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In this paper, considering two typical attack strategies of a DoS jammer, a new kind of H∞ control problem is studied for Cyber-Physical Systems (CPSs) with different transmission mechanism encountering DoS jamming attacks. By defining a concept of working subcycle, the concrete attack strategies of a DoS jammer can be generated by choosing different reasonable value combinations in a unified framework according to the DoS jammer's energy efficiency and stealthiness. Then, for two different transmission mechanisms, namely the time-triggered mechanism (TTM) and the event-triggered mechanism (ETM), in which CPSs can employ in its wireless channels, two DoS jammers employ different attack strategies and launch SINR-based DoS jamming attacks to decrease the quality of wireless communication. Considering the case that the CPSs do not know the DoS jammers' attack strategies, the corresponding H∞ observer-based controllers are designed by using an attack-tolerant mechanism to achieve the desired H∞ disturbance attenuation level, and the controller design problems are transformed to auxiliary convex optimization problems. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed H∞ control methods and the varying of system performance under different interference power chosen by the DoS jammers.

Recent advances in fine manipulation have led to increased interest in both scientific research works and engineering applications. Robot manipulation at a level approaching human skills is gaining attention in both industrial and individual services. A major challenge in fine manipulation is the unavoidable uncertainties and unpredictable conditions encountered in dynamic and unstructured application environments. The employment of biologically inspired (bioinspired) embodiments in fine manipulation shows significant advantages in tackling such problems. The aim of bioinspired embodiment is to improve fine manipulation of robotic systems utilizing the knowledge gained from natural systems with biomimetic methods. Such a method includes sensing, planning, and execution. This article provides a comprehensive survey of the current state of bioinspired technologies in fine manipulation, and outlines new challenges and some potential directions.

In order to save the usage of system resources and adapt the variation of plant state, this study first proposes a novel stochastic-sampling-based adaptive event-triggered scheme (AETS). Second, in the framework of time-delay systems, the closed-loop control system is modelled as a class of delayed stochastic systems where time-delay is distributed in some intervals with probability. Then, by employing stochastic analysis tool and Lyapunov stability theory, a stability criterion for this class of delayed stochastic systems is established to ensure that the system possesses stochastically asymptotic stability with an H ∞ disturbance attenuation performance. Also, a co-design of parameter matrices of the state-feedback controller and the stochastic-sampling-based AETS is implemented. Third, based on the obtained co-design condition, a convex optimisation algorithm for the tradeoffs between disturbance attenuation performance and resource utilisation of the closed-loop control system is further developed. Finally, the effectiveness and feasibility of the proposed control strategy are illustrated by two numerical examples of adaptive event-triggered control for networked control systems under stochastic sampling.

This paper investigates the distributed consensus problem for heterogeneous multi-agent systems via event-triggered scheme. To alleviate the communication burden, a distributed event-triggered consensus algorithm using an open-loop estimate and neighboring information is proposed. In the proposed event-triggered scheme, the control input of each agent is dependent on the estimate and information at discrete instants. Firstly, the novel event-triggered consensus algorithm is proposed for fixed topology, which involves the discrete communication between neighboring agents. Then, for the switching topology, the triggering condition is proposed by virtue of a topology-dependent dwell time approach. Further, the corresponding consensus procedures are given. Finally, the effectiveness of the proposed scheme is illustrated by numerical results.

Active prosthetic knees (APKs) are widely used in the past decades. However, it is still challenging to make them more natural and controllable because: (1) most existing APKs that use rigid actuators have difficulty obtaining more natural walking, and (2) traditional finite-state impedance control has difficulty adjusting parameters for different motions and users. In this paper, a flexible APK with a compact variable stiffness actuator (VSA) is designed for obtaining more flexible bionic characteristics. The VSA joint is implemented by two motors of different sizes, which connect the knee angle and the joint stiffness. Considering the complexity of prothetic lower limb control due to unknown APK dynamics, as well as strong coupling between biological joints and prosthetic joints, an adaptive robust force/position control method is designed for generating a desired gait trajectory of the prosthesis. It can operate without the explicit model of the system dynamics and multiple tuning parameters of different gaits. The proposed model-free scheme utilizes the time-delay estimation technique, sliding mode control, and fuzzy neural network to realize finite-time convergence and gait trajectory tracking. The virtual prototype of APK was established in ADAMS as a testing platform and compared with two traditional time-delay control schemes. Some demonstrations are illustrated, which show that the proposed method has superior tracking characteristics and stronger robustness under uncertain disturbances within the trajectory error in &plusmn, 0 . 5 degrees. The VSA joint can reduce energy consumption by adjusting stiffness appropriately. Furthermore, the feasibility of this method was verified in a human&ndash, machine hybrid control model.

In this paper, we research the resilient control problem for cyber-physical system (CPS) under denial-of-service (DoS) attacks. These malicious DoS attacks aim to impede the communication of measur...

The additional threshold of a mixed event-triggering mechanism (ETM) makes it impossible to guarantee the requirement of asymptotic stability. As a consequence, it is necessary to investigate input-to-state practically stable (ISpS) which is a mild stability property. In this study, the authors firstly model the closed-loop event-triggered control system as a delayed linear parameter-varying (LPV) systems with a mixed ETM and parameter uncertainty. Then, a co-design condition in a sense of ISpS of controller gain and trigger parameters for the delayed LPV systems is obtained by employing the parameter-dependent Lyapunov–Krasovskii functionals and congruent transformation method. Moreover, based on the obtained co-design condition in a sense of ISpS, an optimisation algorithm for the tradeoffs between resource utilisation and robustness of the closed-loop system is further proposed. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed method.

Cooperative braking control is a very important operation in vehicle platoon control for developing intelligent transportation systems, which can effectively increase road capacity, decrease safety hazard, and avoid serial rear-end collisions. This paper focuses on cooperative braking control of autonomous vehicles, the objectives of which are to ensure intervehicles keep within the safe spacing range and rapidly, smoothly, and accurately stop at the desired target stopping positions with zero velocity. To achieve these goals, a three-vehicle platoon framework is presented and the corresponding dynamic model is established based on only information about front-end and rear-end sensors of vehicles, so communication is not needed. The explicit solutions on the three-vehicle platoon are derived by rigorous convergent analysis and detailed proof, such that intrinsic characteristic of the interconnected vehicles is revealed. The resulting convergent conditions and convergent rate are obtained under three cases including: 1) considering internal virtual forces; 2) considering external braking forces; and 3) considering both the internal virtual forces and external braking forces simultaneously. Moreover, an example is further provided to verify that the derived convergence conditions are effective and sufficient under the different controller parameter selection. These results can provide a solution for a wide class of interconnected systems and a guide for controller design to select control parameters in real engineering applications. Simulation results demonstrate the validity of the proposed control approaches.

This paper investigates the robust control method for networked dynamic systems and its application for a direct-drive linear motion control system in a network environment. The unavoidable network-induced random delays are modeled as Markov chains. The control object of the linear motion control system in this study is a double-sided linear switched reluctance machine (DLSRM). To tackle the inherent uncertainties in the DLSRM, a robust control strategy is designed by proposing a new Lyapunov function and applying the free-weighting matrix technique. A state feedback robust controller is designed such that the closed-loop direct-drive linear motion control system over a network is stochastically robust stable. The robust controller can be conveniently obtained by solving a set of linear matrix inequalities. The numerical simulation of an angular positioning system is presented to illustrate the effectiveness of the proposed robust control method. Furthermore, the experimental tests on the networked direct-drive linear motion control system verify the practicability of the proposed method.

With increasing growth of vehicles, traffic congestion and safety deserve to be looked at more closely. Cooperative autonomous driving is an effective solution to reduce traffic congestion and ensure traffic safety. In this paper, cooperative autonomous control of multiple vehicles is considered to realize sharing the same roads without collusion with each other. Lane-following and braking control are two basic operations of cooperative driving. The objectives of lane-following are to make intervehicles keep a safe spacing and run on the middle position of a lane. To reach the targets, two distributed control protocols are proposed in which we consider not only lateral control but also longitudinal control. The stability analysis is also shown for both the control protocols. Braking control is another basic operation for autonomous cooperative control. In order to make vehicles stop at the desired target stopping position (TSP), a new braking control protocol is also designed, and the convergence of which is analyzed and shown that, under three kinds of distinct braking control parameters, the position of the mass center of all vehicles exponentially converges to the TSP, and the velocity of the mass center of all vehicles exponentially converges to zero, which provide a guide for selecting the braking control parameters in real engineering applications. Moreover, the initial and limit conditions of position and velocity are discussed. Simulations demonstrate the validity and superiority of the proposed control protocols compared with existing approaches.

The problem of robust stochastic stability and delayed-state-feedback stabilisation of uncertain Markovian jump linear systems with random Markov delays is investigated. Based on the Lyapunov stability theory and robust analysis techniques, some robust stochastic stability criteria are derived in terms of linear matrix inequalities. Robust delayed-state-feedback controllers that stochastically stabilise the uncertain Markovian jump linear systems is also proposed. The state variable on the controller is assumed to be dependent on the Markov delay that has uncertain transition probabilities. Finally, numerical examples are provided to illustrate the feasibility and effectiveness of the proposed methods.

This paper focuses on the robust output feedback $\mathscr {H}_{2}/\mathscr {H}_\infty $ control issue for a class of discrete-time networked control systems with uncertain parameters and external disturbance. Sensor-to-controller and controller-to-actuator packet dropouts and time delays are considered simultaneously. According to the stochastic characteristic of the packet dropouts and time delays, a model based on a Markov jump system framework is proposed to randomly compensate for the adverse effect of the two-channel packet dropouts and time delays. To analyze the robust stability of the resulting closed-loop system, a Lyapunov function is proposed, based on which sufficient conditions for the existence of the $\mathscr {H}_{2}/\mathscr {H}_\infty $ controller are derived in terms of linear matrix inequalities, ensuring robust stochastic stability as well as the prescribed $\mathscr {H}_{2}$ and $\mathscr {H}_\infty $ performance. Finally, an angular positioning system is exploited to demonstrate the effectiveness and applicability of the proposed design strategy.

This study studies coordinated control of a platoon of vehicles consisting of a leader and multiple followers when multiple vehicles suffer from disturbances. Small disturbances acting on one vehicle may cause large spacing errors between intervehicles. In addition, the spacing errors propagate up or down in a vehicle platoon. To mitigate the adverse effect of the disturbances, a control law is proposed based on only the position information of the vehicle itself and its preceding vehicle. To analyse the disturbances propagation among the platoon, the upper bounds of two transfer functions are presented including the transfer function matrix 𝒢 de from external disturbances to spacing errors as well as the transfer function matrix 𝒢 ue from a leader's input control to spacing errors. Furthermore, an alternative control law is proposed when the velocity of the leader is known by the followers. In this case, two tighter upper bounds of 𝒢 l de and 𝒢 l ue are presented. The derived upper bounds of the transfer functions are independent of the number of vehicles in the platoon. Simulations verify the effectiveness of the proposed approach.

Wireless sensor and actuator networks (WSANs) have a wide range of applications. To perform effective sensing and acting tasks, multiple coordination mechanisms among the nodes are required. As attempt in this direction, this paper describes collaborative estimation and control algorithms design for WSANs. First, a sensor-actuator coordination model is proposed based on distributed Kalman filter in federated configuration. This method provides the capability of fault tolerance and multi-source information fusion. On this basis, an actuator-actuator coordination model based on even-driven task allocation is introduced. Actuators utilize fused sensory information to adjust their action that incur the minimum energy cost to the system subject to the constraints that user’s preferences regarding the states of the system are approximately satisfied. Finally, according to system requirements, a distributed algorithm is proposed to solve the task allocation problem. Simulations demonstrate the effectiveness of our proposed methods.

This paper focuses on sensor scheduling and information quantization issues for target tracking in wireless sensor networks (WSNs). To reduce the energy consumption of WSNs, it is essential and effective to select the next tasking sensor and quantize the WSNs data. In existing works, sensor scheduling’ goals include maximizing tracking accuracy and minimizing energy cost. In this paper, the integration of sensor scheduling and quantization technology is used to balance the tradeoff between tracking accuracy and energy consumption. The main characteristic of the proposed schemes includes a novel filtering process of scheduling scheme, and a compressed quantized algorithm for extended Kalman filter (EKF). To make the algorithms more efficient, the proposed platform employs a method of decreasing the threshold of sampling intervals to reduce the execution time of all operations. A real tracking system platform for testing the novel sensor scheduling and the quantization scheme is developed. Energy consumption and tracking accuracy of the platform under different schemes are compared finally.

The problem of distributed estimation of an unknown noise-corrupted parameter in wireless sensor networks, with a fusion centre, is considered. Convolutional coding and rate-compatible punctured convolutional coding are used to protect the transmission of sensor observations and to reduce the impact of noise channels. Two novel kinds of power scheduling based on different encoding methods are derived for minimising the total power consumption. The formulas of the proposed power scheduling suggest that local sensors with poor observation qualities should decrease their quantisation levels. The levels should also be related to coding methods, channel qualities, a given mean squared error (MSE) and local signal-to-noise ratios. Finally, simulation results show that not only these two schemes are energy-efficient but also they can achieve comparable performance of a given MSE.

Packet losses are a general problem in networked control system and wireless sensor networks (WSNs). In order to increase estimation accuracy and reliability, a filter with finite packet losses called minimum variance filter (MVF) is designed for stochastic systems. The authors develop a packet loss model, and design a novel MVF based on the orthogonal analysis approach. The proposed filters rely only on the packet arrival probability at each time instant and do not need to know whether the measurement is received at a particular time instant. However, the proposed MVF is not applicable to non-linear cases. So an extended MVF is derived for stochastic non-linear systems and applied to track a moving target in WSNs. Simulation results show that, compared to existing methods, the proposed MVFs have superior performance.

An energy-balanced multiple-sensor collaborative scheduling is proposed for maneuvering target tracking in wireless sensor networks (WSNs). According to the position of the maneuvering target, some sensor nodes in WSNs are awakened to form a sensor cluster for target tracking collaboratively. In the cluster, the cluster head node is selected to implement tracking task with changed sampling interval. The distributed interactive multiple model (IMM) filter is employed to estimate the target state. The estimation accuracy is improved by collaboration and measurement information fusion of the tasking nodes. The balanced distribution model of energy in WSNs is constructed to prolong the lifetime of the whole network. In addition, the communication energy and computation resource are saved by adaptively changed sampling intervals, and the real-time performance is satisfactory. The simulation results show that the estimation accuracy of the proposed scheme is improved compared with the nearest sensor scheduling scheme (NSSS) and adaptive sensor scheduling scheme (ASSS). Under satisfactory estimation accuracy, it has better performance in saving energy and energy balance than the dynamic collaborative scheduling scheme (DCSS).

New delay-independent and delay-dependent stability criteria for linear systems with multiple time-varying delays are established by using the time-domain method. The results are derived based on a new-type stability theorem for general retarded dynamical systems and new analysis techniques developed in the author's previous work. Unlike some results in the literature, all of the established results do not depend on the derivative of time-varying delays. Therefore, they are suitable for the case with very fast time-varying delays. In addition, some remarks are also given to explain the obtained results and to point out the limitations of the previous results in the literature.

New stability criteria for linear continuous systems with multiple time-varying delays are established by the Lyapunov function approach based on a new stability theorem for general type of retarde...

In this paper, a decentralized stabilization condition for large-scale linear continuous systems with N x N time-varying delays is established under a decomposition case of the interconnections. Based on a new stability theorem for a general type of retarded dynamic systems, the results are derived by using the Lyapunov function instead of the L yapunov functional. During the derivation, a new technique for estimating the derivative of the L yapunov function for the solution of the system under consideration is used so that the case of N x N time-varying delays can be dealt with as least conservatively as possible. It is noted that the stabilization condition obtained by using the proposed technique is better than those obtained by using the existing Razumikhin-type techniques in the literature. An example with three interconnected subsystems is given to illustrate the proposed method and to show the design of the local memoryless state feedback controllers.

This paper presents some necessary and sufficient stability conditions and some sufficient stability conditions for general classes of retarded dynamic systems. The stability conditions are established by using the Lyapunov function method. However, attention is paid in this paper to establishing as less conservative exponential, generalized exponential and non-exponential decay estimates for the retarded dynamic systems as possible. As applications of the established stability conditions, a class of retarded dynamic systems which have a linear retard-free term are studied in detail and some exponential, generalized exponential and non-exponential iterative decay estimates for the systems are obtained. It is shown that the non-exponential iterative decay estimates are less conservative than the exponential and generalized exponential decay estimates. In addition, the obtained iterative decay estimates involve only algebraic computation; therefore, they are simple and very easy to use. Two examples are giv...

In this paper, automatic motion control is investigated for one of wheeled inverted pendulum (WIP) models, which have been widely applied for modeling of a large range of two wheeled modern vehicles. First, the underactuated WIP model is decomposed into a fully actuated second order subsystem Σa consisting of planar movement of vehicle forward and yaw angular motions, and a nonactuated first order subsystem Σb of pendulum motion. Due to the unknown dynamics of subsystem Σa and the universal approximation ability of neural network (NN), an adaptive NN scheme has been employed for motion control of subsystem Σa . The model reference approach has been used whereas the reference model is optimized by the finite time linear quadratic regulation technique. The pendulum motion in the passive subsystem Σb is indirectly controlled using the dynamic coupling with planar forward motion of subsystem Σa , such that satisfactory tracking of a set pendulum tilt angle can be guaranteed. Rigours theoretic analysis has been established, and simulation studies have been performed to demonstrate the developed method.

This paper presents the robustness bounds of delay-independent asymptotic stability for linear systems with multiple time-varying delayed perturbations including both nonlinear delayed perturbations and linear unstructured/structured perturbations in the delayed states. The case of arbitrary unknown but constant delays is included in the results as a special case. All of the obtained bounds can be maximized by choosing some appropriate free parameter matrices. In six illustrative examples, it is shown that all of the stability robustness bounds obtained by the proposed methods are larger than the existing ones in the literature.

Robust stability conditions for the large-scale time-delay system with structured and unstructured uncertainties are established by the Lyapunov functional method together with matrix measures. As the delays under consideration can be arbitrary unknown but constant, all of the obtained results are delay-independent. An illustrative example is provided to compare with the existing results to show that much larger robust stability bounds can be obtained. Therefore, the proposed method is less conservative than current methods.

Aiming for a better dynamic performance from the robot beyond the physical limits set by the manufacturers, in this paper we propose to integrate the robot dynamics into motion planning and then to approximate the robot joint torques using parameterized B-splines. By introducing a high-dimensional non-linear fitness function, we transform the motion planning problem into an optimization of a non-linear fitness function, and then we develop the approach based on Support Area Level Set Algorithm (SALAS). It integrates dual-stage sampling strategies to avoid early convergence in a small search field and to improve the rate of convergence to the potential solution. The effectiveness of the proposed approach has been verified by the simulation of a two-link robotic manipulator.

A new criterion for delay-independent stability of linear large scale time-delay systems is deduced by employing an improved Razumikhin-type theorem and the m-matrix properties. An illustrative example is given to demonstrate the superiority of the obtained results to those in the literature. >

An improved Razumikhin-type theorem is established, and the advantage of the established theorem for reducing conservatism is discussed. For a class of time-delay systems, a simple asymptotic stability condition is deduced as an application of the established theorem. Two illustrative examples are given to show the superiority of the results to those in the literature. >

In wireless sensor and actuator networks (WSANs), the sensor nodes are involved in gathering information about the physical phenomenon, while the actuator nodes take decisions and then perform appropriate actions upon the environment. The collaborative operation of sensor and actuator nodes brings significant advantages over WSNs, including improved accuracy and timely actions upon the sensed phenomena. However, unreliable wireless communication and finding a proper control strategy cause challenges in designing such network control system. In order to accomplish effective sensing and acting tasks, efficient coordination mechanisms among different nodes are required. In this paper, the coordination and communication problems in WSANs are studied. First, we formulate the mathematical models for the WSANs system. Then, a predictor-controller algorithm based on distributed estimation is adopted to mitigate the effects of network-induced delay. Finally, we apply a collaborative processing mechanism to meet the desired system requirements and improve the overall control performance. This approach will group the sensor and actuator nodes to work in parallel so as to reduce the computation complexity and enhance the system reacting time. Simulation results demonstrate the effectiveness of our proposed method.

Xu and Liu (see ibid., vol.39, no.4, p.839-41, 1994) tried to improve the well-known Razumikhin theorem on the stability of differential functional equations. The commenter states that, the proof of their main result contains an error, so the results may not be correct. In reply Bugong Xu gives a corrected result.

States that some expressions in the above paper by Su and Huang (IEEE Trans. Autom. Contr., vol. 37, no. 10, p.1656-59, 1992) should be modified and that there are also errors in the above paper. >