Mircea-Bogdan Rdac

TL;DR: This paper proposes the design of fuzzy control systems with a reduced parametric sensitivity making use of Gravitational Search Algorithms (GSAs), and suggests a GSA with improved search accuracy.

TL;DR: The ACSS algorithm solves the optimization problems aiming to minimize the objective functions expressed as the sum of absolute control error plus squared output sensitivity function, resulting in optimal fuzzy control systems with reduced parametric sensitivity.

TL;DR: This paper suggests the optimal tuning of low-cost fuzzy controllers dedicated to a class of servo systems by means of three new evolutionary optimization algorithms: Gravitational Search Algorithm, Particle Swarm Optimization algorithm and Simulated Annealing algorithm.

TL;DR: The performance improvement of fuzzy control systems (FCSs) for three tank systems using iterative feedback tuning (IFT) and an IFT algorithm characterized by setting the step size to guarantee the FCS stability is proposed.

TL;DR: This paper proposes new stability analysis and convergence results applied to the Iterative Feedback Tuning (IFT) of a class of Takagi-Sugeno-Kang proportional-integral-fuzzy controllers (PI-FCs) and shows the performance improvement and advantages of the IFT approach to fuzzy control.