Performance Analysis of Particle Swarm Optimization and Genetic Algorithm in Energy-Saving Elevator Group Control System

2021 ◽  
pp. 497-511
Author(s):  
Mohammad Hanif ◽  
Nur Mohammad
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gang Tang ◽  
Peng Lu ◽  
Xiong Hu ◽  
Shaoyang Men

AbstractFor the offshore wave compensation control system, its controller setting will directly affect the platform's compensation effect. In order to study the wave compensation control system and optimization strategy, we build and simulate the wave compensation control model by using particle swarm optimization (PSO) to optimize the controller's control parameters and compare the results with other intelligent algorithms. Then we compare the response errors of the wave compensation platform under different PID controllers; and compare the particle swarm algorithm's response results and the genetic algorithm to the system controller optimization. The results show that the particle swarm algorithm is 63.94% lower than the genetic algorithm overshoot, and the peak time is 0.26 s lower, the adjustment time is 1.4 s lower than the genetic algorithm. It shows that the control effect of the wave compensation control system has a great relationship with the controller's parameter selection. Meanwhile, the particle swarm optimization algorithm's optimization can set the wave compensation PID control system, and it has the optimization effect of small overshoot and fast response time. This paper proposes the application of the particle swarm algorithm to the wave compensation system. It verifies the superiority of the method after application, and provides a new research reference for the subsequent research on the wave compensation control systems.


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