Application Of Sparrow Search Algorithm In PID Control System

The swarm intelligence optimization algorithm is a meta-heuristic algorithm inspired by the behavior of biological groups in nature.It mainly includes ant colony optimization algorithm,particle swarm optimization algorithm,artificial bee colony algorithm,artificial fish swarm algorithm and firefly algorithm.The sparrow search algorithm is a new type of swarm intelligence optimization algorithm proposed in2020.Because of its advantages of fast convergence speed and strong optimization ability,it has been more and more applied in various fields in recent years.In this paper,the application of sparrow search algorithm in PID control system is studied,and the sparrow search algorithm is applied to multivariable PID neural network optimization and engine PID control parameter tuning optimization.The main research contents are as follows:(1)In view of the fact that the initial weights of traditional PID neural network are often obtained randomly,the BP algorithm is used to train the network weights,and it is easy to fall into the local optimal value.The sparrow search algorithm is proposed to optimize the PID neural network.The sparrow search algorithm is used to optimize the initial weights of the PID neural network under offline conditions,and the optimal initial weights are obtained to control the nonlinear coupled system.Finally,the BP algorithm with self-learning ability is used to correct the network weights to avoid the network falling into the local optimum.The results show that the PID neural network controller optimized by the sparrow search algorithm can realize decoupling control and has good anti-interference ability.(2)Due to the low efficiency of parameter optimization and the low accuracy of the solution in the traditional PID controller in practical applications,firstly,based on the idea of numerical optimization,the fitness function weighted by the performance index was designed and improved,and the output of the actuator was added.The overshoot penalty mechanism of the fuel supply amount(fuel supply amount)is used to avoid the possible extreme overshoot and sharp fuel supply phenomenon of the fuel supply output by the actuator.The controller performs parameter optimization,and finally the simulation shows that the PID controller optimized by the sparrow search algorithm can effectively improve the great overshoot caused by the fuel supply of the aero-engine without affecting the speed of the aero-engine.On the feasibility of the PID control parameter optimization method.(3)Aiming at the problems of population diversity reduction and imbalance between exploration and utilization in the later stage of iteration,the sparrow search algorithm is improved by combining chaotic mapping and Gaussian mutation,and the improved chaotic sparrow search algorithm is used to optimize the parameters of aeroengine PID controller,The results show that the aeroengine PID controller optimized by chaotic sparrow search algorithm further reduces the great overshoot of engine fuel supply,and verifies the effectiveness of chaotic sparrow search algorithm in PID control parameter tuning method.