Relay feedback-based Critical parameter estimation for First order plus dead Time Type plant in Networked control System Configuration

Most control strategies for networked control systems (NCS) assume that system model is known "a priori" which is, however, impractical in many industrial applications. To obtain the model of First Order Plus Dead Time type plant for networked control, this paper concentrates on model identification under the networked control environment. Ideal-relay feedback-based networked identification scheme is proposed here along with the new packet-based real-time queuing protocol to identify the plant's critical parameters, which takes into account the effect of nondeterministic factors such as network-induced delay, data packet disordering, and limited data packet loss between the sensor and controller as well as the controller and the actuator. Experimental results show that the proposed networked identification scheme can effectively overcome the impact of various network-induced nondeterministic factors for ideal-relay-based model identification in NCS.

[1]  Yuanqing Xia,et al.  Design and Practical Implementation of Internet-Based Predictive Control of a Servo System , 2008, IEEE Transactions on Control Systems Technology.

[2]  Karl Johan Åström,et al.  Relay Feedback Auto-tuning of Process Controllers – A Tutorial Review , 2002 .

[3]  Qing-Long Han,et al.  Communication Architecture Design for Real-Time Networked Control Systems , 2006, 2006 International Conference on Communications, Circuits and Systems.

[4]  C.C. Hang,et al.  A comparative performance study of PID auto-tuners , 1991, IEEE Control Systems.

[5]  N. Peric,et al.  ATM available bit rate congestion control with on-line network model identification , 2002, 9th International Conference on Electronics, Circuits and Systems.

[6]  James Moyne,et al.  Performance evaluation of control networks: Ethernet, ControlNet, and DeviceNet , 2001 .

[7]  Panos J. Antsaklis,et al.  On the model-based control of networked systems , 2003, Autom..

[8]  Panos J. Antsaklis,et al.  Guest Editorial Special Issue on Networked Control Systems , 2004, IEEE Trans. Autom. Control..

[9]  Ning Xi,et al.  Planning and control of Internet-based teleoperation , 1998, Other Conferences.

[10]  Hu Shousong,et al.  Brief Stochastic optimal control and analysis of stability of networked control systems with long delay , 2003 .

[11]  Hong Ye,et al.  Scheduling of networked control systems , 2001 .

[12]  Cheng-Ching Yu,et al.  Autotuning of PID Controllers: Relay Feedback Approach , 1999 .

[13]  Tianlong Gu,et al.  Queuing Packets in Communication Networks for Networked Control Systems , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[14]  Y. Tipsuwan,et al.  Control methodologies in networked control systems , 2003 .

[15]  Wei Zhang,et al.  Stability of networked control systems , 2001 .

[16]  Tore Hägglund,et al.  Automatic tuning of simple regulators with specifications on phase and amplitude margins , 1984, Autom..

[17]  J. W. Overstreet,et al.  An Internet-based real-time control engineering laboratory , 1999 .

[18]  Guo-Ping Liu,et al.  Design of a Packet-Based Control Framework for Networked Control Systems , 2009, IEEE Transactions on Control Systems Technology.

[19]  Minrui Fei,et al.  Gaussian-basis-function neural network control system with network-induced delays , 2002, Proceedings. International Conference on Machine Learning and Cybernetics.

[20]  Minrui Fei,et al.  A fast model identification method for networked control system , 2008, Appl. Math. Comput..