segmentation algorithm is compared with the existing algorithms and ground truth values in terms of Jaccard coefficient,dice coefficient,precision,Matthews correlation coefficient,f-score and accuracy.The experimental analysis shows that the proposed algorithm achieved 99.18% of accuracy and 92.17% of f-score value,which is better than the existing algorithms.Practical implications-From the experimental analysis,the proposed ARKFCM with enhanced level set algorithm obtained better performance in ultrasound liver tumor segmentation related to graph-based algorithm.However,the proposed algorithm showed 3.11% improvement in dice coefficient compared to graph-based algorithm.Originality/value-The image preprocessing is carried out using CLAHE algorithm.The preprocessed image is segmented by employing selective level set model and Local Ternary Pattern in ARKFCM algorithm.In this research,the proposed algorithm has advantages such as independence of clustering parameters,robustness in preserving the image details and optimal in finding the threshold value that effectively reduces the computational cost.
摘要:Purpose-For the large-scale power grid monitoring system equipment,its working environment is increasingly complex and the probability of fault or failure of the monitoring system is gradually increasing.This paper proposes a fault classification algorithm based on Gaussian mixture model(GMM),which can complete the automatic classification of fault and the elimination of fault sources in the monitoring system.Design/methodology/approach-The algorithm first defines the GMM and obtains the detection value of the fault classification through a method based on the causal Mason Young Tracy(MYT)decomposition under each normal distribution in the GMM.Then,the weight value of GMM is used to calculate weighted classification value of fault detection and separation,and by comparing the actual control limits with the classification result of GMM,the fault classification results are obtained.Findings-The experiment on the defined non-thermostatic continuous stirred-tank reactor model shows that the algorithm proposed in this paper is superior to the traditional algorithm based on the causal MYT decomposition in fault detection and fault separation.Originality/value-The proposed algorithm fundamentally solves the problem of fault detection and fault separation in large-scale systems and provides support for troubleshooting and identifying fault sources.
摘要:Purpose–The two-tank level control system is one of the real-world’s second-order system(SOS)widely used as the process control in industries.It is normally operated under the Proportional integral and derivative(PID)feedback control loop.The conventional PID controller performance degrades significantly in the existence of modeling uncertainty,faults and process disturbances.To overcome these limitations,the paper suggests an interval type-2 fuzzy logic based Tilt-Integral-Derivative Controller(IT2TID)which is modified structure of PID controller.Design/methodology/approach–In this paper,an optimization IT2TID controller design for the conical,noninteracting level control system is presented.Regarding to modern optimization context,the flower pollination algorithm(FPA),among the most coherent population-based metaheuristic optimization techniques is applied to search for the appropriate IT2FTID’s and IT2FPID’s parameters.The proposed FPA-based IT2FTID/IT2FPID design framework is considered as the constrained optimization problem.System responses obtained by the IT2FTID controller designed by the FPA will be differentiated with those acquired by the IT2FPID controller also designed by the FPA.Findings–As the results,it was found that the IT2FTID can provide the very satisfactory tracking and regulating responses of the conical two-tank noninteracting level control system superior as compared to IT2FPID significantly under the actuator and system component faults.Additionally,statistical Z-test carried out for both the controllers and an effectiveness of the proposed IT2FTID controller is proven as compared to IT2FPID and existing passive fault tolerant controller in recent literature.Originality/value–Application of new metaheuristic algorithm to optimize interval type-2 fractional order TID controller for nonlinear level control system with two type of faults.Also,proposed method will compare with other method and statistical analysis will be presented.
摘要:Purpose-The purpose of this paper is to address the problem of control in a typical chaotic power system.Chaotic oscillations cannot only extremely endanger the stabilization of the power system but they can also not be controlled by adding the traditional controllers.So,the sliding mode control based on a fuzzy supervisor can sufficiently ensure perfect tracking and controlling in the presence of uncertainties.Closed-loop stability is proved using the Lyapunov stability theory.The simulation results show the effectiveness of the proposed method in damping chaotic oscillations of the power system,eliminating control signal chattering and also show less control effort in comparison with the methods considered in previous literatures.Design/methodology/approach-The sliding mode control based on a fuzzy supervisor can sufficiently ensure perfect tracking and controlling in the presence of uncertainties.Closed-loop stability is proved using the Lyapunov stability theory.Findings-Closed-loop stability is proved using the Lyapunov stability theory.The simulation results show the effectiveness of the proposed method in damping chaotic oscillations of power system,eliminating control signal chattering and also less control effort in comparison with the methods considered in previous literatures.Originality/value-Main contributions of the paper are as follows:the chaotic behavior of power systems with two uncertainty parameters and tracking reference signal for the control of generator angle and the controller signal are discussed;designing sliding mode control based on a fuzzy supervisor in order to practically implement for the first time;while the generator speed is constant,the proposed controller will enable the power system to go in any desired trajectory for generator angle at first time;stability of the closed-loop sliding mode control based on the fuzzy supervisor system is proved using the Lyapunov stability theory;simulation of the proposed controller shows that the chattering is low control signal.
摘要:Purpose–The purpose of this paper is to extend the work of fusing sensors with a Bayesian method to incorporate the sensor’s reliability with regard to their operating environment.The results are then to be used with the expected decision formula,conditional entropy and mutual information for suboptimally selecting which types of sensors should be fused where there are operational constraints.Design/methodology/approach–The approach is an extension of previous work incorporating an environment parameter.The expected decision formula then forms the basis for sensor selection.Findings–The author found that the performance of the sensors is correlated to the environment of operation,given that the likelihood of error will be higher in a difficult terrain than would otherwise be the case.However,the author also shows the sensors for fusion will vary if the author knows specifically which terrain the sensors will be operating in.Research limitations/implications–The author notes that in order for this technique to be effective,a proper understanding of the limitations of the sensors,possible terrain types and targets have to be assumed.Practical implications–The practical implication of this work is the ability to assess the performance of fused sensors according to the environment or terrain they might be operating under,thus providing a greater level of sensitivity than would otherwise be the case.Originality/value–The author has extended previous ideas on sensor fusion from imprecise and uncertain sources using a Bayesian technique,as well as developed techniques regarding which sensors should be chosen for fusion given payload or other constraints.
摘要:Purpose–The purpose of this paper is to develop a methodology for the existence and global exponential stability of the unique equilibrium point of a class of impulsive Cohen-Grossberg neural networks.Design/methodology/approach–The authors perform M-matrix theory and homeomorphism mapping principle to investigate a class of impulsive Cohen-Grossberg networks with time-varying delays and distributed delays.The approach builds on new sufficient criterion without strict conditions imposed on self-regulation functions.Findings–The authors’approach results in new sufficient criteria easy to verify but without the usual assumption that the activation functions are bounded and the time-varying delays are differentiable.An example shows the effectiveness and superiority of the obtained results over some previously known results.Originality/value–The novelty of the proposed approach lies in removing the usual assumption that the activation functions are bounded and the time-varying delays are differentiable,and the use of M-matrix theory and homeomorphism mapping principle for the existence and global exponential stability of the unique equilibrium point of a class of impulsive Cohen-Grossberg neural networks.
摘要:Purpose–The purpose of this paper is to propose a method to avoid hyperstaticity and eventually reduce the magnitude of undesired force/torques.The authors also study the influence of hyperstaticity on human motor control during a redundant task.Design/methodology/approach–Increasing the level of transparency of robotic interfaces is critical to haptic investigations and applications.This issue is particularly important to robotic structures that mimic the human counterpart’s morphology and attach directly to the limb.Problems arise for complex joints such as the wrist,which cannot be accurately matched with a traditional mechanical joint.In such cases,mechanical differences between human and robotic joint cause hyperstaticity(i.e.over-constrained)which,coupled with kinematic misalignment,leads to uncontrolled force/torque at the joint.This paper focusses on the prono-supination(PS)degree of freedom of the forearm.The overall force and torque in the wrist PS rotation is quantified by means of a wrist robot.Findings–A practical solution to avoid hyperstaticity and reduce the level of undesired force/torque in the wrist is presented.This technique is shown to reduce 75 percent of the force and 68 percent of the torque.It is also shown an over-constrained mechanism could alter human motor strategies.Practical implications–The presented solution could be taken into account in the early phase of design of robots.It could also be applied to modify the fixation points of commercial robots in order to reduce the magnitude of reaction forces and avoid changes in motor strategy during the robotic therapy.Originality/value–In this paper for the first time the authors study the effect of hyperstaticity on both reaction forces and human motor strategies.
摘要:Purpose-In recent years,it is imperative to establish the structure of manufacturing industry in the context of smart factory.Due to rising demand for exchange of information with various devices,and huge number of sensor nodes,the industrial wireless networks(IWNs)face network congestion and inefficient task scheduling.For this purpose,software-defined network(SDN)is the emerging technology for IWNs,which is integrated into cognitive industrial Internet of things for dynamic task scheduling in the context of industry 4.0.Design/methodology/approach-In this paper,the authors present SDN based dynamic resource management and scheduling(DRMS)for effective devising of the resource utilization,scheduling,and hence successful transmission in a congested medium.Moreover,the earliest deadline first(EDF)algorithm is introduced in authors’proposed work for the following criteria’s to reduce the congestion in the network and to optimize the packet loss.Findings-The result shows that the proposed work improves the success ratio versus resource usage probability and number of nodes versus successful joint ratio.At last,the proposed method outperforms the existing myopic algorithms in terms of query response time,energy consumption and success ratio(packet delivery)versus number of increasing nodes,respectively.Originality/value-The authors proposed a priority based scheduling between the devices and it is done by the EDF approach.Therefore,the proposed work reduces the network delay time and minimizes the overall energy efficiency.
摘要:Purpose-The advancements of deep learning(DL)models demonstrate significant performance on accurate pancreatic tumor segmentation and classification.Design/methodology/approach-The presented model involves different stages of operations,namely preprocessing,image segmentation,feature extraction and image classification.Primarily,bilateral filtering(BF)technique is applied for image preprocessing to eradicate the noise present in the CT pancreatic image.Besides,noninteractive GrabCut(NIGC)algorithm is applied for the image segmentation process.Subsequently,residual network 152(ResNet152)model is utilized as a feature extractor to originate a valuable set of feature vectors.At last,the red deer optimization algorithm(RDA)tuned backpropagation neural network(BPNN),called RDA-BPNN model,is employed as a classification model to determine the existence of pancreatic tumor.Findings-The experimental results are validated in terms of different performance measures and a detailed comparative results analysis ensured the betterment of the RDA-BPNN model with the sensitivity of 98.54%,specificity of 98.46%,accuracy of 98.51% and F-score of 98.23%.Originality/value-The study also identifies several novel automated deep learning based approaches used by researchers to assess the performance of the RDA-BPNN model on benchmark dataset and analyze the results in terms of several measures.
摘要:Purpose–Many applications in intelligent transportation demand accurate categorization of vehicles.The purpose of this paper is to propose a working image-based vehicle classification system.The first component vehicle detection is implemented by applying Dalal and Triggs’s histograms of oriented gradients features and linear support vector machine(SVM)classifier.The second component vehicle classification,which is the emphasis of this paper,is accomplished by an improved stacked generalization.As an effective ensemble learning strategy,stacked generalization has been proposed to combine multiple models using the concept of a meta-learner.However,it was found that the well-known meta-learning scheme multi-response linear regression(MLR)for stacked generalization performs poorly on the vehicle classification.Design/methodology/approach–A new meta-learner is then proposed based on kernel principal component regression(KPCR).The stacked generalization scheme consists of a heterogeneous classifier ensemble with seven base classifiers,i.e.linear discriminant classifier,fuzzy k-nearest neighbor,logistic regression,Parzen classifier,Gaussian mixture model,multiple layer perceptron and SVM.Findings–Experimental results using more than 2,500 images from four types of vehicles(bus,light truck,car and van)demonstrated the effectiveness of the proposed approach.The improved stacked generalization produced consistently better results when compared to any of the single base classifier used and four other beta learning algorithms,including MLR,majority voting,logistic regression and decision template.Originality/value–With the seven base classifiers,the KPCR-based stacking offers a performance of 96 percent accuracy and 95 percent k coefficient,thus exhibiting promising potentials for real-world applications.
摘要:Purpose–The purpose of this paper is to investigate the time-varying finite-time formation tracking control problem for multiple unmanned aerial vehicle systems under switching topologies,where the states of the unmanned aerial vehicles need to form desired time-varying formations while tracking the trajectory of the virtual leader in finite time under jointly connected topologies.Design/methodology/approach–A consensus-based formation control protocol is constructed to achieve the desired formation.In this paper,the time-varying formation is specified by a piecewise continuously differentiable vector,while the finite-time convergence is guaranteed by utilizing a non-linear function.Based on the graph theory,the finite-time stability of the close-loop system with the proposed control protocol under jointly connected topologies is proven by applying LaSalle’s invariance principle and the theory of homogeneity with dilation.Findings–The effectiveness of the proposed protocol is verified by numerical simulations.Consequently,the proposed protocol can successfully achieve the predefined time-varying formation in finite time under jointly connected topologies while tracking the trajectory generated by the leader.Originality/value–This paper proposes a solution to simultaneously solve the control problems of time-varying formation tracking,finite-time convergence,and switching topologies.
摘要:Purpose–The purpose of this paper is to improve the control precision of the station-keeping control for a stratosphere airship through the feedforward-feedback PID controller which is designed by the wind speed prediction based on the incremental extreme learning machine(I-ELM).Design/methodology/approach–First of all,the online prediction of wind speed is implemented by the I-ELM with rolling time.Second,the feedforward-feedback PID controller is designed through the position information of the airship and the predicted wind speed.In the end,the one-dimensional dynamic model of the stratosphere airship is built,and the controller is applied in the numerical simulation.Findings–Based on the conducted numerical simulations,some valuable conclusions are obtained.First,through the comparison between the predicted value and true value of the wind speed,the wind speed prediction based on I-ELM is very accurate.Second,the feedforward-feedback PID controller designed in this paper is very effective.Originality/value–This paper is very valuable to the research of a high-accuracy station-keeping control of stratosphere airship.
摘要:Autonomous control of Unmanned Aerial System(UAS)is that UASs can make decisions in the flight and carry out missions autonomously according to the scheduled tasks and rules through online sensing the surrounding situation.Through cooperation,UASs can share information among individual agents and work together to accomplish complicated mission which would not be possible for a single agent otherwise.With the development of UAS technology,autonomous control has become one of the hot topics and key technologies in UAS research field.
摘要:Purpose-The purpose of this paper is to provide a fault diagnosis method for rolling bearings.Rolling bearings are widely used in industrial appliances,and their fault diagnosis is of great importance and has drawn more and more attention.Based on the common failure mechanism of failure modes of rolling bearings,this paper proposes a novel compound data classification method based on the discrete wavelet transform and the support vector machine(SVM)and applies it in the fault diagnosis of rolling bearings.Design/methodology/approach-Vibration signal contains large quantity of information of bearing status and this paper uses various types of wavelet base functions to perform discrete wavelet transform of vibration and denoise.Feature vectors are constructed based on several time-domain indices of the denoised signal.SVM is then used to perform classification and fault diagnosis.Then the optimal wavelet base function is determined based on the diagnosis accuracy.Findings-Experiments of fault diagnosis of rolling bearings are carried out and wavelet functions in several wavelet families were tested.The results show that the SVM classifier with the db4 wavelet base function in the db wavelet family has the best fault diagnosis accuracy.Originality/value-This method provides a practical candidate for the fault diagnosis of rolling bearings in the industrial applications.
摘要:Purpose–The purpose of this paper is to develop an integrated,computer vision-based system to operate a commercial wheelchair-mounted robotic manipulator(WMRM).In addition,a gesture recognition interface system was developed specially for individuals with upper-level spinal cord injuries including object tracking and face recognition to function as an efficient,hands-free WMRM controller.Design/methodology/approach–Two Kinects cameras were used synergistically to perform a variety of simple object retrieval tasks.One camera was used to interpret the hand gestures and locate the operator’s face for object positioning,and then send those as commands to control the WMRM.The other sensor was used to automatically recognize different daily living objects selected by the subjects.An object recognition module employing the Speeded Up Robust Features algorithm was implemented and recognition results were sent as a commands for“coarse positioning”of the robotic arm near the selected object.Automatic face detection was provided as a shortcut enabling the positing of the objects close by the subject’s face.Findings–The gesture recognition interface incorporated hand detection,tracking and recognition algorithms,and yielded a recognition accuracy of 97.5 percent for an eight-gesture lexicon.Tasks’completion time were conducted to compare manual(gestures only)and semi-manual(gestures,automatic face detection,and object recognition)WMRM control modes.The use of automatic face and object detection significantly reduced the completion times for retrieving a variety of daily living objects.Originality/value–Integration of three computer vision modules were used to construct an effective and hand-free interface for individuals with upper-limb mobility impairments to control a WMRM.
摘要:Purpose-This purpose of this paper is to provide an overview of the theoretical background and applications of inverse reinforcement learning(IRL).Design/methodology/approach-Reinforcement learning(RL)techniques provide a powerful solution for sequential decision making problems under uncertainty.RL uses an agent equipped with a reward function to find a policy through interactions with a dynamic environment.However,one major assumption of existing RL algorithms is that reward function,the most succinct representation of the designer’s intention,needs to be provided beforehand.In practice,the reward function can be very hard to specify and exhaustive to tune for large and complex problems,and this inspires the development of IRL,an extension of RL,which directly tackles this problem by learning the reward function through expert demonstrations.In this paper,the original IRL algorithms and its close variants,as well as their recent advances are reviewed and compared.Findings-This paper can serve as an introduction guide of fundamental theory and developments,as well as the applications of IRL.Originality/value-This paper surveys the theories and applications of IRL,which is the latest development of RL and has not been done so far.
摘要:Purpose–The purpose of this paper is to present a control strategy which uses two independent PID controllers to realize the hovering control for unmanned aerial systems(UASs).In addition,the aim of using two PID controller is to achieve the position control and velocity control simultaneously.Design/methodology/approach–The dynamic of the UASs is mathematically modeled.One PID controller is used for position tracking control,while the other is selected for the vertical component of velocity tracking control.Meanwhile,fuzzy logic algorithm is presented to use the actual horizontal component of velocity to compute the desired position.Findings–Based on this fuzzy logic algorithm,the control error of the horizontal component of velocity tracking control is narrowed gradually to be zero.The results show that the fuzzy logic algorithm can make the UASs hover still in the air and vertical to the ground.Social implications–The acquired results are based on simulation not experiment.Originality/value–This is the first study to use two independent PID controllers to realize stable hovering control for UAS.It is also the first to use the velocity of the UAS to calculate the desired position.
摘要:Purpose – The purpose of this paper is to study the existence and exponential stability of anti-periodicsolutions of a class of shunting inhibitory cellular neural networks (SICNNs) with time-varying delays andcontinuously distributed delays.Design/methodology/approach – The inequality technique and Lyapunov functional method are applied.Findings – Sufficient conditions are obtained to ensure that all solutions of the networks convergeexponentially to the anti-periodic solution, which are new and complement previously known results.Originality/value – There are few papers that deal with the anti-periodic solutions of delayed SICNNs withthe form negative feedback – aij(t)αij(xij(t)).
摘要:Purpose-The purpose of this paper is to discuss a technique of restoring data from a broken/damaged near-field communication(NFC)tag whose coil is damaged and seems unrecoverable.Design/methodology/approach-This paper discusses a method to restore data from damaged NFC tags by designing a coil that matches the technical specification of NFC for restoring information.In this paper,an NFC tag with a broken antenna coil and its operational NFC chip is used for restoring data by making an external loop antenna for the same chip.Findings-If the NFC tag is damaged,the information stored on the tag can be lost and can cause serious inconvenience.This research provides an excellent mechanism for retrieving all the information accurately from a damaged NFC tag provided the NFC chip is not damaged.Research limitations/implications-One of the major limitations of this research is that the NFC chip remains intact without any damages.Data can only be recoverable if just the antenna of the NFC tag is damaged;any damage to the NFC chip would make it impossible for the data to be recoverable.Practical implications-The research is carried out with limited resources in an academic institute and hence cannot be compared to antenna designs of the industry.Furthermore,industry vendors are using aluminum to design the coil;however,in this study a copper coil is used for coil design since it is far less expensive than aluminum coil.Originality/value-NFC is a rather new short-range wireless technology and not much work is done in this field as far as antenna study is concerned.This study brings a technique to design a coil antenna for a damaged NFC tag to retrieve all the information without losing even a single bit of sensitive information.
摘要:Purpose–The purpose of this paper is to describe the specification language TML for adaptive mission plans that the authors designed and implemented for the open-source framework Aerostack for aerial robotics.Design/methodology/approach–The TML language combines a task-based hierarchical approach together with a more flexible representation,rule-based reactive planning,to facilitate adaptability.This approach includes additional notions that abstract programming details.The authors built an interpreter integrated in the software framework Aerostack.The interpreter was validated with flight experiments for multi-robot missions in dynamic environments.Findings–The experiments proved that the TML language is easy to use and expressive enough to formulate adaptive missions in dynamic environments.The experiments also showed that the TML interpreter is efficient to execute multi-robot aerial missions and reusable for different platforms.The TML interpreter is able to verify the mission plan before its execution,which increases robustness and safety,avoiding the execution of certain plans that are not feasible.Originality/value–One of the main contributions of this work is the availability of a reliable solution to specify aerial mission plans,integrated in an active open-source project with periodic releases.To the best knowledge of the authors,there are not solutions similar to this in other active open-source projects.As additional contributions,TML uses an original combination of representations for adaptive mission plans(i.e.task trees with original abstract notions and rule-based reactive planning)together with the demonstration of its adequacy for aerial robotics.
摘要:Purpose–Cooperative control of a group of unmanned aerial vehicles(UAVs)is an important area of research.The purpose of this paper is to explore multi-UAV control in the framework of providing surveillance of areas of interest with automatic loss detection and replacement capabilities.Design/methodology/approach–The research is based on the concept of the multi-agent system.The authors present the framework of the multi-agent and protocol design for monitoring the network of a group of UAVs.Findings–If one or more UAVs which is conducting a high priority surveillance task is lost,the system can self-arrange for another UAV to replace the lost UAV and continue to execute its task.This research provides an excellent design protocol for UAV loss detection and replacement scheme.Research limitations/implications–One of the major limitations of this research is that we have only two types of priority levels,high or low.If the priority is more than two levels,for example,high priority 1,high priority 2,or high priority 3,the replacement has not yet been implemented.Originality/value–This paper contributes to the following two aspects of the scientific knowledge.The first contribution is the design of an agent model which jointly considers system architecture,communication,control logic and target monitoring.The second contribution includes the decentralized and automatic UAV loss detection and replacement algorithm.
摘要:Purpose–The purpose of this paper is to propose a layered adjustable autonomy(LAA)as a dynamically adjustable autonomy model for a multi-agent system.It is mainly used to efficiently manage humans’and agents’shared control of autonomous systems and maintain humans’global control over the agents.Design/methodology/approach–The authors apply the LAA model in an agent-based autonomous unmanned aerial vehicle(UAV)system.The UAV system implementation consists of two parts:software and hardware.The software part represents the controller and the cognitive,and the hardware represents the computing machinery and the actuator of the UAV system.The UAV system performs three experimental scenarios of dance,surveillance and search missions.The selected scenarios demonstrate different behaviors in order to create a suitable test plan and ensure significant results.Findings–The results of the UAV system tests prove that segregating the autonomy of a system as multidimensional and adjustable layers enables humans and/or agents to perform actions at convenient autonomy levels.Hence,reducing the adjustable autonomy drawbacks of constraining the autonomy of the agents,increasing humans’workload and exposing the system to disturbances.Originality/value–The application of the LAA model in a UAV manifests the significance of implementing dynamic adjustable autonomy.Assessing the autonomy within three phases of agents run cycle(taskselection,actions-selection and actions-execution)is an original idea that aims to direct agents’autonomy toward performance competency.The agents’abilities are well exploited when an incompetent agent switches with a more competent one.
摘要:Purpose-The purpose of this paper is to use the internal model control to deal with nonlinear stable systems affected by parametric uncertainties.Design/methodology/approach-The dynamics of a considered system are approximated by a Takagi-Sugeno fuzzy model.The parameters of the fuzzy rules premises are determined manually.However,the parameters of the fuzzy rules conclusions are updated using the descent gradient method under inequality constraints in order to ensure the stability of each local model.In fact,without making these constraints the training algorithm can procure one or several unstable local models even if the desired accuracy in the training step is achieved.The considered robust control approach is the internal model.It is synthesized based on the Takagi-Sugeno fuzzy model.Two control strategies are considered.The first one is based on the parallel distribution compensation principle.It consists in associating an internal model control for each local model.However,for the second strategy,the control law is computed based on the global Takagi-Sugeno fuzzy model.Findings-According to the simulation results,the stability of all local models is obtained and the proposed fuzzy internal model control approaches ensure robustness against parametric uncertainties.Originality/value-This paper introduces a method for the identification of fuzzy model parameters ensuring the stability of all local models.Using the resulting fuzzy model,two fuzzy internal model control designs are presented.
摘要:Purpose–The purpose of this paper is to analyze the redistribution of dopant and radiation defects to determine conditions which correspond to decreasing of elements in the considered inverter and at the same time to increase their density.Design/methodology/approach–In this paper,the authors introduce an approach to increase integration rate of elements in a three-level inverter.The approach is based on decrease in the dimension of elements of the inverter(diodes and bipolar transistors)due to manufacturing of these elements by diffusion or ion implantation in a heterostructure with specific configuration and optimization of annealing of dopant and radiation defects.Findings–The authors formulate recommendations to increase density of elements of the inverter with a decrease in their dimensions.Practical implications–Optimization of manufacturing of integrated circuits and their elements.Originality/value–The results of this paper are based on original analysis of transport of dopant with account transport and interaction of radiation defects.