Robust control for uncertain networked control systems with random delays
Networked control systems (NCSs) are a type of distributed control systems where
sensors, actuators, and controllers are interconnected through a communication network.
This system setup has the advantage of low cost, °exibility, and less wiring, but it also
inevitably invites some delays and data loss into the design procedure.
The focus of this thesis is to address the problem of analysis and design of networked
control systems when the communication delays are varying in a random fashion. This
random feature of the time delays is typical for commercially used networks, such as a
DeviceNet (which is a controller area network (CAN)) and Ethernet network. Models for
communication network delays are ¯rst developed, in which Markov processes are used
to model these random network-induced delays. Based on such models, we establish
novel methodologies for stability analysis, control with disturbance attenuation, and
fault estimation for a class of uncertain linear/nonlinear uncertain NCSs with random
communication network-induced delays in both sensor-to-controller and controller-to-
actuator channels. Data packet dropouts in the communication channels also have been
taken into consideration in the modelling and design procedure.
The main technique used in this thesis is based on the Lyapunov-Razumikhin
method, which results in delay-dependent controllers. We ¯rst consider the design prob-
lems for uncertain linear NCSs. In this case, state feedback controllers and dynamic
output feedback controllers are designed to satisfy both stability and disturbance at-
tenuation requirements for this class of NCSs. Moreover, a robust fault estimator that
ensures the fault estimation error is less than a prescribed performance level is designed.
We further go on to address the control problems for uncertain nonlinear NCSs. The
nonlinear plant is ¯rst described by the T-S fuzzy model. Based on this model, stability
analysis, disturbance attenuation, and fault estimation problems are studied for uncer-
tain nonlinear NCSs. It should be noted that system uncertainties, disturbances and
noises are addressed in both cases.
The existence of such controllers and fault estimators are given in terms of the
solvability of bilinear matrix inequalities. Iterative algorithms are proposed to change
this non-convex problem into quasi-convex optimization problems, which can be solved
e®ectively by available mathematical tools.
Finally, to demonstrate the e®ectiveness and advantages of the proposed design
methodologies in this thesis, numerical examples are given in each designed control systems. The simulation results show that the proposed design methodologies can achieve
the prescribed performance requirements.