Abstract
Constraints are always present in practical control engineering applications. Control of system dynamics without due regard to the constraints can lead to sub-optimal behaviour and may even result in instability. Dynamic Programming provides an obvious means of handling process constraints. However the resulting algorithm is computationally demanding, making it incompatible for real-time implementation. This paper describes the Dynamic Programming solution of constrained model predictive control problem. A novel model structure is proposed such that the solution of the optimisation problem is not required at each controller interval making the method compatible for real-time implementation. The model has input-output structure with incremental actuation and incorporates the system constraints information. The optimal controller is shown to satisfy the constraints on both the actuations and controlled variables.
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