Iterative Learning Fault-Tolerant Control for Batch Processes

This paper develops an iterative learning reliable control (ILRC) scheme for batch processes with unknown disturbances and actuator faults. To develop the iterative learning control design, the batch process is transformed to, and treated as, a two-dimensional Fornasini-Marchsini (2D-FM) model. The relevant concepts of fault-tolerance along two-dimensional (2D) axes are introduced. The proposed control law can guarantee the closed-loop convergency along both the time and the cycle directions to satisfy H(infinity) performance, even with unknown disturbances and actuator faults. For performance comparison, a traditional fault-tolerant control law is also developed by considering the batch process in each cycle as a continuous process. Conditions for the existence of the proposed ILRC scheme are given as linear matrix inequalities. Applications to injection velocity control show that the proposed ILRC achieve the design objectives well, with performance improvement along both the time and cycle directions.