Hybrid fuzzy proportional-integral plus conventional derivative control of robotics systems
Autonomous robotic systems
Fuzzy PID Control of a Five DOF Robot Arm
Journal of Intelligent and Robotic Systems
PI-Fuzzy controllers for integral plants to ensure robust stability
Information Sciences: an International Journal
Design and analysis of direct-action CMAC PID controller
Neurocomputing
A two-stage design of adaptive fuzzy controllers for time-delay systems with unknown models
International Journal of Systems Science
Shifting nonlinear phenomena in a DC-DC converter using a fuzzy logic controller
Mathematics and Computers in Simulation
A new adaptive fuzzy controller with saturation employing influential rule search scheme (IRSS)
International Journal of Knowledge-based and Intelligent Engineering Systems
Optimisation criteria in development of fuzzy controllers with dynamics
Engineering Applications of Artificial Intelligence
Three-dimensional min--max-gravity based fuzzy PID inference analysis and tuning
Fuzzy Sets and Systems
A probabilistic fuzzy logic system: learning in the stochastic environment with incomplete dynamics
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Optimization design for PID parameter of mobile robot based on genetic algorithm
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
Genetic fuzzy self-tuning PID controllers for antilock braking systems
Engineering Applications of Artificial Intelligence
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
Fuzzy reasoning in fractional-order PD controllers
AIC'10/BEBI'10 Proceedings of the 10th WSEAS international conference on applied informatics and communications, and 3rd WSEAS international conference on Biomedical electronics and biomedical informatics
A multivariable predictive fuzzy PID control system
Applied Soft Computing
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The majority of the research work on fuzzy PID controllers focuses on the conventional two-input PI or PD type controller proposed by Mamdani (1974). However, fuzzy PID controller design is still a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. This paper investigates different fuzzy PID controller structures, including the Mamdani-type controller. By expressing the fuzzy rules in different forms, each PLD structure is distinctly identified. For purpose of analysis, a linear-like fuzzy controller is defined. A simple analytical procedure is developed to deduce the closed form solution for a three-input fuzzy inference. This solution is used to identify the fuzzy PID action of each structure type in the dissociated form. The solution for single-input-single-output nonlinear fuzzy inferences illustrates the effect of nonlinearity tuning. The design of a fuzzy PID controller is then treated as a two-level tuning problem. The first level tunes the nonlinear PID gains and the second level tunes the linear gains, including scale factors of fuzzy variables. By assigning a minimum number of rules to each type, the linear and nonlinear gains are deduced and explicitly presented. The tuning characteristics of different fuzzy PID structures are evaluated with respect to their functional behaviors. The rule decoupled and one-input rule structures proposed in this paper provide greater flexibility and better functional properties than the conventional fuzzy PHD structures