the paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. some mathematical vector models were obtained for control system multicriterion quality indices with due ...

this study proposes a combination of a fuzzy sliding mode controller (fsmc) with integral-proportion-derivative switching surface based superconducting magnetic energy storage (smes) and pid tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. the goal of design is to improve the dynamic response of power systems after load demand changes. in t...

this paper, presents a suitable control system to manage energy in distributed power generation system with a battery energy storage station and fuel cell. first, proper dynamic shape modeling is prepared. second, control system is proposed which is based on classic controller. this model is educated with genetic algorithm and particle swarm optimization. the proposed strategy is compared with ...

‎here‎, ‎we give a two phases algorithm based on integrating differential evolution (de) algorithm with modified hybrid genetic algorithm (mhga) for solving the associated nonlinear programming problem of a nonlinear optimal control problem‎. ‎in the first phase‎, ‎de starts with a completely random initial population where each individual‎, ‎or solution‎, ‎is a random matrix of control input v...