Adaptive digital control of Hammerstein nonlinear systems with limited output sampling. (English) Zbl 1126.93034

Ding, Feng; Chen, Tongwen; Iwai, Zenta

SIAM J. Control Optim. 45, No. 6, 2257-2276 (2007).

Summary: This paper is motivated by the practical control considerations that nonlinearity is abundant in industrial processes and output sampling rates are often limited due to hardware constraints. In particular, for a Hammerstein nonlinear sampled-data system in which the output sampling period is an integer multiple of the input updating period, we derive, by using a polynomial transformation technique, a mathematical model which is suitable for parameter estimation with dual-rate measurement data. Further, we present an adaptive control scheme for such a dual-rate nonlinear system; the parameter estimation-based adaptive algorithm can achieve virtually asymptotically optimal control and ensure that the closed-loop system is stable and globally convergent. The simulation results are included.

MSC:

93C40	Adaptive control/observation systems
93E10	Estimation and detection in stochastic control theory
93C10	Nonlinear systems in control theory
93B17	Transformations
93E24	Least squares and related methods for stochastic control systems

Keywords:

Hammerstein systems; sampled-data systems; multirate modeling; self-tuning regulator; adaptive control; dual-rate systems; convergence properties; least squares methods