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Robust LQR Based ANFIS Control of x-z Inverted Pendulum

机译:基于鲁棒LQR的x-z倒立摆的ANFIS控制

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Inverted pendulum is a highly unstable, nonlinear and an under-actuated system. Its dynamics resembles many real-time systems such as segways, self-balancing robots, vertical take-off and landing aircraft (VTOL) and crane lifting containers etc. These real-time applications demand the need of a robust controller. In literature, many different control strategies have been discussed to stabilize an inverted pendulum, out of them, the most robust being fuzzy control and sliding mode control. The former is difficult to tune and has a problem of rule explosion for multivariable system, whereas the latter has a problem of discontinuity and chattering. To address the issues in fuzzy controller, a novel robust linear quadratic regulator (LQR) based adaptive-network fuzzy inference system (ANFIS) controller is proposed and implemented on the stabilization of x-z inverted pendulum. The proposed controller is able to solve the problem of robustness in the LQR controller as well as the difficulty in tuning along with rule explosion in fuzzy controller. Furthermore, the designed controller is tested for different pendulum masses and the results show that as compared with conventional PID controller, the proposed controller gives better performance in achieving lesser overshoot and settling time along with better robustness properties.
机译:倒立摆是一个高度不稳定,非线性和驱动不足的系统。它的动态特性类似于许多实时系统,例如电动踏板车,自动平衡机器人,垂直起降飞机(VTOL)和起重机起重集装箱等。这些实时应用需要强大的控制器。在文献中,已经讨论了许多用于稳定倒立摆的控制策略,其中最鲁棒的是模糊控制和滑模控制。前者难以调整,并且对于多变量系统存在规则爆炸的问题,而后者则具有不连续和颤动的问题。针对模糊控制器中存在的问题,提出了一种基于鲁棒线性二次调节器(LQR)的自适应网络模糊推理系统(ANFIS)控制器,并实现了x-z倒立摆的稳定化。所提出的控制器能够解决LQR控制器的鲁棒性问题以及模糊控制器的规则爆炸难以调节的问题。此外,对所设计的控制器进行了不同摆质量的测试,结果表明,与常规PID控制器相比,所提出的控制器在实现更少的过冲和稳定时间以及更好的鲁棒性方面具有更好的性能。

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