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Communication Dans Un Congrès Année : 2022

Predictive and Symbolic Control: Performance and Safety for Non-linear Systems

Résumé

Although Model Predictive Control (MPC) has proven its e ciency in the process operation and it is known for its high performance, it also su ers from design limitation. One of the fundamental issues for such an optimization-based technique is the di culty to guarantee recursive feasibility in the absence of terminal constraints, or alternatively, the complexity of design when a certain basin of a raction or a controlled invariant set needs to be certi ed for the closed loop in the most general nonlinear se ing. Based on symbolic control techniques, this paper proposes a simple and guaranteed solution for such problems. As a main result, a Symbolically guided Model Predictive Control scheme is developed. is controller is an improved version of the generic MPC approach such that the recursive feasibility is guaranteed through appending time-varying terminal constraints, carefully designed using the symbolic control approach, to the optimization problem of the original MPC formulation.
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Dates et versions

hal-03708834 , version 1 (29-06-2022)

Identifiants

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Zakeye Azaki, Antoine Girard, Sorin Olaru. Predictive and Symbolic Control: Performance and Safety for Non-linear Systems. CAO 2022 - 18th IFAC Workshop on Control Applications of Optimization, Jul 2022, Gif-sur-Yvette, France. pp.290-295, ⟨10.1016/j.ifacol.2022.09.039⟩. ⟨hal-03708834⟩
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