Abstract
The PID (proportional–integral–derivative) controller is the most widely used control method in modern engineering control because it has the characteristics of a simple algorithm structure and easy implementation. The traditional PID controller, in the face of complex control objects, has been unable to meet the expected requirements. The emergence of the intelligent algorithm makes intelligent control widely usable. The Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is a new evolutionary algorithm. Compared with other intelligent algorithms, the QUATRE algorithm has a strong global search ability. To improve the accuracy of the algorithm, the adaptive mechanism of online adjusting control parameters was introduced and the linear population reduction strategy was adopted to improve the performance of the algorithm. The standard QUATRE algorithm, particle swarm optimization algorithm and improved QUATRE algorithm were tested by the test function. The experimental results verify the advantages of the improved QUATRE algorithm. The improved QUATRE algorithm was combined with PID parameters, and the simulation results were compared with the PID parameter tuning method based on the particle swarm optimization algorithm and standard QUATRE algorithm. From the experimental results, the control effect of the improved QUATRE algorithm is more effective.
Highlights
The PID controller’s function is to determine the steady-state error value of the system from the actual given value and the actual output value of the control system.The steady-state error is linearly calculated by proportion, integral, and differential to form the control quantity
In many cases, PID controller parameter tuning is indispensable in the control system, as it is an important control method to achieve the purpose of control
Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is improved to optimize PID parameters, especially the first set value range of PID parameters, namely the particles under the different dimensions of search, all particles and random distribution patterns are initialized using the Sim function assigned to the PID controller parameters, through the system performance index function to calculate all the particle’s fitness, and the optimal adaptive value and position of particles are kept in the search space with the constant iterative update, which obtains the global optimal particle of the optimal
Summary
The PID controller’s function is to determine the steady-state error value of the system from the actual given value and the actual output value of the control system. To achieve a better control effect of the PID controller in complex controlled objects, this paper proposes a method of combining the new improved algorithm with PID parameters and proves its feasibility and superiority. The improved QUATRE algorithm was used to optimize the PID parameters, and the performance index function integral of time-weighted absolute error (ITAE) was used as the fitness function to find the optimal value through the improved optimization algorithm. At this time, the best individual was the global optimal parameter combination to achieve the optimal control of the control system
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