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Self-organizing and optimal control for nonlinear systems.

机译：非线性系统的自组织和最优控制。

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摘要

Vehicle formation control is one of important research topics in transportation. Control of uncertain nonlinear systems is one of fundamental problems in vehicle control. In this dissertation, we consider this fundamental control problem. Specially, we considered self-organizing based tracking control of uncertain nonaffine systems and optimal control of uncertain nonlinear systems. In tracking control of nonaffine systems, a self-organizing online approximation based controller is proposed to achieve a prespecified tracking accuracy, without using high-gain control nor large magnitude switching. For optimal control of uncertain nonlinear systems, we considered point-wise min-norm optimal control of uncertain nonlinear systems and approximately optimal control of uncertain nonlinear systems. In point-wise non-norm optimal control, optimal regulation and optimal tracking controllers were proposed with the aid of locally weighted learning observers. By introducing control Lyapunov functions and redefining the optimal criterions, analytic controllers were proposed and were optimal in the sense of min-norm. In approximately optimal control of uncertain nonlinear systems, adaptive optimal controllers were proposed with the aid of iterative approximation techniques and adaptive control. By iteratively learning, the difficulty of solving Hamilton-Jacobian-Bellman (HJB) equation is overcome. The proposed adaptive optimal algorithms can be applied to solve optimal control problem of a large class of nonlinear systems. To show effectiveness of the proposed controllers for above problems, simulations were done in computers.
机译：车辆编队控制是交通运输领域的重要研究课题之一。不确定非线性系统的控制是车辆控制中的基本问题之一。本文考虑了这一基本控制问题。特别地，我们考虑了基于不确定性非仿射系统的自组织跟踪控制和不确定性非线性系统的最优控制。在非仿射系统的跟踪控制中，提出了一种基于自组织在线逼近的控制器，以实现预定的跟踪精度，而无需使用高增益控制或大幅度切换。对于不确定非线性系统的最优控制，我们考虑了不确定非线性系统的逐点最小范数最优控制和不确定非线性系统的近似最优控制。在逐点非标准最优控制中，借助于局部加权学习观测器，提出了最优调节和最优跟踪控制器。通过引入控制Lyapunov函数并重新定义最佳准则，提出了解析控制器，该控制器在最小范数意义上是最佳的。在不确定非线性系统的近似最优控制中，借助于迭代逼近技术和自适应控制提出了自适应最优控制器。通过迭代学习，克服了求解Hamilton-Jacobian-Bellman（HJB）方程的困难。所提出的自适应最优算法可用于解决一类非线性系统的最优控制问题。为了显示所提出的控制器对上述问题的有效性，在计算机中进行了仿真。

著录项

  • 作者

    Dong, Wenjie.;

  • 作者单位

    University of California, Riverside.;

  • 授予单位 University of California, Riverside.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 98 p.
  • 总页数 98
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

  • 入库时间 2022-08-17 11:37:40

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