Genetic-Algorithm-Based Optimization of Ant Colony Controller for Fractional-Order Systems

Kumar, Ambreesh; Upadhyaya, Varun; Singh, Atul; Pandey, P. N.; Sharma, Rajneesh

doi:10.1007/978-981-13-1132-1_34

Cited by 3 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Examples of the commonly used cost functions include the integral square error (ISE) [60], the integral time absolute error (ITAE) [61], the weighted sum of the absolute errors [62], and others [63]. Also, the multiobjective functional optimization was used where several performance 6 Mathematical Problems in Engineering measures are optimized [64,65]. Among the most commonly used cost functions is the quadratic cost function [66].…”

Section: Sliding Mode Control Parameters Tuned By a Geneticmentioning

confidence: 99%

Synchronization of Synchronous Reluctance Motors Using the Discrete Sliding Mode Control Technique

Rahman

Zribi

Smaoui

2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The synchronous reluctance motor (SynRM) drive system is known to exhibit chaotic behavior under specified conditions. In this paper, the discrete-time sliding mode control (DSMC) technique is used to synchronize two SynRMs starting from different sets of initial conditions. The mixed variable speed reaching law is adopted in the design of the controller scheme. The parameters of the designed control scheme are tuned using a genetic algorithm (GA). Simulation results are presented to demonstrate the effectiveness of the proposed controller. In addition, the performance of the proposed control scheme is studied through simulations when bounded disturbances and mismatches between the parameters of the systems and those of the control scheme exist. The simulation results show that the designed control scheme is robust to bounded external disturbances and to mismatches in the parameters of the systems.

show abstract