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This article presents a skill learning-based hierarchical control strategy for human–robot cooperative manipulation, which constitutes a novel learning-control system. The high-level learning strategy aims to learn the motor skills from human demonstrations by fusion with dynamic motion primitives (DMPs) and the Gaussian mixture model (GMM). The lower level control strategy guarantees the compliance of the robot movement under human interaction using admittance control and integral barrier Lyapunov function (IBLF)-based adaptive neural controller. First, the robot learns the motor skills from observing the successful execution of tasks by a demonstrator through DMP-GMM methods. Then, the robot reproduces the complex skills and executes the interactive task by demonstrations. Finally, the effectiveness of the proposed learning-control strategy is demonstrated with experimental results. The results show that the developed hierarchical strategy has good performance in cooperation by learning and control that reacts compliantly to robot interaction with human subjects.

•The DoS jamming attacks and the channel fading are considered.•Working subcycle is defined to express the random attack strategy in a unified framework.•DoS jamming attacks occur on the measurement and control channels simultaneously.•Without knowing the DoS jammers’ attack strategy, controllers are designed for CPSs; and•This control method can also address the CPS only with inherent packet dropouts.

Without the known state equation, a new state estimation strategy is designed to be against malicious attacks for cyber physical systems. Inspired by the idea of data reconstruction, the compressive sensing (CS) is applied to reconstruction of residual measurements after the detection and identification scheme based on the Markov graph of the system state, which increases the resilience of state estimation strategy against deception attacks. First, the observability analysis is introduced to decide the triggering time of the measurement reconstruction and the damage level from attacks. In particular, the dictionary learning is proposed to form the over-completed dictionary by K-singular value decomposition (K-SVD), which is produced adaptively according to the characteristics of the measurement data. In addition, due to the irregularity of residual measurements, a sampling matrix is designed as the measurement matrix. Finally, the simulation experiments are performed on 6-bus power system. Results show that the reconstruction of measurements is completed well by the proposed reconstruction method, and the corresponding effects are better than reconstruction scheme based on the joint dictionary and the traditional Gauss or Bernoulli random matrix respectively. Especially, when only 29% available clean measurements are left, performance of the proposed strategy is still extraordinary, which reflects generality for five kinds of recovery algorithms.

Wireless sensor and actuator networks (WSANs) are emerging as a new generation of sensor networks. To accomplish effective sensing and acting tasks, efficient coordinate mechanisms among the nodes are desirable. As an attempt in this direction, this paper develops a collaborative estimation and control mechanism, which addresses the nodes coordination in a distributed manner. First, we discuss the system model and system partition that are used to construct the distributed architecture. Then, a collaborative estimation and control scheme is proposed to coordinate sensor and actuator nodes. This scheme includes two components, namely recursive least squares based federated Kalman filter (RLS-FKF) and PID neural network (PIDNN). It schedules the corresponding nodes based on the characteristics of current events, deals with data fusion and system estimation problems through RLS-FKF, and utilises PIDNN controller to improve system transient and steady-state responses. Simulations demonstrate the effectiveness of proposed methods.

This paper considers a leader-following tracking control problem for second-order multiagent systems (MASs) under measurement noises and directed communication channels. It is assumed that each follower-agent can measure the relative positions and velocities of its neighbors in a noisy environment. Based on a novel velocity decomposition technique, a neighbor-based control law is designed to realize local control strategies for these continuous-time agents. It is shown that the proposed consensus protocol can guarantee that all the follower-agents track the active leader. In addition, this result is extended to a more general case with switching topologies. Finally, a numerical example is given for illustration.

Abstract: This paper investigates the H 2/H ∞ control problem for a class of discrete-time networked control systems with random communication time delays. Both sensor-to-controller (S-C) and controller-to-actuator (C-A) random network-induced delays are considered. Two independent Markov chains are used to model the S-C and C-A random delays. The resulting closed-loop system is a jump linear time-delay system induced by two Markov chains. Sufficient conditions for existence of H 2/H ∞ controller are established by free-weighting matrix and stochastic Lyapunov functions. A simulation example illustrates the effectiveness of the proposed method.

New necessary and sufficient stability criteria for linear systems with multiple uncertain delays are established by using the time-domain and the frequency-domain methods, respectively. The results are first established based on a new-type time-domain stability theorem for retarded dynamical systems and a new technique for estimating the derivative of Lyapunov function along the solution of system at some specific instants. Then, the same criteria are derived by the frequency-domain techniques. The established stability criteria are not only the least conservative but also involve the least tuning parameters.

Four new stability theorems for general classes of retarded dynamical systems are established by using the Lyapunov function approach in this paper. A new technique is proposed for estimating the derivative of the Lyapunov function along the solution of a system at some specific instant. It is remarked that the stability conditions obtained by the established stability theorems together with the proposed technique are less conservative than those obtained by the existing Razumikhin-type theorems and techniques in the literature. Four illustrative examples and two corollaries for systems with a single time-varying delay or multiple time-varying delays are given to show the applications of the established stability theorems and the proposed technique.

Two new asymptotic stability criteria for linear time-invariant systems with multiple delays are established by using a quadratic inequality lemma together with frequency-domain techniques. One criterion is for delay-dependent α-stability and another is for delay-independent asymptotic stability. Each of them has only one tuning parameter matrix P>0 as the Lyapunov-type stability criteria for the corresponding linear time-invariant systems without delays do. Both of the established stability criteria are given in the form of LMI problems and hence are very easy to use in applications. In addition, it is remarked that the established delay-independent asymptotic stability criterion with one tuning parameter matrix P>0 improves and simplifies the existing criterion with more than one tuning parameter matrix 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.

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.