[[abstract]]A fuzzy sliding-mode controller was optimized through real-coded genetic algorithms and successfully implemented on an industrial XY table. The fuzzy sliding-mode controller is special type of fuzzy controller. By using the sliding surface, the fuzzy rule is simpler and the entire rule base is more compact. Thus, more easy to apply self-learning schemes. The real-coded genetic algorithm uses the internal floating-point representation of the computer system. With this advantage, the finite resolution problem of traditional genetic algorithm has been solved. The experimental results show the success of this approach.[[notice]]補正完
In this paper, the stability analysis of a genetic algorithm-based (GA-based) H1 adaptive fuzzy slid...
[[abstract]]In this article, a novel on-line genetic algorithm-based fuzzy-neural sliding mode contr...
[[abstract]]In this article, a novel on-line genetic algorithm-based fuzzy-neural sliding mode contr...
[[abstract]]In this paper, an intelligent fuzzy sliding mode control system, which cooperates with a...
[[abstract]]In this paper, genetic algorithms were applied to search a sub-optimal fuzzy rule-base f...
Abstract- In this paper, we design fuzzy sliding mode controller by real-value genetic algorithms. I...
[[abstract]]In this paper, we proposed a genetic-based sliding mode fuzzy controller design method t...
In this paper, we proposed a genetic-based sliding mode fuzzy controller design method to avoid the ...
In this paper, we demonstrate a PID controller design for high precision positioning table using a r...
Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three cont...
All control systems suffer from problems related to undesirable overshoot, longer settling times and...
[[abstract]]The paper presents an optimal fuzzy logic controller design using efficient robust optim...
Performing control is necessary for processes where a variable needs to be regulated. Even though co...
In this paper, we present three novel techniques for enhancing the power of a genetic algorithm (GA)...
This paper examines the applicability of genetic algorithms (GA) in the complete design of fuzzy log...
In this paper, the stability analysis of a genetic algorithm-based (GA-based) H1 adaptive fuzzy slid...
[[abstract]]In this article, a novel on-line genetic algorithm-based fuzzy-neural sliding mode contr...
[[abstract]]In this article, a novel on-line genetic algorithm-based fuzzy-neural sliding mode contr...
[[abstract]]In this paper, an intelligent fuzzy sliding mode control system, which cooperates with a...
[[abstract]]In this paper, genetic algorithms were applied to search a sub-optimal fuzzy rule-base f...
Abstract- In this paper, we design fuzzy sliding mode controller by real-value genetic algorithms. I...
[[abstract]]In this paper, we proposed a genetic-based sliding mode fuzzy controller design method t...
In this paper, we proposed a genetic-based sliding mode fuzzy controller design method to avoid the ...
In this paper, we demonstrate a PID controller design for high precision positioning table using a r...
Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three cont...
All control systems suffer from problems related to undesirable overshoot, longer settling times and...
[[abstract]]The paper presents an optimal fuzzy logic controller design using efficient robust optim...
Performing control is necessary for processes where a variable needs to be regulated. Even though co...
In this paper, we present three novel techniques for enhancing the power of a genetic algorithm (GA)...
This paper examines the applicability of genetic algorithms (GA) in the complete design of fuzzy log...
In this paper, the stability analysis of a genetic algorithm-based (GA-based) H1 adaptive fuzzy slid...
[[abstract]]In this article, a novel on-line genetic algorithm-based fuzzy-neural sliding mode contr...
[[abstract]]In this article, a novel on-line genetic algorithm-based fuzzy-neural sliding mode contr...