The Research Of Nonlinear Ltr Control Method Based On Ph Neutralization Process

The pH neutralization process widely exists in the field of daily life and industrial process such as biomedicine,chemical production,and water treatment.However,the existing control methods have always had difficulty in the control of pH neutralization process due to its variable gain,strong non-linearity and difficulty in modeling.It is still a hot and difficult issue in industrial process control problem.Because of its robustness,good dynamic performance and simple structure,Loop Transfer Recovery method has always been a popular control method in the field of flight control,vehicle and ship motion control.The characteristics of the pH neutralization process are:sensitive control of the neutralization point,fast response speed,and needs faster and better tracking performance stronger robustness compared with other chemical reactions.In order to optimize the control of pH neutralization process and extend the LTR control method to the process industry,in this paper,two corresponding non-linear LTR control method for two different models of the pH neutralization process were designed,which achieved a good control effect.For the pH neutralization process strong acid equivalent model,the model was inverse S-transformed and a two-degree-of-freedom LTR controller is designed to achive the control of this model,and the tracking performance of the controller and robustness under different disturbances of acid and alkali is verified.At the same time,based on the frequency domain characteristics of the system,the sensitivity function is used to verify the robust performance of the system in the frequency domain,and a good control effect is achieved.Aiming at the pH neutralization process identification model,a Hammerstein model for pH neutralization was established in this paper.Genetic algorithm is used to optimize the initial value and domain value of neural network accelerates the network training process,and it was combined with Back Propagation neural network to establish the inverse model of system.The control of the inverse model by the LTR controller realizes the control of the Hammerstein model of the pH neutralization process.A good control effect is achieved,the LTR controller is further improved,and the application range of the LTR control is extended.For the problem that the LTR controller can not take into account the adjustment time and overshoot.This paper start with the weighting matrix parameters of controller,and design a parameter adaptive LTR control method.The adaptive rules based on error feedback adjustment and fuzzy rules are used respectively to make dynamic adjustment of the weighted matrix parameters.The simulation experiments show that both of the proposed adaptive adjustment rules can not only achieve the requirements of system robustness,but also speed up the system adjustment time and reduce the overshot of the system.This work completed the optimization of the LTR controller,is a proven method of improving the LTR.