用虚拟目标值和支持向量机直接设计非线性控制器

对于复杂被控对象, 通常采用间接方法设计控制系统. 由于必须首先辨识对象模型, 因此这类方法往往耗时较多. 本文基于虚拟目标值反馈调整(VRFT)方法的思想, 利用支持向量机(SVM), 给出一种非线性控制器直接设计方法. 论文首先分析了VRFT方法与内模控制的关系, 接着给出了基于虚拟目标值(VR)和SVM的非线性控制器的结构和设计步骤. 仿真结果表明, 该方法具有良好的处理非线性和噪声的能力, 并且能消除稳态误差. 与经典基于神经网络(NN)的间接模型参考控制方法相比, 计算量大大降低.

Direct nonlinear controller design using virtual reference and support vector machine

Indirect methods are usually employed to design control systems for complicated industrial processes, which is often time-consuming because the process model must be obtained first by identification methods. Motivated by the virtual reference feedback tuning (VRFT) method, we propose a new direct nonlinear controller design method using virtual reference (VR) and support vector machine (SVM). Firstly, the relation between VRFT and internal model control (IMC) is analyzed; and then, the structure and design procedure of the proposed nonlinear controller are given. Simulation results demonstrate that this method can effectively deal with the noise and nonlinearity, and can eliminate the steady-state error. Moreover, the amount of calculation is reduced significantly in comparison with the normal indirect model reference control method using neural networks.