Lyapunov-Based Model Predictive Control of Nonlinear Systems Subject to Data Losses

• Published in: IEEE transactions on automatic control Vol. 53; no. 9; pp. 2076 - 2089
• Main Authors: Munoz de la Pena, D., Christofides, P.D.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.10.2008; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Control system synthesis; Control systems; Control theory. Systems; Data integrity; Data loss; Design optimization; Dynamical systems; Exact sciences and technology; Fault-tolerant control systems; Invariants; Mathematical models; Networked control systems; networked control systems (NCS); Nonlinear control systems; Nonlinear dynamics; Nonlinear systems; Open loop systems; Optimization; Performance analysis; Predictive control; predictive control for nonlinear systems; Predictive models; process control applications; Process control. Computer integrated manufacturing; Sampling methods; Software; Studies; Asynchronous; process control applications; Non linear control; Lyapunov method; Control synthesis; Stability region; Invariant set; Hybrid system; Model predictive control; Chemical reactor; Sampling; Fault tolerant system; Predictive control; Mathematical programming; Process control; Distributed system; Equilibrium point; Closed feedback; Fault-tolerant control systems; Model reference adaptive control systems; Open loop; Distributed control; predictive control for nonlinear systems; Wireless network; networked control systems (NCS); Lyapunov function; Asynchronous transmission
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2008.929401

In this work, we focus on model predictive control of nonlinear systems subject to data losses. The motivation for considering this problem is provided by wireless networked control systems and control of nonlinear systems under asynchronous measurement sampling. In order to regulate the state of the system towards an equilibrium point while minimizing a given performance index, we propose a Lyapunov-based model predictive controller which is designed taking data losses explicitly into account, both in the optimization problem formulation and in the controller implementation. The proposed controller allows for an explicit characterization of the stability region and guarantees that this region is an invariant set for the closed-loop system under data losses, if the maximum time in which the loop is open is shorter than a given constant that depends on the parameters of the system and the Lyapunov-based controller that is used to formulate the optimization problem. The theoretical results are demonstrated through a chemical process example.