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Robust tracking control and signal estimation for networked control systems

Networked control systems (NCSs) are known as distributed control systems (DCSs) which are based on traditional feedback control systems but closed via a real-time communication channel. In an NCS, the control and feedback signals are exchanged among the system’s components in the form of information packages through the communication channel. The research of NCSs is important from the application perspective due to the significant advantages over the traditional point-to-point control. However, the insertion of the communication links would also bring challenges and constraints such as the network-induced delays, the missing packets, and the inter symbol interference (ISI) into the system design. In order to tackle these issues and move a step further toward industry applications, two important design problems are investigated in the control areas: Tracking Control (Chapter 2–Chapter 5) and Signal Estimation (Chapter 6–Chapter8). With the fact that more than 90% of control loops in industry are controlled by proportional-integral-derivative (PID) controllers, the first work in this thesis aims to propose the design algorithm on PID controllers for NCSs. Such a design will not require the change or update of the existing industrial hardware, and it will enjoy the advantages of the NCSs. The second motivation is that, due to the network-induced constraints, there is no any existing work on tuning the PID gains for a general NCS with a state-space model. In Chapter 2, the PID tracking control for multi-variable NCSs subject to time-varying delays and packet dropouts is exploited. The H_infty control is employed to attenuate the load disturbance and the measurement noise. In Chapter 3, the probabilistic delay model is used to design the delay-scheduling
tracking controllers for NCSs. The tracking control strategy consists of two parts:
(1) the feedforward control can enhance the transient response, and (2) the feedback
control is the digital PID control. In order to compensate for the delays on both
communication links, the predictive control scheme is adopted.
To make full use of the delay information, it is better to use the Markov chain to
model the network-induced delays and the missing packets. A common assumption
on the Markov chain model in the literature is that the probability transition matrix is
precisely known. However, the assumption may not hold any more when the delay is
time-varying in a large set and the statistics information on the delays is inadequate.
In Chapter 4, it is assumed that the transition matrices are with partially unknown
elements. An observer-based robust energy-to-peak tracking controller is designed for
the NCSs. In Chapter 5, the step tracking control problem for the nonlinear NCSs is in-
vestigated. The nonlinear plant is represented by Takagi-Sugeno (T-S) fuzzy linear model. The control strategy is a modified PI control. With an augmentation technique, the tracking controller design problem is converted into an H_infty optimization problem. The controller parameters can be obtained by solving non-iterative linear
matrix inequality conditions. The state estimation problem for networked systems is explored in Chapter 6. At
the sensor node, the phenomenon of multiple intermittent measurements is considered
for a harsh sensing environment. It is assumed that the network-induced delay is time-
varying within a bounded interval. To deal with the delayed external input and the
non-delayed external input, a weighted H_infty performance is defined. A Lyapunov-
based method is employed to deal with the estimator design problem. When the
delay is not large, the system with delayed state can be transformed into delay-free
systems. By using the probabilistic delay model and the augmentation, the H_infty
filter design algorithm is proposed for networked systems in Chapter 7. Considering
the phenomenon of ISI, the signals transmitted over the communication link would
distort, that is, the output of the communication link is not the same with the input
to the communication link. If the phenomenon occurs in the NCSs, it is desired to
reconstruct the signal. In Chapter 8, a robust equalizer design algorithm is proposed
to reconstruct the input signal, being robust against the measurement noise and the
parameter variations. Finally, the conclusions of the dissertation are summarized and future research
topics are presented. / Graduate

  1. http://hdl.handle.net/1828/4033
  2. H. Zhang, A. Saadat Mehr, and Y. Shi, “Improved robust energy-to-peak filtering for uncertain linear systems,” Signal Processing, vol. 90, no. 9, pp. 2667–2675, 2010.
  3. H. Zhang, Y. Shi and A. Saadat Mehr, “Robust energy-to-peak filtering for networked systems with time-varying delays and randomly missing data,” IET Control Theory & Applications, vol. 4, no. 12, pp. 2921–2936, 2010.
  4. H. Zhang, Y. Shi and A. Saadat Mehr, “Robust weighted H1 filtering for networked systems with intermittent measurements of multiple sensors,” In- ternational Journal of Adaptive Control and Signal Processing, vol. 4, no. 25, pp. 313–330, 2011.
  5. H. Zhang, Y. Shi and A. Saadat Mehr, “Robust H_infty PID control for multivari- able networked control systems with disturbance/noise attenuation,” Interna- tional Journal of Robust and Nonlinear Control, vol. 22, no. 2, pp. 183–204, 2012.
  6. H. Zhang, Y. Shi and A. Saadat Mehr, “Robust static output feedback control and remote PID design for networked motor systems,” IEEE Transactions on Industrial Electronics, vol. 58, no. 12, pp. 5396–5405, 2011.
  7. H. Zhang, Y. Shi and A. Saadat Mehr, “Robust non-fragile dynamic vibration absorbers with uncertain factors,” Journal of Sound and Vibration, vol. 330, no. 4, pp. 559-566, 2011.
  8. H. Zhang, Y. Shi, A. Saadat Mehr, and H. Huang, “Robust energy-to-peak FIR equalization for time-varying communication channels with intermittent observations,” Signal Processing, vol. 91, no. 7, pp. 1651–1658, 2011.
  9. H. Zhang, Y. Shi and A. Saadat Mehr, “Robust equalization for inter symbol interference communication channels,” IET Signal Processing, vol. 6, no. 2, pp. 73–78, 2012.
  10. H. Zhang, Y. Shi and A. Saadat Mehr, “On H_infty filtering for T-S fuzzy systems,” IEEE Transactions on Fuzzy Systems, vol. 20, no. 2, pp. 396–401, 2012.
  11. H. Zhang and Y. Shi, “Observer-based H_infty feedback control for arbitrarily time-varying discrete-time systems with intermittent measurements and input constraints,” ASME Transactions, Journal of Dynamic Systems, Measurement, and Control, accepted and in press, 2011.
  12. H. Zhang and Y. Shi, “Delay-dependent stabilization of discrete-time systems with time-varying delay via switching technique,” ASME Transactions, Journal of Dynamic Systems, Measurement, and Control, accepted and in press, 2011.
  13. H. Zhang, Y. Shi and A. Saadat Mehr, “Stability and stabilization of switched discrete-time systems with uncertain subsystem occurrence probabilities,” In- ternational Journal of Adaptive Control and Signal Processing, accepted and in press, 2011.
  14. H. Zhang, Y. Shi and M. Liu, “H_infty step tracking control for networked discrete-time nonlinear systems with integral and predictive actions,” IEEE Transactions on Industrial Informatics, accepted and in press, 2012.
  15. H. Zhang and Y. Shi, “Parameter-dependent H_infty filtering for linear parameter varying systems,” ASME Transactions, Journal of Dynamic Systems, Mea- surement, and Control, accepted and in press, 2012.
Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/4033
Date22 June 2012
CreatorsZhang, Hui
ContributorsShi, Yang
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf
RightsAvailable to the World Wide Web

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