Model-Based Dissipative Control of Nonlinear Discrete-Time Systems over Networks

─The problem of output feedback control of nonlinear discrete-time systems connected over a network is studied in this paper. The Model-Based Networked Control Systems (MB-NCS) scheme is used to reduce communication to free up network resources for other applications. This is done by implementing an approximate model of the plant at the controller node to predict plant output values between sensor measurements. Communication is further reduced by considering an aperiodic event-triggered communication scheme that transmits data only when the error in the output exceeds a specified threshold. With the model and aperiodic updates, the plant is able to operate in open-loop for relatively large time intervals while still maintaining a desired level of accuracy in the control signal. When control systems are allowed to operate in open-loop like this, they often become sensitive to unmodeled dynamics. This paper considers model mismatch between the plant and model as well as bounded disturbances that may cause performance issues. In this paper, the model-based network architecture is represented as a standard negative feedback design problem for analysis purposes. Dissipative theory is applied to the feedback system for stability analysis and control synthesis. The results provide average squared boundedness with a constructive bound of the system output despite the presence of aperiodic updates, nonlinear dynamics, model uncertainties, and external disturbances.