A PD-like self-tuning fuzzy controller without steady-state error
Fuzzy Sets and Systems
Real-valued genetic algorithms for fuzzy grey prediction system
Fuzzy Sets and Systems
Auto-tuning of multivariable PID controllers from decentralized relay feedback
Automatica (Journal of IFAC)
Theory and application of a novel fuzzy PID controller using a simplifier Takagi-Sugeno rule scheme
Information Sciences: an International Journal - Special issue analytical theory of fuzzy control with applications
Search space boundary extension method in real-coded genetic algorithms
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Neuro-Control and Its Applications
Neuro-Control and Its Applications
Two-level tuning of fuzzy PID controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
New methodology for analytical and optimal design of fuzzy PID controllers
IEEE Transactions on Fuzzy Systems
Tuning of the structure and parameters of a neural network using an improved genetic algorithm
IEEE Transactions on Neural Networks
Study on continuous network design problem using simulated annealing and genetic algorithm
Expert Systems with Applications: An International Journal
Study on continuous network design problem using simulated annealing and genetic algorithm
Expert Systems with Applications: An International Journal
Self-organizing genetic algorithm based tuning of PID controllers
Information Sciences: an International Journal
Evolutionary algorithms based design of multivariable PID controller
Expert Systems with Applications: An International Journal
Model-free adaptive control design using evolutionary-neural compensator
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Covariance matrix adaptation evolution strategy based design of centralized PID controller
Expert Systems with Applications: An International Journal
Chaos driven evolutionary algorithms for the task of PID control
Computers & Mathematics with Applications
Expert Systems with Applications: An International Journal
Computers & Mathematics with Applications
| Hi-index | 12.06 |
In this paper, we will propose a modified crossover formula in genetic algorithms (GAs), and use this method to determine PID controller gains for multivariable processes. It is well known that GA is globally optimal search method borrowing the concepts from biological evolutionary theory. In the traditional crossover fashion, only two parent chromosomes are usually used to be crossed by each other. The proposed algorithm, however, is designed to provide a more accurate adjusting direction for evolving offspring because of the use of multi-crossover genetic operations. Then we apply the innovative GA into the design of multivariable PID control systems for deriving optimal or near optimal control gains such that the defined performance criterion of integrated absolute error (IAE) is minimized as much as possible. Finally, a 2x2 multivariable controlled plant with strong interactions between input and output pairs will be illustrated to demonstrate the effectiveness of the proposed method. Some comparison results with the traditional GA and BLT method are also demonstrated in the simulation.