The handling of various input constraints in the self-tuning generalized predictive control (STGPC) problem of ARIMAX/ARMAX systems is considered. The methods based on the Lagrange multipliers and Lemke’s algorithm are used to solve the constrained optimization problem. A self-tuning controller is implemented in an indirect way, and the considered constraints imposed on the control input signal...

Multivariable liquid level control is essential in process industries to ensure quality of the product and safety of the equipment. However, the significant problems of the control system include excessive time consumption and percentage overshoot, which result from ineffective performance of the tuning methods of the PID controllers used for the system. In this paper, fuzzy logic was used to t...

Model-reference adaptive control with neurofuzzy methodology is derived in this paper. Associate memory network(AMN) is investigated in detail to be the possible implementation as the direct self-tuning nonlinear controller. The essence of the neurofuzzy controller has been discussed and the local stability of the system is reached. The performance of the model-reference adaptive neurofuzzy con...

Since the emergence of PID controllers, control system engineers are in pursuit of more and more sophisticated versions of these controllers to achieve better performance, particularly in situations where providing a control action to even a minimal degree of satisfaction is a problem. This work is an attempt to contribute in this field. Variations in the values of weight, the friction coeffici...

This paper presents a new state-space self-tuning control scheme for adaptive digital control of continuous multivariable nonlinear stochastic hybrid systems with input saturation. Here, the continuous nonlinear stochastic system is assumed to have unknown system parameters, system and measurement noises, and inaccessible system states. The proposed method enables the development of a digitally...

Two controllers which extend the PD+I fuzzy logic controller to deal with the plant having time varying nonlinear dynamics are proposed. The adaptation ability of the first self tuning PD+I fuzzy logic controller (STPD+I_31) is achieved by adjusting the output scaling factor automatically thereby contributing to significant improvement in performance. Second controller (STPD+I_9) is the simplif...