A Non-Linear Offset-Free Model Predictive Control Design Approach

This paper presents a non-linear model predictive control approach for offset-free tracking and the rejection of piece-wise constant disturbances. The approach involves augmenting the system’s state vector with the integral of the tracking error, enabling the design of a non-linear model predictive...

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Bibliographic Details
Published in:Actuators 2024-08, Vol.13 (8), p.322
Main Authors: Zhang, Haoran, Prempain, Emmanuel
Format: Article
Language:English
Subjects:
Closed loops
Control algorithms
Control systems
Control systems design
Controllers
Disturbances
Equality
Equilibrium
integral control
Methods
non-linear model predictive control
Nonlinear control
Nonlinear systems
optimal control
Predictive control
real-time control
Simulation
Simulation methods
Stability augmentation
State vectors
Tracking errors
water tank process
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Summary:This paper presents a non-linear model predictive control approach for offset-free tracking and the rejection of piece-wise constant disturbances. The approach involves augmenting the system’s state vector with the integral of the tracking error, enabling the design of a non-linear model predictive controller for this augmented system. Nominal closed-loop stability is enforced thanks to a terminal equality constraint and proven by a Lyapunov argument. Compared to the existing offset-free approaches in the literature, our method offers greater simplicity, as it does not rely on linear approximations of the system to control. Furthermore, it eliminates the need to estimate disturbances, a task that is especially challenging with non-linear systems. Comprehensive simulations and experimental tests are conducted according to a non-linear, coupled, two-tank laboratory experiment, demonstrating the robustness and effectiveness of the proposed approach.
ISSN:2076-0825
2076-0825
DOI:10.3390/act13080322