Employing a Gaussian Particle Swarm Optimization method for tuning Multi Input Multi Output-fuzzy system as an integrated controller of a micro-grid with stability analysis.
Mahdi MirMohammad DayyaniTole SutiknoMorteza Mohammadi ZanjirehNavid RazmjooyPublished in: Comput. Intell. (2020)
Keyphrases
- stability analysis
- particle swarm
- optimization method
- nonlinear systems
- adaptive neural
- fuzzy controller
- adaptive fuzzy
- sliding mode control
- evolutionary algorithm
- fuzzy systems
- fuzzy control
- nonlinear functions
- controller design
- optimization methods
- fuzzy model
- optimization algorithm
- genetic algorithm
- differential evolution
- membership functions
- control scheme
- fuzzy logic controller
- adaptive control
- fuzzy rules
- fuzzy sets
- fuzzy logic
- lyapunov function
- simulated annealing
- control law
- multi objective
- particle swarm optimization algorithm
- neural network
- control system
- inverted pendulum
- control strategy
- fuzzy neural network
- artificial neural networks
- genetic programming
- maximum likelihood
- particle swarm optimization
- evolutionary computation
- learning rate
- tracking error
- rule base
- mathematical model
- control algorithm
- closed loop
- computational intelligence
- input output
- fitness function
- metaheuristic
- optimal control
- neuro fuzzy
- real time
- feedback control
- fuzzy inference system
- pid controller
- convergence rate
- soft computing
- convergence speed