Development Of Predictive Control Strategy Using Self-Identification Matrix Technique (SMT)

This article describes an easy to use predictive control strategy using selfi-dentification matrix technique (SMT). A description for the condition number effect for suitable tracking behaviour has been analyzed. Simple rules based on the step response of the process are applied for the proposed matrix W-SMT. A new formula is produced for the main controller tuning parameter lambda(rho alpha). In the novel formula, lambda(rho alpha) is mainly extracted by regression analysis of first order plus dead time processes. Several plants are used to compare the proposed controller as function of the tuning parameters and tuning strategy. The effectiveness of the proposed strategy in wide ranging plants parameters has been compared with other techniques. Simulation results show that the use of the proposed strategy results in superior performance compared to previous techniques. Even though the tuning is based on approximation of actual processes with a first order plus dead time model. However, this strategy would not be suitable for systems with strong nonlinearities

Identification and self-tuning control of electro-pneumatic actuator system with control valve

In this paper, a mathematical modeling of pneumatic actuator system is developed by using RLS algorithm. An ARX model is chosen for the model structure. In order to cater the time-varying parameter of pneumatic system, a self-tuning controller is implemented based on the pole-assignment controller. An online RLS algorithm update the parameter estimation at every sample interval. The pole-assignment control parameter is then updated accordingly to the changes of the system parameters. Result of the system performance is compared with the conventional PID controller optimized by PSO algorithm. It is observed that the self-tuning controller performed well with almost zero error at steady state condition and overshoot less than 1%