|
STATE-DEPENDENT PARAMETER NONLINEAR SYSTEMS: IDENTIFICATION, ESTIMATION AND CONTROL
Peter C. Young, Andrew P. McCabe and Arun Chotai
Centre for Research on Environmental Systems and Statistics,
Lancaster University, Lancaster LA1 4YQ, England
A control system design procedure is proposed for a widely applicable class of discrete-time, non-linear systems in which the system nonlinearities are incorporated into a linear model structure in the form of State-Dependent Parameter (SDP) functions. The identification and estimation of both non-parametric and parametric SDP models is discussed briefly. The SDP NMSS model structure is defined, and the SDP Proportional-Integral-Plus (PIP) control algorithm is derived using an optimal LQ technique. The practical utility of the design methodology is illustrated by a numerical example.
Keywords: Discrete-time non-linear systems, Estimation, Identification, Non-minimal state space (NMSS) models, Non-linear Proportional-Integral-Plus (PIP) control, State dependent parameter (SDP), State feedback
Session slot T-We-A21: Posters of Nonlinear Systems/Area code 2c : Non-linear Systems
 | 