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Tuning of PID controller parameters is one of the usual tasks of the control engineers due to the wide applications of this class of controllers in industry. In this paper the Iterative Feedback Tuning (IFT) method is applied to tune the PID parameters. The main advantage of this method is that there is no need to the model of the system, so that is useful in many processes which there is no obvious model of the system. In many cases this feature can be so useful in tuning the controller parameters. The IFT is applied here to tune the PID parameters. Speed control of DC motor was employed to demonstrate the effectiveness of the method. The results is compared with other tuning methods and represented the good performance of the designed controller. As it is shown, the step response of the system controlled by PID tuned with IFT has more robustness and performs well. [ABSTRACT FROM PUBLISHER]

The focus of this paper is to design an adaptive robust decoupled fuzzy sliding-mode controller for a class of nonlinear systems. The proposed controller contains two terms; the adaptive fuzzy term and an adaptive robust term. The adaptive fuzzy term is used to improve the controlling of the preliminary oscillations, while the adaptive robust term is used to cope with uncertainties such as modeling errors and unknown sudden external disturbances, which are inevitable in practical applications. The proposed controller has an added advantage that it does not need the bound of uncertainties. Also, despite coping well with uncertainties the chattering which is a harmful phenomenon in practical applications is not observed in control signal. The asymptotic stability of the proposed controller is guaranteed via Lyapunov synthesis method. The proposed controller is applied to the highly nonlinear rotational translational actuator (RTAC) system via computer simulation. The simulation results show the effectiveness of the proposed controller in coping well with uncertainties while ensuring asymptotic stability. [ABSTRACT FROM PUBLISHER]

In this study, a sliding adaptive fuzzy controller is applied for chaos synchronization of two multi time-delayed Rossler systems. Two fuzzy systems with adaptation laws obtained from gradient descent method with novel cost function are employed to achieve two control laws. In this method, the first derivation of the Lyapunov function is considered as the cost function which must be minimized. To design the controller, two sliding surfaces are defined as the inputs of fuzzy systems. Lyapunov stability theory is used to guarantee the stability of error dynamics. The sliding adaptive fuzzy control scheme can be implemented without the requirement that the bounds of the uncertainties and the disturbances. It should be note that the control procedure is done with only two control signals. Simulation results of chaos synchronization for uncertain Rossler system are presented to demonstrate the validity and effectiveness of the proposed method for synchronization of two identical multi time-delayed chaotic systems. [ABSTRACT FROM PUBLISHER]