Tracking control with aperiodic sampling over networks with delay and dropout

Abstract

This paper introduces a discrete-time technique for output feedback tracking control with aperiodic sampling over networks suffering delay and dropout. Introducing the concept of pseudo sampling, NCS is modelled as a linear parameter varying (LPV) system. Two methods are explained to obtain a convex approximation of the uncertainty region. It is clarified how to perform the approximation to have the uncertainty space as small as possible. Using this uncertainty space, a polytopic approximation is obtained for the LPV model. The approximated model is used to synthesise a controller for set-point tracking and disturbance rejection. An observer is also synthesised based on this model. The simplicity of the model together with a small uncertainty space, results in less conservative LMI conditions. Compared to the existing results, an improved tracking performance is obtained. The final value theorem for discrete-time LTI systems with constant sampling period is extended to time varying sampling periods. This theorem is used to design a feedforward gain for zero steady-state tracking of staircase reference signals.

KEYWORDS:

• Aperiodic sampling
• conservatism
• discrete-time modelling
• disturbance rejection
• final value theorem
• linear parameter varying system
• networked control system
• observer
• pseudo sampling
• polytopic approximation
• switched linear system
• tracking control

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Kamran Mohajeri

Kamran Mohajeri was born in Iran in 1970. He received the B.Sc. degree from IAU Karaj branch in electronics engineering and the M.Sc. degree from IAU science and Research branch, Tehran in control engineering. He is currently pursuing PhD in control engineering with Tafresh University, Iran. He has twenty years of experience in RTU and SCADA systems. His research interests include networked control, robust control and intelligent control.

Ali Madadi

Ali Madady was born in Aqdash, Saveh, Iran in 1966. He received his B.Sc., M.Sc. and Ph.D. degrees in electrical and electronic engineering from Amir-Kabir University of Technology (Tehran Polytechnic), Iran, in 1989, 1993 and 2001, respectively. From 1991 to 1996, he was a part-time research member of Iranian Research Organization for Science and Technology (IROST). Also from 1994 to 2001, he was a part-time lecturer of Shamsipour Institute of Technology (SIT), Tehran, Iran. In 2001, he joined Tafresh University, Tafresh, Iran, where he is currently an Associate Professor and originator of Control Engineering Group. His research interests include iterative learning, adaptive control, robust control and nonlinear systems.

Babak Tavassoli

Babak Tavassoli received the BS in Electronics Engineering in 1998, MS and Ph.D. in Control Engineering in 2001 and 2009, all from the University of Tehran, Iran. From 2009 to 2010 he was with the Research Institute of Petroleum Industry working on control and monitoring in refineries. Since 2010, he has been with the K. N. Toosi University of Technology as an assistant professor. His activities include teaching BS and MS courses and supervising student theses or projects. His research interests are hybrid dynamical systems, networked control systems, and model predictive control. He is also interested in industrial automation technologies and industrial communication protocols.