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首页> 外文期刊>Transactions of the Institute of Measurement and Control >Direct adaptive model-free control of a class of uncertain nonlinear systems using Legendre polynomials
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Direct adaptive model-free control of a class of uncertain nonlinear systems using Legendre polynomials

机译:使用Legendre多项式的一类不确定非线性系统的直接自适应模型控制

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In this paper, a simple model-free controller for a class of uncertain nonlinear systems is presented using Legendre polynomials. According to the orthogonal functions theorem, Legendre polynomials are universal approximators. From this point of view, they are similar to fuzzy systems and can be used as a controller to approximate the ideal control law. Legendre coefficients are estimated online using the adaptation rule obtained from stability analysis. In comparison with fuzzy systems and neural networks, Legendre polynomials are simpler and less computational. Moreover, there are very few tuning parameters in Legendre polynomials. The case studies are an inverted pendulum and an articulated robot manipulator. Simulation results verify the effectiveness of the proposed controller and its robustness against large uncertainties. Comparisons with model-free controller using extended state observer and adaptive fuzzy systems show the superiority of proposed controller in disturbance rejection.
机译:本文使用Legendre多项式提出了一种用于一类不确定的非线性系统的简单模型控制器。根据正交功能定理,Legendre多项式是通用近似器。从这个角度来看,它们类似于模糊系统,可以用作控制法以近似理想的控制法。使用从稳定性分析获得的适应规则在线估计图例系数。与模糊系统和神经网络相比,Legendre多项式更简单,计算更少。此外,Legendre多项式中的调整参数很少。案例研究是倒挂摆和铰接式机器人操纵器。仿真结果验证了所提出的控制器的有效性及其对大型不确定性的鲁棒性。使用扩展状态观察者和自适应模糊系统的无模型控制器的比较显示了扰动抑制的提出控制器的优越性。

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