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Autonomous robotics working in the uncertain environment have drawn increasing interests from researchers. Here, an issue of online motion optimization under unknown environment is considered while preserving the safety and improving the flexible manoeuvrability of robot–environment interaction. This problem is addressed by improving the conventional dynamic movement primitives (DMPs) framework with force tracking constraints. First, an initial motion is learned through the DMPs. At the stage of skill generalization, a temporal coupling term combining with force constraints scheme which is inspired by the barrier Lyapunov function and finite‐time prescribed performance is deduced and adds to the original DMPs, so as to remain the contacting force staying within a predefined limit while aligning the motion along with surface of unknown environment adaptively. In this way, not only the contacting force can be guaranteed within a safe margin, but the shape of generalizing motion is preserved. Then the convergence and stability of the proposed DMPs are proved which is grounded on Laplace transformation‐based stability analysis to ensure the performance and safety. Finally, the proposed method is instantiated combined with conventional PID controller through the compared simulations to verify its effectiveness. [ABSTRACT FROM AUTHOR]

This study investigates a distributed leader‐following consensus problem for a class of high‐order uncertain non‐linear multiagent systems. For the uncertain non‐linear terms in the systems, the authors propose a less conservative Lipschitz condition, which the Lipschitz growth parameters are unknown. By using the adaptive method, the unknown Lipschitz growth parameters are estimated asymptotically. Furthermore, to lower the frequency of controller updates, a new dynamic event‐triggered control strategy with the novel dynamic variable is constructed based on the event‐triggered method. The distributed consensus protocol is proposed based only on the relative state information of neighbouring agents and the protocol can ensure that the Zeno‐behaviour no longer occurred. Based on the Lyapunov stability theory, it is strictly proved that the state variables of the followers can track asymptotically those of the leader. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

In this study, the visual servoing control problem is investigated, and a fixed time based visual servoing control scheme is proposed for quadrotor unmanned aerial vehicles. First, based on the perspective projection principle and target points, effective image features are defined on an image plane called the virtual image plane. Then, the image feature dynamics and QUAV dynamics are combined to derive a coupled non‐linear system, and the non‐linear system is decoupled into two subsystems under inner–outer loop control framework. Furthermore, the novel sliding mode surfaces based fixed‐time controllers are designed, and the resulting closed‐loop systems are proved to be stable. Finally, the numerical simulations and experiments are conducted to validate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The path optimisation problem of mobile sensor networks for arrival‐of‐angle (AOA) target localisation, using the consensus‐based extended information filter is considered, in this study. A new idea of equipping sensors with information‐driven mobility to improve the estimation accuracy with respect to a stationary target is proposed by the authors. A gradient descent method is used for mobile sensors, which are subject to geometric constraints, to choose the next optimal waypoints. The corresponding optimisation problem is solved in a distributed manner, by selecting a proper cost function for each mobile sensor. It is shown that the boundedness of the estimation error is guaranteed. Moreover, they find that the mobility of sensors does decrease the estimation error bounds compared with the static sensor networks, which is beneficial for the localisation performance. Simulation is carried out to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study is concerned with a joint localisation and tracking problem for autonomous underwater vehicle (AUV), subject to asynchronous clock and stratification effect in cyber channels as well as the model disturbances in physical channels. The authors first construct an integrated state and clock model, which allows the co‐design of communication and control strategies. Then, an asynchronous localisation algorithm is developed to estimate the position of AUV, where the asynchronous clock and the stratification effect are both considered. With the estimated position information, a reinforcement learning based tracking controller is developed for the AUV to track the reference point. Particularly, the multivariate probabilistic collocation method is adopted to evaluate the model uncertainty. Moreover, the convergence analyses for the localisation algorithm and tracking controller are also given. Finally, simulation results are presented to show the effectiveness of the proposed method. It is demonstrated that the communication energy consumption and tracking error can be significantly reduced, through the co‐design of localisation and tracking strategies. [ABSTRACT FROM AUTHOR]

This study considers the tracking control problem of an uncertain quadrotor unmanned aerial vehicle with model uncertainties and wind gust disturbances, and a novel robust dynamic surface control based multiple state variables constrained control scheme is proposed. Under the presented control framework, the overall quadrotor system is decoupled into a translational subsystem and a rotational subsystem. These two subsystems are connected to each other through common attitude extraction algorithms. For the translational subsystem, the novel robust multiple state variables constrained control inputs are designed to ensure the state variables within the prescribed constraints. For the rotational subsystem, the dynamic surface control based tracking controllers are proposed to track the desired attitudes. In the end, the resulting closed‐loop system is proved to be stable in the sense of uniform ultimate boundness, and numerical simulations and experiments are conducted to validate the feasibility and effectiveness of the designed control scheme. [ABSTRACT FROM AUTHOR]

The problem of tracking control is considered for a class of non‐linear time‐delay systems in the presence of unknown dead‐zone input and tracking error satisfying the prescribed performance. The new state transformation for tracking error is firstly utilised to ensure that the tracking error is within the prescribed boundaries. At the same time, the indirect adaptive neural networks and a new inequality are used to deal with the unknown non‐linear time‐delay terms and the completely unknown dead‐zone input, respectively. Then, the authors design the controller based on the dynamic surface control technique. By constructing the Lyapunov functional, it is shown that the resulting closed‐loop system is stable in the sense of uniformly ultimate boundedness and that the tracking error converges to a small residual set with the prescribed performance. Finally, simulation examples are given and the results show the effectiveness of the proposed control design method. [ABSTRACT FROM AUTHOR]

This study investigates the stabilisation problem for a class of discrete‐time two‐dimensional (2D) switched systems. Here the 2D systems mean that the state evolves following two independent directions, which are usually represented as horizontal states and vertical states. The considered systems are represented by Roesser model and incorporate both stable and unstable modes. Based on a switching signal regulation approach, which restricted the switching number as well as the running time ratio between the unstable and stable modes, the exponential stability condition is established for the 2D switched systems with synchronous switching. Besides, solving the proposed stabilisation results in linear matrix inequality form, the stabilising controller gains can be obtained. Moreover, considering the time delay in the controllers when the switching occurs, the proposed results are extended to the stabilisation problem for the 2D switched systems under asynchronous switching. A numerical example further demonstrates the validity of the developed results. [ABSTRACT FROM AUTHOR]

Wireless control system (WCS) refers to the feedback control system with state and (or) control information transmitted over wireless channels. The control system stability is severely affected by the wireless transmission reliability, which in turn relies heavily on the scheduling of limited wireless communication resources, such as channel, time and power. Therefore, co‐design of control stabilisation and transmission scheduling is of vital importance. In this study, the authors firstly explore the effect of wireless transmission reliability on control performance for a WCS with multiple subsystems, local sensors and a remote combination of controller–scheduler. Then a feedback control method is designed to mitigate the impact of unreliable transmission in the loop of sensor‐to‐controller and controller‐to‐actuator. Stabilisation and transmission scheduling are co‐designed to stabilise the system and minimise the control‐communication cost by solving a mixed‐integer non‐linear programming problem. A decomposition scheme is finally proposed to optimise the control performance by minimising the gap with standard linear quadratic regulator controller as well as the communication cost by allocating the transmission channels, time‐slots and power. The effectiveness and advantage of the proposed scheme are demonstrated by the simulation results for a slab temperature control system in hot rolling process. [ABSTRACT FROM AUTHOR]

In this study, the state feedback fixed‐time control problem is addressed for a class of high‐order strict‐feedback non‐linear systems (SFNSs) with mismatching system uncertainties. Based on the fixed‐time control technique and uniform exact difference method, a new fixed‐time tracking control algorithm via the backstepping method in conjunction with a novel second‐order sliding mode super‐twisting‐like structure adaptive fixed‐time disturbance observer is proposed. Compared with many existing finite‐time control results in which the convergence time grows unboundedly when the system initial conditions grow, the fixed‐time control provides faster convergence rate by using high‐degree terms and the settling time function derived only with controller parameters, is allowed to be adjusted independently of the system initial conditions. Moreover, to avoid the computation explosion, the singularity problem and to relax the assumption on the mismatching system uncertainties, the dynamics surface control method is employed based on a novel non‐linear non‐smooth first‐order filter. Then the semi‐globally uniformly fixed‐time convergent performance of the high‐order SFNSs is achieved. Finally, theoretical results are supported by simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper studies the problem of distributed output feedback consensus tracking control for leader–following non‐linear multi‐agent systems in strict‐feedback form under a directed graph topology with prescribed performance requirement. The unknown external disturbances are considered in the followers. First, the authors design reduced‐order observers to estimate the unmeasured state variables of the followers online. Then, the novel controllers are designed with prescribed performance control based on backstepping method. The dynamic surface control technique is used to deal with the calculating explosion problem. It is strictly proved that the resulting whole system is stable in the sense of semi‐globally uniformly ultimately boundedness and both transient and steady‐state performance of consensus tracking errors are preserved based on Lyapunov stability theory. Finally, a simulation example is presented to verify the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

This study studies the leader–following consensus problem for a class of multi‐agent systems with unknown non‐linear uncertainties. It is proved that the global consensus can be achieved by distributed feedback controller subject to actuator saturation for switching topologies and time‐varying delays. Sufficient conditions in terms of linear matrix inequalities are derived to ensure that all following agents could reach consensus asymptotically with a leader, which provide the allowable upper bound of communication delay. Stability analysis is mainly based on algebraic graph theory, non‐linear analysis and Barbalat's lemma. Numerical simulations are given to demonstrate the effectiveness of the main results. [ABSTRACT FROM AUTHOR]

This study investigates the finite‐time consensus problem of leaderless and leader‐following multi‐agent systems. Two novel nonlinear consensus protocols are presented based on event‐driven strategies, which can significantly reduce the communication consumption and the frequency of the controller updates. It is shown that the multi‐agent system can achieve consensus in finite time under the proposed nonlinear consensus protocols. Moreover, the bound of the triggering interval is provided to illustrate that no Zeno behaviour exists. Finally, some simulations are employed to verify the effectiveness of the proposed consensus protocols. [ABSTRACT FROM AUTHOR]

This study investigates decentralised fault‐tolerant finite‐time stabilisation problem for a class of interconnected non‐linear systems with gain fault in each actuator. Each subsystem of the interconnected system is with lower‐triangular structure. In the procedure of controller design, unknown faults of the system are eliminated via robust control technology. Then, based on finite‐time Lyapunov stability theorem and recursive design algorithm, decentralised state feedback controller is proposed to guarantee global finite‐time stabilisation of the interconnected system. Finally, two simulation examples are given to verify the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]

Vertical take‐off and landing (VTOL) aircraft system is a non‐linear complex system with multi‐variable large‐disturbances. Hence it is a difficult task to control it efficiently. For the first time, this study applies the most advanced kernel‐based dual heuristic programming (DHP) algorithm into solving the optimal control problems of VTOL aircraft systems successfully. Kernel‐based DHP (KDHP) algorithm is developed by integrating sparse kernel machines and approximately linear dependence analysis into the critic learning of DHP algorithm. Kernel machines are used as approximation structure for the critic module in the proposed KDHP algorithm, while multilayer perceptron neural networks (MLPNNs) are used as approximation structure for conventional DHP algorithm. Compared with conventional MLPNNs with manually designed structures, kernel method can obtain better generalisation capability. Hence to a certain extent, the proposed KDHP algorithm has better learning efficiency and generalisation capability. Moreover, the simulation and experimental results of VTOL aircraft system control problems demonstrate that the optimal controller based on the proposed KDHP algorithm is effective. [ABSTRACT FROM AUTHOR]

This study investigates the cooperative linear output regulation problem of heterogeneous multi‐agent systems with periodic switching topologies. A novel distributed adaptive control law is presented based on dynamic state feedback with the feedback gain independent of the Laplacian matrix of the underlying system communication topology. It is shown that the cooperative output regulation problem can be solved under a necessary and sufficient condition. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed control law. [ABSTRACT FROM AUTHOR]

This study studies a distributed estimation problem in relay assisted wireless sensor networks (WSNs). Different from most existing works, the network consists of two kinds of nodes, that is, sensor nodes (SNs) which is capable of sensing and computing and relay nodes (RNs), which is only capable of simple data aggregation. The problem of how to coordinate two kinds of nodes to facilitate distributed estimation is challenging because of their heterogeneous capability. The authors first develop a min‐weighted rigid graph‐based topology optimisation scheme to reduce the redundancy of communication links such that the energy consumption in the relay assisted WSN can be reduced. With the optimised topology, a consensus‐based estimation algorithm is proposed for SNs and RNs, respectively. The asymptotic unbiasedness and consistency of the estimation algorithm are analysed in the presence of measurement and communication noises. The proposed method is applied to estimate the distribution of slab temperature in the hot rolling process. It is demonstrated that the topology optimisation reduces communication energy consumption, while the deployment of RNs improves temperature estimation accuracy as compared to a homogeneous WSN with SNs only. [ABSTRACT FROM AUTHOR]