2D Terminal Constrained Model Predictive Iterative Learning Control of Batch Processes With Time Delay

Qiyuan Zhang,Jingxian Yu,Limin Wang

doi:10.1109/access.2019.2939428

Abstract

In this paper, a 2D terminal constrained model predictive iterative learning control method of batch processes with time delay is proposed to deal with time delay, input and output constraints, and disturbances in batch processes. Firstly, an iterative learning control law is designed for the given batch process; then the state error and output tracking error are introduced, and the original state-space model is converted to an equivalent 2D-FM model. In the meantime, an optimal performance index with terminal constraints is introduced, and an update law is designed to minimize the objective function under input and output constraints. The robust constraint set is adopted that the system state is converged to this set round the desired point. Then, based on the designed optimal performance index and Lyapunov stability theory, the MPC problem is transformed into a linear matrix inequality problem and a sufficient condition is given to ensure the robust asymptotically stability of the closed-loop system. Finally, the validity of the proposed method is proved by the simulation on a stirred tank.

Highlights

The batch process production is widely used in various industries such as fine chemicals, biopharmaceuticals and metalworking
Great achievements have been made in the researches on the batch process control [1]–[9]
How to effectively handle the issue of time delay in batch processes has been the focal point in this field

Summary

INTRODUCTION

The batch process production is widely used in various industries such as fine chemicals, biopharmaceuticals and metalworking. The advantages of the presented method: (1) under the 2D system theoretical frame work, the model predictive control is combined with iterative learning control to ensure the improvement of tracking performance along the direction of time and the direction of batch; (2) a min-max optimization and an update law are proposed to minimize the ‘‘worstcase’’ performance index in the infinite time domain, where the infinite time domain optimization problem is concerted to the LMI input and output constraints convex optimization problem by using the theory of linear matrix inequalities; (3) the designed controller has certain robustness, which can resist the effect of internal and external disturbances and ensure the systems’ stability. The feasibility and superiority of the presented method are proved through modeling and simulation

PROBLEM FORMULATION

CASE STUDIES

ROBUSTNESS TO REPETITIVE DISTURBANCES

ROBUSTNESS TO PARAMETER CHANGES

CONCLUSION