Ahmet Onat 博士 特別講演会

Digital control systems where sensor, control computation and actuator functions reside on different computers connected by a communication network are called "Networked Control Systems" (NCS). The advantages of networked control systems are very diverse and address many of the demands of industrial development. However usage of networked control systems introduces time-delay uncertainty in closed-loop system dynamics caused mainly by the time sharing of the communication medium as well as network data loss. This has a destabilizing effect on system performance.

Although both computational power of computers and communication speed of networks has increased dramatically, their real-time characteristics have not evolved to match the requirements from a control point of view. New control methodologies that cope with these factors and even take advantage of them are emerging.

The presentation first examines some current methods in design and implementation of networked control systems that improve existing methods. Then a novel networked control system architecture that runs under non ideal network conditions with packet loss and noise is introduced. The proposed network control system architecture uses a model to predict the plant states into the future and generate corresponding control signals. Then, an array of the predicted control signals is sent to the actuator node side of the NCS rather than a single control signal like in basic networked control systems. This array of signals can control the plant if they are applied consecutively with sampling time intervals. However this is not necessary under ideal conditions where the network is lossless; only the first control signal in each array is applied to the plant as a newer packet arrives every sampling period. The remainder of the array of predicted control signals is only used when packet loss occurs. This approach enables the system to be controlled in a pre-simulated manner and stability can be maintained even with high packet loss probabilities.

Synchronization of the network elements becomes a problem in this approach since models are involved. Synchronizing the actuator and controller is done by an algorithm that can identify control signal arrays that have trustable information.

The proposed model based predictive networked control system architecture was tested on a DC motor. The effects of packet loss were examined to reveal that the packet loss does not cause destabilization of the system, when packet loss occurs and a control packet cannot be sent to the actuator node, which prevents the changes in reference from being applied to the plant. The overall effect is the retardation of the response of the plant to the reference. Effects of noise are also examined. Finally a method for determining the number of predictions to be made at the controller node (the prediction horizon) is suggested.