Quasi-Min-Max MPC for Nonlinear System via Embedding Approach

Abstract:

A quasi-min-max model predictive control (MPC) algorithm is proposed for constrained nonlinear system via an embedding approach. The nonlinear system can be approximated by a linear parameter varying (LPV) model. And a method based on invariant set is proposed for the embedding model to reduce the computational complexity. The proposed method constructs a one-step invariant set comprises an interpolation between several pre-computed invariant sets at each time instant. Then control law is obtained by solving a constrained QP problem, which is also useful for the nonlinear system. The performances of the approach are presented via an example.

• Periodical: Advanced Materials Research (Volume 320)
• Pages: 481-486
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.320.481
• Online since: August 2011
• Authors: Min Zhao, Ping Ping Song
• Keywords: Invariant Set, Nonlinear System, Quasi-Min-Max MPC

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