Multiobjective evolution based fuzzy PI controller design for nonlinear systems

Authors:
G. L. O. Serra;C. P. Bottura
Affiliations:
Control and Intelligent Systems Laboratory, State University of Campinas, 400, 13083-852, Campinas-SP, Brazil;Control and Intelligent Systems Laboratory, State University of Campinas, 400, 13083-852, Campinas-SP, Brazil
Venue:
Engineering Applications of Artificial Intelligence
Year:
2006

Citing 8
Cited 11

Tuning of PID controllers based on gain and phase margin specifications

Automatica (Journal of IFAC)
Genetic algorithms + data structures = evolution programs (3rd ed.)

Genetic algorithms + data structures = evolution programs (3rd ed.)
Engineering intelligent hybrid multi-agent systems

Engineering intelligent hybrid multi-agent systems
Neural Networks: Theoretical Foundations and Analysis

Neural Networks: Theoretical Foundations and Analysis
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Adaptive Control Systems: Techniques and Applications

Adaptive Control Systems: Techniques and Applications
Fuzzy gain scheduling: controller and observer design based on Lyapunov method and convex optimization

IEEE Transactions on Fuzzy Systems
Survey Research on gain scheduling

Automatica (Journal of IFAC)

A new adaptive fuzzy controller with saturation employing influential rule search scheme (IRSS)

International Journal of Knowledge-based and Intelligent Engineering Systems
PID control of MIMO process based on rank niching genetic algorithm

Applied Intelligence
Development method for a robust PID fuzzy controller of LPV systems

FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Takagi-Sugeno fuzzy control method for nonlinear systems

CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Preferences in multi-objective evolutionary optimisation of electric motor speed control with hardware in the loop

Applied Soft Computing
Classical and fuzzy-genetic autopilot design for unmanned aerial vehicles

Applied Soft Computing
Survey paper: A survey on industrial applications of fuzzy control

Computers in Industry
Fuzzy frequency response: Proposal and application for uncertain dynamic systems

Engineering Applications of Artificial Intelligence
Tuning of PID controller based on a multiobjective genetic algorithm applied to a robotic manipulator

Expert Systems with Applications: An International Journal
Simple model-free controller for the stabilization of planetary inverted pendulum

Journal of Control Science and Engineering
Fuzzy sliding mode autopilot design for nonminimum phase and nonlinear UAV

Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

This work proposes a gain scheduling adaptive control scheme based on fuzzy systems, neural networks and genetic algorithms for nonlinear plants. A fuzzy PI controller is developed, which is a discrete time version of a conventional one. Its data base as well as the constant PI control gains are optimally designed by using a genetic algorithm for simultaneously satisfying the following specifications: overshoot and settling time minimizations and output response smoothing. A neural gain scheduler is designed, by the backpropagation algorithm, to tune the optimal parameters of the fuzzy PI controller at some operating points. Simulation results are shown to demonstrate the efficiency of the proposed structure for a DC servomotor adaptive speed control system used as an actuator of robotic manipulators.