LQG benchmark based performance assessment for ILC based on two-dimensional model

With the rapid development of industrial batch processes, iterative learning control (ILC), which is a common and effective control strategy for batch processes, has received much attention. However, the performance assessment for ILC is still an open problem. A new method is proposed to assess the control performance of iterative learning control (ILC) using a two-dimensional (2-D) linear quadratic Gaussian (LQG) benchmark. First this study converts the batch process under ILC into a 2-D Roesser model. Then to assess the 2-D closed-loop system, the traditional LQG tradeoff curve is extended to the LQG tradeoff surface. The advantages of the proposed strategies are demonstrated by some simulation tests.