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This paper proposes a new method to design a fuzzy logic controller by genetic algorithms (GAs). The basic idea of this new methodology is to use a new way to mutate the chromosome. Bio-process control problem is used to compare the proposed mutation to traditional mutation. The results show that the proposed mutation efficiently improves GA's performance.
In the paper a new approach to a design of fuzzy controllers is proposed, based on an automatic selection of membership functions shapes. The automatization is achieved by optimization using a genetic algorithm relative to a chosen system performance criterion. The software system for fuzzy control of the cart-ball system is also described. The described system is developed in such a way that modules...
Different methods and schemes have been proposed in literature for tuning continuous and discrete PI (ProportionalIntegral) controllers. This paper proposes a scheme in which, this controller structure is explored in a different way, by looking its behavior as a lag compensator and tuning it by genetic algorithms. A difference with conventional approaches is the manner to evaluate every individual...
An adaptive fuzzy controller for controlling a multi-input-multi-output uncertain nonlinear system is proposed in this paper. The controller design is observer based since not all the system states are measurable. The fuzzy adaptive controller with modulated membership function (FAC_MMF) modulates the fuzzy sets on both the consequent and antecedent parts by adjusting a few parameters. As searching...
Computational intelligence competitions have recently gained a lot of interest. These contests motivate and encourage researchers to participate on them, and to apply their work areas to specific games. During the last two years, one of the most popular competitions held on computational intelligence in games conferences is the car racing competition. This competition combines the fun of driving to...
A fuzzy logic controllers based on Proportional Navigation Guidance law with minimal rule base was proposed in this study. The fuzzy logic controller is a knowledge based controller, which alters the value of the equivalent navigational constant to reap the maximum benefits in terms of the missile performance. Genetic algorithm was employed to optimize the number of rules, and was designed by selecting...
The translational oscillations with a rotational proof-mass actuator (TORA) is a well-known benchmark for examining the advantages and limitations of different nonlinear control design techniques. In this paper, a single-input-rule-modules (SIRMs) based type-2 fuzzy logic control scheme is proposed for this nonlinear multivariable system. And, genetic algorithms (GAs) are adopted to determine the...
A collision-avoidance planning method in multi-robot system based on genetic algorithm optimized by fuzzy logic control is designed, which include a simplified three-tier structure: avoid robot, avoid static obstacles and moving to the goal. These actions reason independently, and take information from different sensors as inputs; all the outputs are next anticipant movement of robot. Then, it synthesizes...
The genetic algorithms (GAs) are used to optimize design for a non-minimum phase (NMP) system with time delay. The intelligent composite control strategy can effectively eliminate the overshoot and undershoot of a NMP system. In order to guarantee the smooth switch of the control modes, the fuzzy inference and optimization are imported. The simulation results show that the performance of control system...
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