A SVM internal model control approach for unknown nonlinear discrete systems. (Chinese. English summary) Zbl 1212.93145

Kim, Chol Jin; Zhang, Naiyao

J. Tsinghua Univ., Sci. Technol. 49, No. 11, 1880-1885 (2009).

Summary: This paper presents an approximate internal model control approach for unknown nonlinear discrete SISO systems based on the support vector machine (SVM). The control law consists of a nominal controller and a robust controller. The nominal controller is derived from the SVM-NARMA approximate internal model by optimizing a quadratic performance index. The robust controller reduces the effects of the uncertainties. The stability and robustness of the closed-loop system are proved using the Lyapunov method. The results show that the method can be applied not only to systems with ill-defined relative degrees but also to non-minimum phase systems. Extensive simulations demonstrate the effectiveness of this control approach.

MSC:

93C10	Nonlinear systems in control theory
93B35	Sensitivity (robustness)
93D05	Lyapunov and other classical stabilities (Lagrange, Poisson, \(L^p, l^p\), etc.) in control theory

Keywords:

support vector machine; internal model control; unknown nonlinear discrete systems; non-minimum phase systems