Gain adaptation of networked dc motor controllers based on qos variations

Abstract

Connecting a complex control system with various sensors, actuators, and controllers as a networked control system by a shared data network can effectively reduce complicated wiring connections. This system is also easy to install and maintain. The recent trend is to use networked control systems for time-sensitive applications, such as remote dc motor actuation control. The performance of a networked control system can be improved if the network can guarantee Quality-of-Service (QoS). Due to time-varying network traffic demands and disturbances, QoS requirements provided by a network may change. In this case, a network has to reallocate its resources and may not be able to provide QoS requirements to a networked control application as needed. Therefore, the application may have to gracefully degrade its performance and perform the task as best as possible with the provided network QoS. This paper proposes a novel approach for networked dc motor control systems using controller gain adaptation to compensate for the changes in QoS requirements. Numerical and experimental simulations, and prototyping, are presented to demonstrate the feasibility of the proposed adaptation scheme to handle network QoS variation in a control loop. The effective results show the promising future of the use of gain adaptation in networked control applications.

Controller design for Networked Control Systems—An approach based on L2 induced norm

“…A stabilizable discrete system (F, G) described by (1) can be controlled by a discrete optimal FSFC K which produces a closed-loop L 2 induced norm bound γ if there exist matrices Q = Q T ≥ 0, R = R T > 0, P = P T > 0 which satisfy the LMI…”

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“…The methodology presented in this paper can be used to design a time-driven FSFC for any discrete linear system described by (1) such that a specified L 2 induced norm bound γ is satisfied when it is connected as a NCS under arbitrary ineffective transmission arising out of data-loss and/or jitter, satisfying a rate constraint r = N M where N represents the number of consecutive samples of ineffective transmission in every M successive transmissions. Two approaches are followed viz.…”

“…(47) and setting β = 0.01, Q = β[C T C] and R =[1], it is seen that the LMI (19) is satisfied for a specified γ = 0.97 with…”

Modeling and Implementation for Embedded DC Motor Ethernet Control System

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