Study On Delay In Networked Control Systems

A major trend in modern industrial and commercial systems is to integrate computing, communication, and control into different levels of machine/factory operations and information processes. These new distributed control systems are called Networked Control System (NCS), which have many advantages such as simple connection, flexible configuration, convenient maintenance and sharing information. In network control systems (NCS),undetermined network delays always exist in the data communication between sensor and controller, controller and actuator. The delays on size and properties connect with network system structure, communication protocol and network load, and then it tend to be random, time varying and uncertain. The delay can cause significant deterioration of system performance, even make the system unstable. Therefore, it is especial important to analyze and research network delays.In this paper, networked control systems and their inherent characteristics are summarized. Reasons for time-delay occurred and the composition of the time delay are deeply analyzed. The results of simulation show that the delays affect control performance in network control systems and can destabilize the systems. The results of simulation also illuminate that the stability of closed-loop networked control systems is determined by the total delay in networked control systems.To solve the problem of the adverse effect of network-induced delay on the networked control systems, two novel methods of prediction compensation based on classical Smith predictor principle. The forward delays of network and controlled plant are removed from the close loop and appear as gain blocks before the output, and the time-variant uncertain delay in the return path is totally eliminated from the system. Further, it can cancel effects of delays of the network and controlled plant for system stability in the closed loop, and enhance control performance quality of the entire system. The novel Smith predictors realize double Smith dynamic prediction compensation controls on structure for delays of network and controlled plant. The novel Smith predictors are the real-time, on-line and dynamic predictors, and they do not include models of all network delays on actualization. Therefore network delays do not need to be measured, identified or estimated on line. As a consequence, it reduce requirement of clock synchronization. Furthermore, it avoids estimate errors which are brought due to inaccurate model, and avoid node memory resource to be wasted when network delays are identified. Simultaneity, it avoids compensation errors, which are brought by network delays owing to vacancy-sampling and multi-sapling.The new Smith predictors are applicable to scopes that network delays are random, time varying and uncertain, and larger than one, even tens of sampling periods, simultaneity there are data packet dropouts in the loops. The networked control systems based on the new Smith predictors are designed to validate the effectiveness of compensation. The effectiveness of compensation and control performance in network control systems using the new predictors are researched by simulation when the statistic characteristic is different and models of the predictor and true controlled plant are unmatched, or model parameters have bigger errors. The results of simulation show that systems, based on novel Smith predictors, have stronger robustness and desirable dynamic performance, when network delays are random, time-variant and uncertain, and possibly large compared to one, even tens sampling periods, and models of predictor and true controlled plant are unmatched. Therefore, the new control schemes of compensation are effective.Smith predictor is a relatively effective compensation model of the delay in control theory. But the Smith predictor is sensitive to the change of the system parameter, which is based on accurate mathematical model. The robustness of the Smith predictor is very bad when the system parameter vary greatly. Furthermore, the delays in networked control systems is random and uncertain, it is not applicable to apply the Smith predictor to the NCS directly. Considering the fuzzy controller is not sensitive to parameter variance, fuzzy PID control is combined to constitute a Smith estimation and fuzzy PID controller taking advantage of the merits of them. The accuracy requirement, required by the Smith predictor, to the models of predictor and the delay is improved by introducing fuzzy control. PID control, by which the error of the stable system can be eliminated, and fuzzy control act together, which make the entire system robust. The results of the simulation show that the method is effective.