PID type fuzzy controller and parameters adaptive method
Fuzzy Sets and Systems
A PID type fuzzy controller with self-tuning scaling factors
Fuzzy Sets and Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Particle swarm-based optimal partitioning algorithm for combinational CMOS circuits
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
Use of particle swarm optimization for machinery fault detection
Engineering Applications of Artificial Intelligence
A hybrid particle swarm optimization algorithm for the vehicle routing problem
Engineering Applications of Artificial Intelligence
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In this paper, a new PID-type fuzzy logic controller (FLC) tuning strategy is proposed using a particle swarm optimization (PSO) approach. In order to improve further the performance and robustness properties of the proposed PID-fuzzy approach, two self-tuning mechanisms are introduced. The scaling factors tuning problem of these PID-type FLC structures is formulated and systematically resolved, using a proposed constrained PSO algorithm. The case of an electrical DC drive benchmark is investigated, within a developed real-time framework, to illustrate the efficiency and superiority of the proposed PSO-based fuzzy control approaches. Simulation and experimental results show the advantages of the designed PSO-tuned PID-type FLC structures in terms of efficiency and robustness.