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The convergence analysis of two-dimensional based integrated predictive iterative learning control (2D-IPILC) is presented for batch process in presence of output noises. In the 2D-IPILC method, iterative learning control (ILC) in the batch domain is integrated reasonably with real-time model predictive control (MPC) in the time domain. Based on the 2D system theory, system response of output tracking...
A new iterative learning control (ILC) method is presented for the trajectory tracking control of a kind of linear system. This new method does not need much detailed knowledge of the system. After a fixed reference batch is properly selected, the ratio of the input change and corresponding output change between the current and fixed reference batches multiplied by an exponential learning coefficient...
A new iterative learning control method is presented for the trajectory tracking control of linear time-variant systems. This new method does not need detailed knowledge of the controlled system. However, a reference batch is designed, in which some small change of the input trajectory in the current batch is applied to the controlled system, and then its output trajectory is obtained. The ratio of...
This paper presents an iterative learning control strategy for a fed-batch fermentation process using linearised models identified from process operational data. Off-line calculated control policies for batch fermentation processes may not be optimal when implemented on the processes due to model plant mismatches and/or the presence of unknown disturbances. In order to overcome the effect of model...
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