The main purpose of this article is to present the design, optimal setting and experimental study a multivariable PID controller supposed for electrohydraulic power steering system with load-sensing function. set performed through an optimization procedure based on genetic algorithm. embedded into microcontroller mobile machinery used in laboratory test rig investigation servo system. Results o...

A process model satisfies the integral controllability (IC) condition if the model can be used in a model-based controller that can be arbitrarily detuned without jeopardizing closed-loop stability. For decoupling multivariable control this requirement is equivalent to the inequality 1 ˆ Re 0 GG for the actual and estimated process steady-state gain matrices G and Ĝ . This necessitates experime...

This paper describes the fuzzy model reference adaptive controller design for nonlinear system based on TSK model. The stability of closed-loop system can be assured by Lyapunov function and the adaptive law is developed. The parameters of the controller can be regulated by the adaptive rules and the control scheme is applied on the automatic gauge control system and spherical motor system as t...

PID control systems are widely used as a basic control technology in the industrial control system today. However, tuning of PID control systems is not always easy, because of its simple control structure to wide classes of industrial control processes. In order to improve the issues, we developed a ModelDriven PID control system, named MD PID Control system, by extending the “model driven cont...

Abstract This paper explores the use of the Expectation-Maximisation (EM) algorithm as an alternative to the more usual gradient search methods for the computation of Maximum-Likelihood estimates of linear dynamic systems. This new approach is shown to afford several advantages, particularly where multivariable systems are concerned, since no a-priori parameterisation of the system is required....

Based on the Alopex evolutionary optimization algorithm with constrained T-S model, this paper presents an intelligent fuzzy predictive controller to solve the control difficulties of industry process with multi-variables. The T-S model is firstly established for nonlinear multivariable systems and its sequence parameters of fuzzy rules are identified by local recursive least square method. The...