Robust economic model predictive control of nonlinear networked control systems with communication delays

Summary In this work, we consider economic model predictive control of nonlinear networked control systems subject to external disturbances and communication delays in both sensor‐to‐controller and controller‐to‐actuator channels. The problem is addressed in the framework of the min‐max model predic...

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Vydáno v:International journal of adaptive control and signal processing Ročník 34; číslo 5; s. 614 - 637
Hlavní autoři: Mao, Yawen, Liu, Su, Liu, Jinfeng
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bognor Regis Wiley Subscription Services, Inc 01.05.2020
Témata:
Actuators
Algorithms
Communication
Compensation
Computer simulation
Control systems
Control theory
Controllers
Design optimization
Economic analysis
economic model predictive control
Economic models
input‐to‐state practical stability
Liapunov functions
networked control systems
Nonlinear control
Nonlinear systems
Predictive control
Robust control
transmission delays
ISSN:0890-6327, 1099-1115
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Shrnutí:Summary In this work, we consider economic model predictive control of nonlinear networked control systems subject to external disturbances and communication delays in both sensor‐to‐controller and controller‐to‐actuator channels. The problem is addressed in the framework of the min‐max model predictive control. First, a delay compensation strategy is proposed to minimize the impact of communication delays on the control performance. In the compensation strategy, once the receiver at the controller node receives a new state measurement, the controller generates a control sequence and sends the sequence to the actuator to compensate for delayed control inputs. Subsequently, the presence of disturbance is explicitly considered for robustness and the semi‐feedback min‐max optimization algorithm is used to design the control law based on the estimate of the current state reconstructed by the estimator. Furthermore, the input‐to‐state practical stability of the proposed approach is established by constructing a modified Lyapunov function. Simulation results of a numerical example and a chemical process example demonstrate the applicability and effectiveness of our approach.
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ISSN:0890-6327
1099-1115
DOI:10.1002/acs.3103