Parameter optimised iterative learning control algorithm for multi-batch reactor

Abstract

A two-dimensional iterative learning PID control algorithm with Markov tuning method for batch reaction process is presented in this study. The learning algorithm with parameters tuned by Markov method can be explicitly tackling the repetitiveness of batch process, while achieve precise tracking of preset trajectory. It further shows that the control algorithm can guarantee convergence of the tracking error. Simulation results show that the parameters tuned by the Markov method can make the tracking error converge faster compared with the intimal control method.

Keywords

• adaptive control
• learning systems
• nonlinear control systems
• optimisation
• batch processing (industrial)
• iterative methods
• three-term control
• iterative learning control
• chemical reactors
• multibatch reactor
• two-dimensional iterative learning pid control algorithm
• markov tuning method
• batch reaction process
• learning algorithm
• markov method
• batch process
• tracking error
• intimal control method
• parameter optimised iterative learning control algorithm