We seek to achieve co-operating adaptive autonomous robots capable of functioning in a semistructured environment. Such an adaptive capacity implies a context sensitive control structure which has either been learnt or acquired through an evolution process. A method is therefore presented which uses a genetic algorithm to optimise the global strategy of two co-operating autonomous robots. The c...

This paper presents a novel indirect adaptive Power System Stabilizer (PSS) via a developed synergetic control methodology and fuzzy systems. Fuzzy system is utilized in an adaptive scheme to estimate the system using a nonlinear model. The synergetic control guarantees robustness of the controller and makes the controller easy to implement because of using a chatter free continuous control law...

In this document we carry out a comparative analysis of the application of Fuzzy Logic Controllers (hereinafter FLCs), Fuzzy Temporal Rules-Based Controllers (hereinafter FTRCs), Temporal Fuzzy Logic Controllers (hereinafter TFLCs) and Faded Temporal fuzzy Logic Controllers (hereinafter FTFLCs), to improve the adaptive distributed routing. To obtain a good knowledge base the controllers were ev...

On-line genetic algorithm-based fuzzy-neural sliding mode controller using improved adaptive bound reduced-form genetic algorithm Ping-Zong Lin a , Wei-Yen Wang b , Tsu-Tian Lee c & Chi-Hsu Wang a a Department of Electrical and Control Engineering , National Chiao Tung University , Hsinchu, Taiwan b Department of Applied Electronics Technology , National Taiwan Normal University , Taipei, 106 T...

Autonomous robots operating in unstructured environments clearly require some capacity for adaptive behaviour. This paper presents a method for achieving an adaptive response based on a multi-layer control architecture. The primary level of control is composed of the Behaviour Synthesis Architecture [1] which is continuously modified by a secondary layer, composed of a Fuzzy Logic controller. T...

This paper assesses the operator functional state (OFS) based on a collection of psychophysiological (i.e., cardiovascular and EEG) and performance measures. Two types of adaptive fuzzy model, namely ANFIS (adaptivenetwork-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved ...

in this paper, the fuzzy system has been used for fault detection and diagnosis of a yeast fermentation bioreactor based on measurements corrupted by noise. in one case, parameters of membership functions are selected in a conventional manner. in another case, using certainty factors between normal and faulty conditions the optimal values of these parameters have been obtained through the genet...

An adaptive backstepping fuzzy-immune controller for a class of chaotic systems is proposed. An adaptive backstepping fuzzy method and adaptive laws are used to approximate nonlinear functions and the unknown upper bounds of uncertainty, respectively. The proposed adaptive backstepping fuzzy-immune controller guarantees the stability of a class of chaotic systems while maintaining good tracking...

This paper develops a decentralized adaptive fuzzy control scheme for robot manipulators via a combination of genetic algorithm and gradient method. The controller for each link consists of a feedforward fuzzy torque-computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line by an improved genetic algorithm, that is to say, not only the param...