基于支持向量机的非线性离散动力学系统控制

提出了一种用支持向量机辨识系统状态空间模型的非线性离散动力学系统控制新方法. 在本方法中, 采用最小二乘支持向量机在每一个工作点辨识非线性系统的局部最优线性化模型. 针对该模型, 采用常规的线性控制方法在每个工作点设计局部线性控制器, 并在整个控制任务的每个工作点重复此设计过程.用该方法对两个典型的非线性离散系统采用极点配置技术进行了仿真验证, 结果显示系统对参考输入具有满意的跟踪性能, 证明该方法是有效和可行的.

Nonlinear discrete dynamic system based on support vector machines

A new approach to control a nonlinear discrete dynamic system based on support vector machines (SVM) is proposed in this paper, which depends on the identification of a state space model by SVM. Firstly, a local optimal linearization model is identified at every operating point by least squares support vector machines (LS-SVM), which belongs to the least squares version of SVM. For a linearization model, any linear controller design technique can be applied to design local linear controller at the operating point, and design procedure is repeated at every operating point in the control task. The proposed approach is applied to two typical examples. Pole placement technique is chosen as the linear design technique. Finally, simulation results show that the system has satisfactory tracking performance with reference input because of the desirable ability of SVM.