International Journal of Control, Automation, and Systems 2025; 23(3): 757-766
https://doi.org/10.1007/s12555-024-0667-9
© The International Journal of Control, Automation, and Systems
This study delves into a robust model predictive control method for impulsive positive system, incorporating control input/state constraints and interval uncertain. Initially, a state feedback controller is devised, and sufficient conditions for ensuring positivity and stability of the closed-loop impulsive positive system with interval uncertain are obtained utilizing the linear copositive Lyapunov function and the linear cost function. Subsequently, linear programming techniques are applied to solve the optimization problem, yielding optimal control inputs. This designed control strategy ensures the system’s positivity and stability while meeting control input/state constraints. Lastly, the validity of the approach is proved using numerical simulation examples.
Keywords Impulsive positive system, interval uncertain, linear programming, robust model predictive control.
International Journal of Control, Automation, and Systems 2025; 23(3): 757-766
Published online March 1, 2025 https://doi.org/10.1007/s12555-024-0667-9
Copyright © The International Journal of Control, Automation, and Systems.
Donglin Shi, Jun Ai, and Yuchang Feng*
Northeast Electric Power University
This study delves into a robust model predictive control method for impulsive positive system, incorporating control input/state constraints and interval uncertain. Initially, a state feedback controller is devised, and sufficient conditions for ensuring positivity and stability of the closed-loop impulsive positive system with interval uncertain are obtained utilizing the linear copositive Lyapunov function and the linear cost function. Subsequently, linear programming techniques are applied to solve the optimization problem, yielding optimal control inputs. This designed control strategy ensures the system’s positivity and stability while meeting control input/state constraints. Lastly, the validity of the approach is proved using numerical simulation examples.
Keywords: Impulsive positive system, interval uncertain, linear programming, robust model predictive control.
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