Research On Temperature PID Control Method Based On QUATRE Algorithm

PID(Proportional – Integral – Derivative)controller is the most representative control method in modern engineering control because of its simple model,high reliability and enduring.However,with the development of the times,the complexity of industrial control objects and the requirements for control accuracy are getting higher and higher.The traditional PID control can no longer meet the needs of control,especially for temperature control in thermal power plants,chemical plants,steel mills and other industries with large hysteresis and nonlinear control objects.In this paper,we propose a PID rectification method based on a parallel QUATRE(QUasi-Affine TRansformation Evolutionary)algorithm of Communication strategy and apply it to the electric furnace temperature control system,and we also propose a fuzzy PID control and BP(back propagation)neural network PID controller using the parallel QUATRE optimization of communication strategy for the electric furnace temperature intelligent control method.The main works are summarized as follows :(1)We propose an parallel algorithm based on communication strategy due to that original QUATRE algorithm tends to fall into the local optimal solution.In order to verify the feasibility of the proposed parallel QUATRE algorithm,four test functions are used to test the functions of the proposed improved QUATRE algorithm,the original QUATRE algorithm and the standard particle swarm algorithm.The results of the experiments verify the performance of the improved QUATRE algorithm in finding the optimal solution.(2)In response to PID control accuracy and efficiency requirements.The PID parameter tuning method of parallel QUATRE algorithm based on the communication strategy of this paper is proposed.Combining the mathematical model of electric furnace temperature control,a conventional PID control simulation model of electric furnace temperature control is established.The proposed method is used to simulate the controlled object,and the superiority of the intelligent algorithm is verified by comparison with the traditional Z-N(Ziegler –Nichols)method setting.The standard particle swarm algorithm is compared with simulation experiments,and the experimental results show that the temperature control performance of the electric furnace using this method is relatively excellent.(3)There is no systematic setting method for fuzzy PID quantization parameters,which leads to poor control effect.A fuzzy PID controller based on improved QUATRE algorithm is proposed.For the electric furnace temperature control model in this paper,a fuzzy PID controller is designed,and the quantization factor and the proportional factor are optimized by combining the algorithm with the fuzzy PID controller.The simulation verification is carried out through the mathematical model of the electric furnace temperature,and the comparison of the simulation effect of the conventional PID controller obtained by the empirical method with a set of quantitative parameter fuzzy PID controller and the Z-N tuning method is compared.(4)A BP-PID neural network controller is designed for the electric furnace temperature control system in this article.Aiming at the problem that BP neural network is easy to fall into local solution,which leads to low control accuracy,a BP neural network PID controller based on improved QUATRE algorithm is proposed.The improved QUATRE algorithm is used to adjust the initial weights of the BP neural network.Through the simulation experiment of the temperature control model,the simulation experiment results of the conventional BP-PID controller and the PID controller of the ZN engineering tuning method in temperature control are compared,and its good performance is verified.All the control strategies in this article are analyzed and summarized for the control of this article.The model gives a recommended strategy.