非一致目标跟踪不确定系统自适应学习控制的切换算法

In many practical control systems, all kinds of uncertainties and the problem of non-uniform trajectory tracking are existing extensively, especially, the study on the problem of non-uniform trajectory tracking with parameter uncertainties is an important research topic in the field of iterative learning control. By considering different parameter forms and the problem of non-uniform trajectory tracking, the design and analysis of adaptive iterative learning controller for the nonlinear uncertain systems with time-varying parameters are studied in this project covering the following contents. (1) For linearly parameterized uncertain systems with time-varying parameter, combined with switching control theory, the adaptive switching iterative learning controller is designed and the convergence analysis is studied by the new-designed Lyapunov function to solve the problem of non-uniform trajectory tracking. (2) By combining the existing methods of dealing with time-varying parameters with neural network/fuzzy logic systems, based on switching control theory, research on design of adaptive switching iterative learning controller for the nonlinearly parameterized uncertain systems with time-varying parameters and the problem of non-uiform trajectory tracking is done. By selecting the appropriate Lyapunov function, analysis on convergence of the tracking error is studied theoretically. On this basis, the feasibility and effectiveness of the controller are demonstrated by the simulation of the practical system. The studies in this project will enrich and perfect the theory of iterative learning control. Hence, this work is of significant importance for academic and theory research in the intelligent robot system.

在很多实际控制系统中，各种不确定性，非一致目标跟踪问题都是广泛存在的，特别是对参数不确定性非一致目标跟踪问题的研究是迭代学习控制领域的一个重要研究方向。本项目以时变参数非线性不确定系统为研究对象，针对非一致目标跟踪问题，考虑不同的参数存在形式下的自适应迭代学习控制器的设计。主要研究内容包括：结合切换控制理论，研究时变参数线性参数化不确定系统的非一致目标跟踪问题，设计自适应切换迭代学习控制器，构造新型的Lyapunov函数并给出收敛性分析；将已有的处理时变参数的方法与神经网络或模糊逻辑系统相结合，基于切换控制理论，研究时变参数非线性参数化不确定系统的非一致目标跟踪问题，设计自适应切换迭代学习控制器，选取合适的Lyapunov函数证明误差的收敛性；在此基础上，针对实际系统的例子做仿真来证明控制器的可行性和有效性。本研究将进一步丰富和完善迭代学习控制理论，在智能机器人系统中具有重要的应用价值。

在很多实际控制系统中，各种不确定性，非一致目标跟踪问题都是广泛存在的，特别是对参数不确定性非一致目标跟踪问题的研究是迭代学习控制领域的一个重要研究方向。本项目以理论突破为重点，分别针对不同参数存在形式下的时变参数非线性不确定系统的非一致目标跟踪问题提出了自适应迭代学习控制器设计方案。构造出了新型的Lyapunov函数并给出收敛性分析。在理论研究的基础上，针对实际系统的例子做了仿真，证明了设计的控制器的可行性和有效性。课题主要围绕不同参数形式下的时变参数系统非一致目标跟踪问题的自适应迭代学习控制算法设计与稳定性分析问题进行研究。本研究进一步丰富和完善了迭代学习控制理论，在智能机器人系统中具有重要的应用价值。