Research on State Feedback Controller of the Networked Control System with Long Delay

The use of avionics networks for flight control system has reduced aircraft weight, system installation, integration and maintenance costs as well as introduced time delays and structured uncertainties. This paper studies the robust stability and stabilisation problem of uncertain networked flight control system with random time delays. Some new sufficient criteria with simple mathematical forms for robust stability and stabilisation of networked flight control system are derived by a free weighting matrix approach. A memoryless state feedback robust controller and the maximum bound of time delay are obtained based on the solution of linear matrix inequalities (LMIs) which are established by the Lyapunov-Krasovskii stability theory. Numerical examples are given to illustrate the effectiveness of design procedure.

In order to solve the potential issues caused by network induced delays and dropouts which could arise the performance degradation and system instability, this paper studies the stochastic stability problem of Networked control systems (NCSs) with arbitrary time delays and packet dropouts by using an active time-varying sampling method. The random time delays and successive packet dropouts are driven by two separately Markov chains and NCSs are modelled as a discrete time Markovian jump linear systems. Based on Lyapunov approach, sufficient conditions for the stochastic stability of the networked control system are derived and stabilization controller is designed in terms of linear matrix inequalities (LMIs) correspondingly. Gridding approach is introduced to guarantee the solvability of the LMIs with finite jump modes. A numerical example is given to illustrate the effectiveness of the proposed method which stabilizes the NCS with random time delays and packet dropouts.

This study addresses the stabilisation problem for networked control systems with random time delays. Depending on the prior knowledge, two kinds of time delays are considered. One is the Markov delay, and the other one is the arbitrary-bounded delay. By making full use of the most recent delay information, a novel controller with delay-dependent control gains is constructed, and the stability conditions of the closed-loop system with either Markov delays or arbitrary-bounded delays are derived. Cone complementarity linearisation approach is employed to design the stabilising controllers. Finally, simulation and experimental results are given to illustrate the effectiveness of the obtained results.

The random time delay brings great challenges to the controller design for the Internet-based teleoperation system, the worst case is that it can destabilize the Internet-based teleoperation system. This paper first gives a brief historical preview of bilateral passive control theory, and then a direct passive scattering transform method, extending the passive bilateral control method to the Internet-based random time delay teleoperation system, is advanced to guarantee the teleoperation system's stability with any non-symmetric random network time delay. Finally, a virtual master-slave manipulator bilateral control scheme is designed for mobile robot teleoperation based on the passive scattering transformation method, and simulations are carried out to verify the results at the end of this paper. © 2012 IEEE.

Based on the controlled process that is linear time-invariant system, the network-induced long time delay is viewed as time-varying parameter uncertainties. The uncertainty parameters model of networked control systems with long time delay is set up. The existing conditions of asymptotic stability for networked control system with long time delay are presented by Lyapunov method and robust control theory. The design method of stabilization controller for networked control system is proposed in terms of linear matrix inequalities. In the end the simulation based on the networked control unstable system is studied. The simulation results show the proposed controller is feasible and effective.

This paper presents a novel predictive control scheme with an enhanced Smith predictor for a networked control system with random time delays and system uncertainties. In the scheme, time axis is partitioned into equidistant small intervals to limit the continuous time varying delays into several discrete values. The stability of the networked control system is achieved by establishing an offline database and an online update strategy for Smith predictor, which reduces the reliance on the determined model of delay and system uncertainties in comparison with conventional Smith predictor. In this way, a sequence of finite forward predictive control signals of all possible time delays can be generated in advance and the actual delays will be compensated in real time when achieving the real delay information. Illustrative examples are given to demonstrate the effectiveness and robustness of the proposed predictive methods towards the random transmission delays and system uncertainties integrated in the networked control system.

Markovian jumping systems have arisen naturally in the mathematical modeling of phenomena spanning disciplines in the social sciences, natural sciences, and engineering. This kind of stochastic dynamical systems can be employed to model the dynamics when parameters are subject to random abrupt changes due to sudden environment changes, subsystem switching, system noises, executor faults, and so forth. Much attention has been given to modeling, optimization, and real applications of such stochastic dynamical systems in the literature in recent years. As the advanced control and optimization will provide a basis for the design and application of such stochastic systems, these advanced techniques would result in substantial and sustainable benefits. The accepted papers in this special issue include stochastic stability, stabilization, stochastic control optimization, system modeling and identification methods, predictive control, signal processing, robust filtering, multiagent systems, networked control systems, time-delayed systems, neural networks, the Takagi-Sugeno fuzzy systems, simulated annealing, and fault detection methods.

In this paper, static output feedback stochastic stabilization and disturbance attenuation issues for a class of discrete-time Networked Control Systems (NCSs) subject to random failures and random delays are addressed. The different random processes are modeled as Markovian chains, and the resulting closed-loop system belongs to the class of discrete-time Markovian Jump Linear Systems (MJLS). Results are formulated as matrix inequalities. A numerical algorithm based on nonconvex optimization is provided and its running is illustrated on a classical example from literature.

This paper concentrates on the nonlinear filtering for systems with event-triggered data transmission and random time delays. A stochastic event-triggered sensor schedule is introduced to reduce the excessive measurements, which achieves a lower communication rate with a good estimation performance. The time delay is modeled by a Poisson distribution, and a D-length buffer is used to retrieve partly delayed measurements. Subsequently, a nonlinear filter is designed for the state estimation with event-triggered data transmission and random time delays. An example is provided to verify the performance of the proposed algorithm.

The problem of stabilization of networked control systems (NCSs) with data packet dropout is studied. Sufficient conditions are presented on the stability and stabilization of the NCSs with packet dropout. The novelty of this work lies in that NCSs with arbitrary but finite data packet dropout are modelled as switched linear systems, and this enables us to apply the result of switched systems to the analysis and synthesis of such NCSs. The admissible upper bound of the dropped packets can be determined by a set of linear matrix inequalities (LMIs) which guarantee the stability of the NCSs. Stabilizing controllers (via state feedback and static output feedback) can be constructed by solving a set of LMIs. Also, for an NCS with a convergence rate constraint, similar results are obtained. Examples are worked out to illustrate the effectiveness of the proposed method

The aim of this paper is to develop a novel robust variable sampling period controller (RVSPC) for networked control systems (NCSs) in the presence of random time delays and packet losses. Different from the existing control techniques for NCSs, the RVSPC controller is constructed as a hybrid robust controller with the adaptive variable sampling period. To adapt to the delay variation, a so-called variable sampling period adjuster based on a time delay predictor (TDP) and a time delay and packet detector is designed to adjust effectively the sampling period. To efficiently compensate for the random delays and packet losses, the hybrid controller is designed as a combination of a quantitative feedback theory (QFT)-based robust controller and a robust state feedback controller (RSFC) with adaptive control gain. A smart switch based on the TDP is then used to select properly the main control unit as the QFT or RSFC corresponding to the current delay and packet loss status. Illustrative examples with NCSs including both computation and communication delays and packet losses are finally carried out to illustrate the effectiveness of the proposed method.

This paper focuses on a new H∞ controller design issue for networked control systems with external disturbance as well as random time delays and packet dropouts in forward and feedback channels, which are modeled by multiple Markov chains in a unified style. The output feedback controller is designed to stabilize the networked control system and also achieves the prescribed H∞ disturbance attenuation level. The addressed controller design problem is transformed into a nonlinear minimization problem with LMI constraints. An illustrative example is provided to show the effectiveness of the proposed methods. Copyright © 2014 John Wiley & Sons, Ltd.

This paper investigates the quantized guaranteed cost control design (GCCD) for networked control systems (NCSs) with interval parameters and random delays. A comprehensive NCS model is established, incorporating three key elements: Interval parameters represented as convex combinations of endpoints, random delays governed by a Markov chain, and quantization effects described by the sector‐bound method. Based on the model, sufficient conditions for the GCCD are derived using the Lyapunov functional approach combined with the cone complementary linearization (CCL) algorithm. Numerical simulations demonstrate the efficacy of the proposed method.

The problem of stabilization of networked control systems (NCSs) with time-varying transmission delays is investigated. The time-varying delays lie in any two adjoining sampling instants of the plant. A technique is proposed for designing stabilizing controllers by converting NCSs with time-varying transmission delays into parameter uncertain systems with constant input delay, then the theory of robust stabilization of delay systems can be applied to solving this problem. Sufficient condition on stabilization of such NCSs is developed in terms of linear matrix inequality.

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