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The paper analyses a networked control system consisting of a linear time-invariant system with a static feedback nonlinearity, subject to large delays in the feedback loop. This model is valid for example in wireless data flow control, where a saturation occurs since the flow is one-directional. The present paper extends previous results by proving necessity, in case the loop gain is uniformly less than one. The results are validated and illustrated in a simulation study.

In this paper, the robust stability of a perturbed linear continuous-time system is examined when controlled using a sampled-data networked control system (NCS) framework. Three new robust stability bounds on the time-invariant perturbations to the original continuous-time plant matrix are presented guaranteeing stability for the corresponding discrete closed-loop augmented delay-free system (ADFS) with multiple time-varying sensor and actuator delays. The bounds are differentiated from previous work by accounting for the sampled-data nature of the NCS and for separate communication delays for each sensor and actuator, not a single delay. Therefore, this paper expands the knowledge base in multiple inputs multiple outputs (MIMO) sampled-data time delay systems. Bounds are presented for unstructured, semi-structured, and structured perturbations.

The insertion of communication networks in the feedback loops of control systems is a defining feature of modern control systems. These systems are often subject to unknown inputs in a form of disturbances, perturbations, or attacks. The objective of this paper is to design and analyse an observer for networked dynamical systems with unknown inputs. The network effect can be viewed as either a perturbation or time-delay to the exchanged signals. In this paper, we (1) review an unknown input observer (UIO) design for a non-networked system, (2) derive the networked unknown input observer (NetUIO) dynamics, (3) design a NetUIO such that the effect of higher delay order terms are nullified and (4) establish stability-guaranteeing bounds on the networked-induced time-delay and perturbation. The formulation and results derived in this paper can be generalised to scenarios and applications where the signals are perturbed due to a different source of perturbation or delay.

This paper presents a fault-tolerant control (FTC) scheme for nonlinear systems which are connected in a networked control system. The nonlinear system is first transformed into two subsystems such that the unobservable part is affected by a fault and the observable part is unaffected. An observer is then designed which gives state estimates using a Luenberger observer and also estimates unknown parameter of the system; this helps in fault estimation. The FTC is applied in the presence of sampling due to the presence of a network in the loop. The controller gain is obtained using linear-quadratic regulator technique. The methodology is applied on a mechatronic system and the results show satisfactory performance.

This paper addresses the problem of optimal and robust H2 control for discrete-time periodic systems with Markov jump parameters and multiplicative noise. To analyse the system performance in the presence of exogenous random disturbance, an H2 norm is firstly established on the basis of Gramian matrices. Further, under the condition of exact observability, a necessary and sufficient condition is presented for the solvability of H2 optimal control problem by means of a generalised Riccati equation. When the transition probabilities of jump parameter are incompletely measurable, an H2-guaranteed cost norm is exploited and the robust H2 controller is designed through a linear matrix inequality (LMI) optimisation approach. An example of a networked control system is supplied to illustrate the proposed results.

This paper is concerned with a tracking controller design problem for discrete-time networked predictive control systems. The control law used here is a combined state-feedback control and integral control. Since not all the states are available in practice, a local Luenberger observer is utilised to estimate the state vector. The measured output and estimated state vector are packed together and transmitted to the tracking controller via a communication channel with a limited capacity. Meanwhile, the control signal is also transmitted through a communication network.Network-induced delays on both links are considered for the signal transmission and modelled by Markov chains. Moreover, it is assumed that the elements in Markov transition matrices are subject to uncertainties. In order to fully compensate for network-induced delays, the controller generates a sequence of control signals which are dependent on each possible delay in the feedforward channel. By taking the augmentation twice, we obtain delay-...

This article investigates a class of constrained nonlinear networked control systems (NCSs) subject to external disturbances, input and state constraints and network-induced constraints. From a practical perspective, the network-induced constraints considered include the time delays and packet dropouts on both the sensor-to-controller (S-C) channel and the controller-to-actuator (C-A) channel simultaneously. The min–max model predictive control method is proposed to design the control packets by incorporating the external disturbances into the optimisation problem. Moreover, the input-to-state practical stability of the resulting nonlinear NCS is established by constructing a novel Lyapunov function. Finally, the simulation results and the comparison studies are presented to demonstrate the effectiveness and improvement of the proposed method.

The consensus problem of discrete-time networked multi-agent systems (NMASs) with a communication delay is investigated in this article, where the dynamics of agents described by discrete-time linear time-invariant systems can be either uniform or non-uniform. For the NMASs with a directed topology and constant delay, a novel protocol based on the networked predictive control scheme is proposed to compensate for communication delay actively. Using algebraic graph theories and matrix theories, necessary and/or sufficient conditions of achieving consensus are obtained, which indicates that, under the proposed protocol, the consensus is independent of the network delay and only dominated by agents' dynamics and communication topology. Meanwhile, the protocol design and consensus analysis are also presented in the case of no network delay. Simulation results are further presented to demonstrate the effectiveness of theoretical results.

Event-based control aims at reducing the information exchange over the communication network in feedback-control systems. This article extends a state-feedback approach to event-based control to cope with communication delays and packet losses in the feedback link. The main result is a bound for the maximum tolerable communication delay, which guarantees that the event-based state-feedback loop is stable in the sense that its state remains in a bounded surrounding of the state of a continuous-time state-feedback loop. This result is extended to communication links with additional packet losses. Simulation studies and experimental results illustrate the performance of the event-based control loop.

This article is concerned with the problem of H ∞ predictive control of networked control system with random network delay. A new control scheme termed networked predictive control is proposed. This scheme mainly consists of the control prediction generator and network delay compensator. While designing the predictor, the control input to the actuator may be different due to networked induced time-delay and data dropout, and two cases are considered depending on the way that the observer obtains the plant control input u t . The necessary and sufficient conditions are given for the closed-loop networked predictive control system to be stochastically stable for different u t and random network delays in controller to actuator channel (CAC) and sensor to controller channel (SCC). A simulation study shows the effectiveness of the proposed scheme.

The aim of this article is to provide a set of results in stability of model-based networked control systems (MB-NCS) with intermittent feedback, which we intend will serve as a nexus between the study of systems with instantaneous feedback and with continuous feedback. We apply the concept of intermittent feedback to a class of networked control systems known as MB-NCS. MB-NCS use an explicit model of the plant in order to reduce the network traffic while attempting to prevent excessive performance degradation, while intermittent feedback consists of the loop remaining closed for some fixed interval, then open for another interval. We begin by introducing the basic architecture for model-based control, then discuss the concept of intermittent feedback, its applications in various fields and its role as a link between instantaneous and continuous feedback. We then provide our results for the model-based architecture with intermittent feedback. We also address the case with output feedback (through the use...

We consider the analysis and synthesis of discrete-time networked control systems (NCSs), where the plant has additive uncertainty and the controller is updated with the sensor information at stochastic time intervals. It is shown that the problem is linked to H1-control of linear discrete-time stochastic systems and a new small gain theorem is established. Based on this result, sufficient conditions are given for ensuring mean square stability of the NCS, and the genetic algorithm is utilised to design the controller of the NCS based on a linear matrix inequality technique. An illustrative example is given to demonstrate the effectiveness of our proposed method.

This article presents the networked control of a robotic anthropomorphic manipulator based on a second-order sliding mode technique, where the control objective is to track a desired trajectory for the manipulator. The adopted control scheme allows an easy and effective distribution of the control algorithm over two networked machines. While the predictability of real-time tasks execution is achieved by the Soft Hard Real-Time Kernel (S.Ha.R.K.) real-time operating system, the communication is established via a standard Ethernet network. The performances of the control system are evaluated under different experimental system configurations using, to perform the experiments, a COMAU SMART3-S2 industrial robot, and the results are analysed to put into evidence the robustness of the proposed approach against possible network delays, packet losses and unmodelled effects.

This article deals with the problem of L 2-gain for a class of networked control systems with time-varying network delay in both forward and feedback channels. An improved network predictive control scheme is proposed to compensate the effects of network delay and data dropout using a switching control strategy. Based on the average dwell time method, the restrictions that the original delay-compensation strategy imposes on the subsystems are relaxed and a sufficient condition for weighted L 2-gain is developed for a class of switching signal. An example illustrates the effectiveness of the proposed method.

We explore the LQG control of a networked control system (NCS) in which a linear plant is controlled remotely over a network or other shared communication medium. The medium provides a limited number of simultaneous connections, so that only a subset of the plant's sensors and actuators may communicate with the controller at any one time, subject to known transmission delays. Instead of insisting on jointly optimal control and medium access policies, we reduce the infinity of possible access sequences down to those which preserve the stabilisability and detectability of the underlying plant, and are periodic. Our choice of communication and NCS model effect a kind of ‘decoupling’ of the LQG problem, in the sense that the medium access policy can be selected independently of the controller. This guarantees the existence of a stabilising LQG controller which is optimal for the communication policy of choice, and which is then combined with a delay compensator. We include simulations that illustrate our appr...

We examine a distributed control problem for internal flow management in a multi-zone climate unit. The problem consists of guaranteeing prescribed indoor climate conditions in a cascade connection of an arbitrarily large number of communicating zones, in which air masses are exchanged to redirect warm air from hot zones (which need to be cooled down) to cold zones (which need to be heated up), and to draw as much fresh air as possible to hot zones, relying on the ventilation capacity of neighbouring ‘‘collaborative’’ zones. The controller of each zone must be designed so as to achieve the prescribed climate condition, while fulfilling the constraints imposed by the neighbouring zones—due to their willingness to cooperate or not in the air exchange—and the conservation of flow, and despite the action of unknown disturbances. We devise control laws which yield hybrid closed-loop systems, depend on local feedback information, take on values in a finite discrete set, and cooperate with neighbour controllers to achieve different compatible control objectives, while avoiding conflicts.

This paper addresses the stability of a newly-developed control strategy for networked control systems (NCS). This control strategy hones the potential of constrained model predictive control (MPC) by buffering the predicted control sequence at the actuator in anticipation of typical data transmission errors associated with NCS. Closed-loop stability in the sense of Lyapunov is guaranteed for the controller in the linear case, by bounding the projected receding horizon costs by lower- and upper-bounding terms using a predetermined terminal cost. A stability theorem is developed, which provides a suboptimal measure for the controller in real time, and is sufficient to estimate the worst-case transmission delay that can be handled by the developed control buffering strategy. The stability conditions, as governed by the theorem, are validated through real-time implementation on an electro-hydraulic servo system of an industrial processing machine, through an Ethernet network.

A general solution of the H2 control problem is presented for linear systems described by rational transfer matrices, not necessarily proper or stable. The control system is considered in the standard configuration, which includes the synthesis model of the plant and the controller. The H2 control problem consists of internally stabilizing the control system while minimizing the H2 norm of its transfer function. The notion of internal stability is based on bounded-input bounded-output stability and means that subsystems defined by any pair of input and output signals within the control system all are bounded-input bounded-output stable. In this manner, the optimal control system is devoid of impulsive as well as non-decaying exponential modes. The solution proceeds in three steps. First, the set of all controllers that internally stabilize the control system is parameterized. Then the subset of the stabilizing controllers that achieve a finite value of the H2 norm of the control system transfer matrix is...

In this paper the effects of quantization in an important class of networked control systems called model-based networked control systems (MB-NCS) are considered. The MB-NCS architecture uses an explicit model of the plant in the controller in order to reduce the network traffic, while attempting to prevent excessive performance degradation. Sufficient stability conditions for two types of static and a dynamic quantization schemes for MB-NCS are derived. An important feature is that the stability conditions are explicitly expressed in terms of the plant and controller dynamics, the error between the model and the plant parameters, the transmission or update times, the quantization parameters, and a robustness measure of the system to parameter uncertainty. This is important because it allows the design of the controller and network parameters to achieve the desired goals. Examples are used throughout to illustrate the main results.

This paper describes a novel control technique to deal with networked control systems with random communication time delay, which is known to highly degrade the control performance of the controlled system. This problem can be solved using a modified model predictive control, which uses the future control sequence to compensate for the forward communication time delay. Also, using a model predictor, the time delay in the backward channel can be compensated as well. Another key part of this paper is to analyse the stability of the networked control systems. The analytical criteria are obtained for both fixed and random communication time delays. The simulation results and practical experiments illustrate that the proposed controller design is realistic.

We study a linear discrete-time partially observed system perturbed by white noises. The observations are transmitted to the controller, and its outputs are sent to the actuators via communication channels that provide random transmission times and may lose messages. Various signals may incur independent delays and arrive at the destination point out of order. Under certain assumptions, a recursive minimum variance state estimator is proposed. A finite horizon linear-quadratic optimal control problem is also solved.

Sliding mode control is a well-known technique capable of making the closed loop system robust with respect to certain kinds of parameter variations and unmodelled dynamics. The sliding mode control law consists of a continuous component which is based on the model knowledge and discontinuous component which is based on the model uncertainty. This paper extends two known adaption laws for the switching gain for continuous-time sliding mode controllers to the multiple input case. Because these adaption laws have some fundamental problems in discrete-time, we introduce a new adaption law specifically designed for discrete-time sliding mode controllers.

Multilayer neural networks are used in a non-linear adaptive control problem. The plant is an unknown feedback linearizable continuous-time system with relative degree 1. The single-input:/single-output system is studied first and then the methodology is extended to control square multi-input/multi-output systems. The control objective is for the plant to track a reference trajectory, and the control law is defined in terms of the outputs of the neural networks. The parameters of the networks are updated on-line according to an augmented tracking error and the network derivatives. A local convergence theorem is given on the convergence of the tracking error. This control algorithm is applied to control a two-input/two-output relative-degree-two system.

Time-optimal feedback control laws are derived for seven fourth-order systems with real non-positive eigenvalues and a single saturable control input. The method is based on the property of time-optimality exhibited by a certain predictive control strategy.

Feedback control is developed for a class of distributed systems described by second-order evolution equations with unbounded observation. In order to increase the degree of stability of the system, a dynamic compensator is designed on the basis of a finite-dimensional model of the system, and a feedback control system is constructed by using sensor outputs. It is shown that the degree of stability of the whole system including the compensator is improved by ‘modal control’ based on a finite-dimensional modal model.

The objective of this paper is to provide a mathematical framework for building reliable control using less reliable controllers. The new ingredient in the design is the multiple control system which provides the necessary redundancy for reliability enhancement in control systems subject to controller failures. The proposed reliability design is based upon the decentralized control schemes used so far for synthesizing reliable control systems subject to perturbations in the plant interconnection structure.

An on-line computer control method is suggested for a time-suboptimal feedback control of systems with multiple delays in the control variables. The method, which is developed for bounded control inputs, is given in the form of on efficient algorithm. The scheme is essentially based on solving the minimum-time problem using the linear programming method iteratively under real-time computing constraints. A numerical example is given to demonstrate the efficiency of the proposed control algorithm.

In this paper, two control strategies are presented for the study of the control of a large-scale electric power system. In the first, the control is obtained by decomposition of the system to what are called ‘ ∊-coupled ’ subsystems, and in the second, a control strategy using closed-loop hierarchical control techniques is introduced. Finally, these two approaches are applied to a system consisting of three plants.

Integrated excitation and/or governor control systems are the result of using novel approaches for the selection of stabilizing signals in electric power systems. Such controllers have usually been derived on the basis of a linearized system model, an attractive practical feature of these being that a linear, time-invariant optimal controller may be derived. The power system is non-linear, however, and it is for this non-linear system that an optimal controller is ideally required. Previous work in the area is shown to be deficient in the light of this requirement and subsequently time-invariant integrated controllers suitable for use with the non-linear system are developed. These controllers incorporate model following with integral action and are shown to effect improved control of the nonlinear system over a wide range of operating conditions. The manner in which the proposed control system design procedure may permit the integrated control of large power systems is also of considerable pract...

An analytical evaluation of the adaptive loop response of a model-reference adaptive control system is presented using sinusoids as a test signal. A schematic diagram of the feedback system containing a primary control loop and an adaptive control loop are given.