Python code for implementing a set of basic robust model predictive control (RMPC) algorithms for linear systems.

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RMPCPy

Python code for implementing a set of basic robust model predictive control (RMPC) algorithms for linear systems. The algorithms incorporated in this repository are for both linear time-invariant (LTI) and linear parameter-varying (LPV) systems. These algorithms are listed below:

  1. Shrinking Tube MPC for LTI Systems: Chisci L, Rossiter JA, Zappa G. Systems with persistent disturbances: predictive control with restricted constraints. Automatica 2001. Available at: https://www.sciencedirect.com/science/article/pii/S0005109801000516

  2. Rigid Tube MPC for LTI Systems: Mayne DQ, Seron MM, Raković SV. Robust model predictive control of constrained linear systems with bounded disturbances. Automatica 2005. Available at: https://www.sciencedirect.com/science/article/pii/S0005109804002870

  3. Disturbance Feedback Robust MPC for LTI Systems: Goulart PJ, Kerrigan EC, Maciejowski JM. Optimization over state feedback policies for robust control with constraints. Automatica 2006. Available at: https://www.sciencedirect.com/science/article/pii/S0005109806000021?via%3Dihub

  4. A Simple Robust MPC for LPV Systems: Bujarbaruah M, Rosolia U, Stürz YR, Borrelli F. A simple robust MPC for linear systems with parametric and additive uncertainty. IEEE American Control Conference 2021. Available at: https://ieeexplore.ieee.org/document/9482957

  5. Robust MPC for LPV Systems with Optimization-Based Constraint Tightening: Bujarbaruah M, Rosolia U, Stürz YR, Zhang X, Borrelli F. Robust MPC for linear systems with parametric and additive uncertainty: A novel constraint tightening approach. arXiv preprint, 2020. Available at: https://arxiv.org/abs/2007.00930

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Owner
Monimoy Bujarbaruah
PhD student in MPC Lab at UC Berkeley.
Monimoy Bujarbaruah
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