Robust receding horizon control of constrained nonlinear systems
Abstract
We present a method for the construction of a robust dual-mode, receding horizon controller which can be employed for a wide class of nonlinear systems with state and control constraints and model error. The controller is dual-mode. In a neighborhood of the origin, the control action is generated by a linear feedback controller designed for the linearized system. Outside this neighborhood, receding horizon control is employed. Existing receding horizon controllers for nonlinear, continuous time systems, which are guaranteed to stabilize the nonlinear system to which they are applied, require the exact solution, at every instant, of an optimal control problem with terminal equality constraints. These requirements are considerably relaxed in the dual-mode receding horizon controller presented in this paper. Stability is achieved by imposing a terminal inequality, rather than an equality, constraint. Only approximate minimization is required. A variable time horizon is permitted. Robustness is achieved by employing conservative state and stability constraint sets, thereby permitting a margin of error. The resultant dual-mode controller requires considerably less online computation than existing receding horizon controllers for nonlinear, constrained systems.>
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Model predictive control is an optimization-based control addressing optimal tracking control performance and input and state constraints.
“Model predictive control (MPC) [12], or receding horizon control [13], is an optimization-based control addressing optimal tracking control performance and input and state constraints, such as saturation of control inputs and physical limits of workspace and speed.”
From Incremental Model Predictive Control Exploiting Time-Delay Estimation for a Robot Manipulator (2022) · cites this paper as [13]
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Incremental Model Predictive Control Exploiting Time-Delay Estimation for a Robot Manipulator
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- Authors
- Michalska, H., & Mayne, D. Q.
- Affiliations
- McGill University (CA)
- University of California, Davis (US)
- Venue
- IEEE Transactions on Automatic Control
- Published
- 1993
- Volume
- 38
- Issue
- 11
- Pages
- 1623-1633
- ISSN
- 0018-9286 (ISSN-L)
- OpenAlex
- W2110703708
- Cited by
- 1,181
- References
- 18
- Citations by year
- 2026: 15 · 2025: 27 · 2024: 29 · 2023: 34 · 2022: 39 · 2021: 47 · 2020: 48 · 2019: 36 · 2018: 34 · 2017: 36 · 2016: 38 · 2015: 40 · 2014: 40 · 2013: 31 · 2012: 33
- FWCI
- 31.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Automatic Control (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
- Physical Sciences › Mathematics › Numerical Analysis › Advanced Optimization Algorithms Research
- Keywords
- dual-mode control, nonlinear systems, state and input constraints, model error, terminal equality constraints, linear feedback control, stability, near-optimal control, online algorithms
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