Research On Iterative Optimization Control Containing Modification Term Methods And Improvement For Batch Process

The batch process is characterized by little batch, multiple varieties, serialization, technology intensive and is widely used in modern process industry. With the expansion of the scope of application of industrial processes and the increasing complexity of batch process, the urgent need is to have the further study for batch process optimization control method. So it has great theoretical and practical significance in the optimization control of batch process.The iterative optimum control strategies based on iterative learning control algorithm make full use of the limitation of run-time and the repetitiveness of performing and can get through optimum control problems of systems with strong uncertainty, nonlinearity. In this paper, optimal control problem for the model mismatch of batch process is studied. First, the optimal control of batch processes and its development status are introduced, and the basic principle of iterative learning control method and iterative learning control with a correction term (ISOPE) are described in detail. The gradient estimation in ISOPE is an important factor in the performance of the method. Through simulation performance analysis of different ISOPE gradient estimation methods, it can be seen that features and the influence of different gradient estimation method to the optimization results. And on this basis, the introduction of the gradient error norm condition gives the upper bound in order to achieve a qualitative judgment as to its accuracy, thus, the method based on gradient error norm conditions ISOPE is proposed, simulation results demonstrate the effectiveness of the method. Due to the adjustment of coefficient of controlled variable, K value, which has a greater influence on the effect of the optimization process and the final performance, it is proposed that adjustment coefficient K has adaptive adjustment method through the effect analysis. Meanwhile, for the gradient weights with an effect on the iterative optimization, it is proposed adaptive method of the gradient correction weights and simulation results demonstrate the effectiveness of the method. Finally, on the basis of the above method, in view of the uncertainty of gradient direction correction, the ISOPE method based on the gradient error norm condition and gradient direction correction is proposed. It means that based on existing iterative optimization control information, the use of Gaussian mixture model can describe the direction of improvement, and it gives direction as the direction of the gradient correction combined ISOPE algorithm to optimize control. The simulation results demonstrate the effectiveness of the proposed method.