Model Approximate Of Complex System And Closed Loop Identification

In the field of the complex control process, object model often contains characters such as time delay, nonlinear, high order. Model reduction and approximation are often used in the design of model-based controller, and the complexity of the model determines the design difficulty of the controller. During the design process and implementation of the multivariate and multi-time-delay control system, the decoupled model is relatively complex. It is unable to design the controller directly due to the tedious derivation and lots of calculation which is not only time-consuming but also laborious. Therefore, the complex model order is required to be reduced. At present, the model approximation draws widely attention in the field of industrial control, especially in the predictive control and the process optimization based on model.Therefore, after a deep research on the related fields of model approximate method. The paper conducts the model identification method and model approximation method on multi-delay superposition model and multi-delay superposition model with non-minimum phase system in internal model control as well as high order delay model that often appears in industrial control.In the model identification and the model approximation, the main purpose is to solve the model structure and the optimization algorithm. This paper puts forward the second order plus time delay model with right half plane zero point to approximate the complex model of non-minimum phase. On the model approximation optimization algorithm, the paper uses three kinds of optimization algorithm, including the suboptimal algorithm in time domain, the frequency weighted recursive least squares algorithm (FRLS) in frequency domain and particle swarm optimization (PSO). The accuracies of the approximate model gotten by the three kinds of optimization algorithms were also compared. Simulation results show that using the second order non-minimum phase model structure, the gotten approximate model can fully reflect the dynamic characteristics of the original model, and the used three kinds of optimization algorithms all have a good optimization precision. The ISE index, the FISE index and the ITAE index are adopted respectively to get a comprehensive evaluation to analyze the advantages and disadvantages of the three kinds of model approximation algorithm. The paper is also used PSO algorithm as a tool for the model approximate of higher order delay model and complex model with additional multi-delay. It puts the traditional model approximate of pure mathematics theoretical derivate problem into a minimization optimization of PSO algorithm after setting the initial value on the range. The ITAE index are adopted to evaluate the model approximation algorithm.In addition, the actual industrial process is under the closed loop condition for the stability requirements. The paper also gives a two-steps closed loop identification method based on open loop transformation and a closed-loop identification method based on PSO. The simulation experiments prove the effectiveness of the given method.