Design and implementation of linear robust networked control systems

Abstract

Networked Control Systems is a control system where the plant and the controller exchange information via a shared communication network and the network is considered as part of the closed loop control system. Unfortunately the network introduces network induced random varying time delays and data packet loss amongst the communication network imperfections. The network delays are considered to be between the controller and the actuator and between the sensor and the controller. These network imperfections degrade the performance of the closed loop control system and result in closed loop system instability. The complexity of measuring the communication network imperfection in networked control systems makes it difficult for the control engineers to develop methods for design of controllers that can incorporate and compensate these imperfections in order to improve the performance of the networked control systems. In this thesis a co-simulation toolset called LabNS2 is developed to address the first problem of measuring the communication network imperfections by providing an ideal environment that can be used to investigate the influence of network time delays or packet loss. The software environment of the toolset is based on LabVIEWTM and Network Simulator Version 2 (NS2). A new robust predictive optimal controller design method is developed to address the problem of the destabilising effect of the network induced time delay between the controller and the actuator. The design approach is based on time shifting of the optimisation horizon and a state predictor. The design of the controller is based on a model of the plant with delay in the control vector equal to the delay between the controller and the actuator or to the sum of the delays between the controller and the actuator and between the sensor and the controller. The time shifting approach allows the design of the controller to be performed for a model without time delay. Then the control action is based on the future values of the state space vector estimates. The state predictor is developed to predict these future values of the state using the present and past values of the state estimates and control actions. This technique is made possible by the use of the plant model Transition Matrix. A Discrete Kalman Filter is modified to address the problem of the destabilising effect of the network induced time delay between the sensor and the controller. An additional state estimation vector is added to the filter estimate at every current moment of time. iv The developed methods are implemented for networked control of a dish antenna driven by two stepper motors. The outcomes of the thesis can be used for the education and fundamental research purposes, but the developed control strategies have significant sense towards the Square Kilometer Array projects and satellite systems industry.