Adaptive Predictive Functional Control of a Class of Nonlinear Systems based on Dynamical Linearization
Abstract
This paper employs a concept of partial derivative called Pseudo-Partial-Derivative (PPD) to dynamically linearize nonlinear system, and the aggregation method is applied to deal with the future predictive PPD, then adaptive predictive functional control algorithm of nonlinear system is presented. The design demands low requirement for the model, which is based directly on PPD derived online from the input output data, and the given algorithm can also provide the bounded input output sequence and track setpoint without steady-state error. Simulations for the time-delay plant and the pH neutralization experiment of the chemical reaction process show that the proposed method is efficient for the system parameters perturbation and external disturbance.
