Affiliation: | 1. Information and Control Institute, Hangzhou Dianzi University, Hangzhou, People's Republic of China Contribution: Writing - original draft;2. Information and Control Institute, Hangzhou Dianzi University, Hangzhou, People's Republic of China Contribution: Methodology;3. Information and Control Institute, Hangzhou Dianzi University, Hangzhou, People's Republic of China;4. Information and Control Institute, Hangzhou Dianzi University, Hangzhou, People's Republic of China Contribution: Resources |
Abstract: | It is known that the key indicators of batch processes are controlled by conventional proportional–integral–derivative (PID) strategies from the view of one-dimensional (1D) framework. Under such conditions, the information among batches cannot be used sufficiently; meanwhile, the repetitive disturbances also cannot be handled well. In order to deal with such situations, a novel two-dimensional PID controller optimized by two-dimensional model predictive iterative learning control (2D-PID-MPILC) is proposed. The contributions of this paper can be summarized as follows. First, a novel two-dimensional PID (2D-PID) controller is developed by combining the advantages of a PID-type iterative learning control (PIDILC) strategy and the conventional PID method. This novel 2D-PID controller overcomes the aforementioned disadvantages and extends the conventional PID algorithm from one-dimension to two-dimensions. Second, the tuning guidelines of the presented 2D-PID controller are obtained from the two-dimensional model predictive control iterative control (2D-MPILC) method. Thus, the proposed approach inherits the advantages of both PID control, PIDILC strategy, and 2D-MPILC scheme. The superiority of the proposed method is verified by the case study on the injection modelling process. |