Abst rac t The slip power recovery configuration is an attractive scheme of variable speed drive, with high efficiency and low converter rating; however, high performance control has being difficult. In this paper, novel applications of fuzzy logic for the intelligent control of a slip power recovery system are presented. A direct fuzzy logic controller and an adaptive fuzzy controller, based o...

Since the large erecting mechanism has nonlinearities, parameter uncertainties and external disturbance, it is difficult to realize a model-based sliding mode control design. So a fuzzy adaptive sliding mode control scheme which combined fuzzy control with sliding mode control is proposed to achieve nonlinear control of the erecting mechanism. This control scheme is mainly use the fuzzy system ...

A new Multi-Stage Fuzzy (MSF) controller based on Multi-objective Harmony Search Algorithm (MOHSA) is proposed in this paper to solve the Load Frequency Control (LFC) problem of power systems in deregulated environment. LFC problem are caused by load perturbations, which continuously disturb the normal operation of power system. The objectives of LFC are to mini small size the transient deviati...

In this paper, a robust adaptive fuzzy control system using feedback linearization is proposed for a three-phase active power filter (APF). The APF system is divided into two separate loops: the current dynamic inner loop and the DC voltage dynamic outer loop. Adaptive fuzzy tracking control using feedback linearization is employed for the current dynamic inner loop to overcome the drawbacks of...

15. Supplementary Notes Supported by a rant from the U.S. Department of Transportation, University Transportation Centers Program. 16. Abstract Arterial traffic signal control is a very important aspect of traffic management system. Efficient arterial traffic signal control strategy can reduce delay, stops, congestion, and pollution and save travel time. Commonly used pre-timed or traffic actu...

Motivated by the need to develop more effective methods of controlling uncertain non-linear systems, this paper focus on developing an adaptive fuzzy model-based controller, in which the optimisation variables remain in the fuzzy domain. The scheme uses an on-line fuzzy identification scheme, which is able to generate a fuzzy relational model using the training data from the system. The propose...

This paper proposes a reinforcement fuzzy adaptive learning control network (RFALCON), constructed by integrating two fuzzy adaptive learning control networks (FALCON), each of which has a feedforward multilayer network and is developed for the realization of a fuzzy controller. One FALCON performs as a critic network (fuzzy predictor), the other as an action network (fuzzy controller). Using t...

A hybrid indirect and direct adaptive fuzzy output tracking control schemes are developed for a class of nonlinear multiple-input–multiple-output (MIMO) systems. This hybrid control system consists of observer and other different control components. Using the state observer, it does not require the system states to be available for measurement. Assisted by observer-based state feedback control ...