Predefined-time practical consensus for multi-agent systems via event-triggered control

This paper studies the predefined-time practical consensus problem for multiple single-integrator systems through event-triggered control. A new kind of time-varying functions is firstly proposed. Then, new event-triggered control inputs as well as triggering conditions are designed on the basis of the time-varying function and the local broadcasted states. In particular, the control scheme is fully-distributed because no global information of the system and the communication topology is needed. Furthermore, the consensus analysis is presented based on a sufficient condition for predefined-time practical stability. It illustrates that practical consensus can be ensured with a completely pre-specified time. Besides, the exclusion of Zeno behavior at all the time instants is addressed. Numerical results verify the validity of the obtained control method.     

漂浮基空间机器人的基于模糊神经网络的自适应补偿控制

针对自由漂浮状态的空间机器人模型不确定性及其动力传动机构的摩擦死区非线性,将一种自适应模糊小脑模型关联控制( FCMAC)补偿策略用于轨迹跟踪及补偿问题.利用模糊神经网络并引入GL矩阵及其乘法算子“.”分别对执行机构中的摩擦死区及系统模型不确定部分进行自适应补偿,其补偿误差及外界扰动通过滑模控制器来消除.基于Lyapunov理论证明了闭环系统跟踪误差的有界性.仿真表明控制器可以达到较高精度,且能满足实时性要求.     

EKF enhanced MPC for rapid attitude stabilization of space robots with bounded control torque in postcapture

Space robots play a more and more important role in on-orbit service missions. It is essential for a space robot to stabilize its attitude rapidly after capturing an unknown target, because of its residual momentum. Regarding uncertainties in inertial parameters of the target, process and measurement, and insufficient measurements, this paper first presents extended Kalman filter (EKF) enhanced model predictive control (MPC) strategy for rapid attitude stabilization of space robots with bounded control torque of the actuator and the manipulator in postcapture, in which motion of the manipulator is planned to make up for the limitation of the actuator. Thanks to the Jacobian matrix, which is required for EKF, the linear varying time-MPC is applied to handle the constraints of the drive torque, which can be solved by the online active set method effectively and efficiently. Simulation has been done for the 2D and the 3D models, and the results show that the whole system, including the base and the manipulator can be stabilized, and inertial parameters of the target can converge to their ideal values with the constraints. In addition, robustness of the presented method has been verified by Monte Carlo simulation.     

Stochastic control and time scheduling for irregular robots

Vehicles of different sizes are difficult to navigate in close vicinity. In this paper, we propose multi-vehicle coordination strategy by stochastic control and time scheduling to guarantee no collisions. We use contours and relative motions of vehicles to calculate collision time and use it in multi-vehicle scheduling and reduce computation burden. The proposed strategy enables the vehicles to add calculation delay when vehicles are moving towards the destinations. To avoid complicated control rule design for motion-restricted irregular vehicles, we propose stochastic control to provide satisfactory performance. By changing the frequency of control update, a modification is proposed to take congestion into account. Simulation examples are given to demonstrate the effectiveness of the proposed approach.     

Operational space consensus of multiple heterogeneous robots without velocity measurements

This paper proposes a control algorithm for networks of multiple heterogeneous robot manipulators, which solves the leader–follower and the leaderless consensus problems in the operational space. In the leader–follower scenario, the controller ensures that all the robots in the network asymptotically reach a given leader pose (position and orientation), provided that, at least, one follower robot has access to the leader pose. Without a leader pose, in the leaderless problem, the robots asymptotically reach a pose of consensus. The controller is a simple distributed proportional plus damping injection (P+d) scheme which does not require velocity measurements. A singularity-free representation, unit quaternions, is used to describe the orientation of each manipulator. The paper presents some simulations, with a network of six 6-Degrees-of-Freedom (DoF) manipulators, and experiments, with a network of three 6-DoF manipulators, to show the effectiveness of the proposed controller.     

Energy-Time optimal control of wheeled mobile robots

This paper focuses on the energy-time optimal control of wheeled mobile robots undergoing point-to-point transitions in an obstacles free space. Two interchangeable models are used to arrive at the necessary conditions for optimality. The first formulation exploits the Hamiltonian, while the second formulation considers the first variation of the augmented cost to derive the necessary conditions for optimality. Jacobi elliptic functions are shown to parameterize the closed form solutions for the states, control and costates. Analysis of the optimal control reveal that they are constrained to lie on a cylinder whose circular cross-section is a function of the weight penalizing the relative costs of time and energy. The evolving optimal costates for the second formulation are shown to lie on the intersection of two cylinders. The optimal control for the wheeled mobile robot undergoing point-to-point motion is also developed where the linear velocity is constrained to be time-invariant. It is shown that the costates are constrained to lie on the intersection of a cylinder and an extruded parabola. Numerical results for various point-to-point maneuvers are presented to illustrate the change in the structure of the optimal trajectories as a function of the relative location of the terminal and initial states.     

Predefined-time hierarchical controller-estimator time-varying formation-containment tracking for multiple Euler-Lagrange systems with two-layer leaders

This paper mainly discusses the problem of the predefined-time time-varying formation-containment tracking (TVFCT) for the multiple Euler-Lagrange systems (MELSs), where the external disturbances are taken into consideration. To cope with the above problem, a two-layer formation-containment tracking (FCT) framework is established, namely, the real leaders’ formation layer and the followers’ containment layer, where the analysis of the system is executed step by step. Meanwhile, the corresponding hierarchical control algorithms based on nonsingular terminal sliding mode are designed for different layers to facilitate the implementation of the TVFCT control problem. With the help of the Lyapunov function and predefined-time stability theory, some sufficient criteria for the convergence of the proposed algorithms are provided. In the end, the simulation results demonstrate the effectiveness of the theoretical results and the designed controller.     

Distributed-parameter control in function space

Optimal control of distributed-parameter systems is studied from a function space point of view. The adjoint-space technique of Balakrishnam is applied to solve a general class of linear distributed-parameter final-value problems in Hilbert space. The minimum-time control problem with multi-norm constraints for a general class of approximately controllable systems is treated, using the technique of Sarachik and Kranc, through the application of Hölder's inequality. Finally, a generalized Hölder's inequality for more than two Banach spaces is given, which is useful for solving a certain class of nonlinear control problems by the same methods. Two examples are included which illustrate the theory.     

A dynamic output feedback control law for elastic joint robots via feedback-passivity approach

Motivated by recent dynamic output feedback passivation results, a new set-point control law is presented for an elastic joint robot when the velocity measurements are not available. The proposed methodology designs an additional dynamics with which the parallel-connected system is feedback passive. That is, the composite nonlinear robot system has relative degree one with a new output and its zero-dynamics subsystem becomes the virtual closed-loop system with a simple proportional-derivative (PD) control law. This approach provides an alternative way of replacing the role of the velocity measurements for the PD law. With the proposed control law, the transfer function of the additional system has the form of sG(s) with a strictly positive real (SPR) G(s). Robustness analysis is also given with regard to uncertainties on the robot parameters. The performance of the proposed control law is illustrated in the simulation studies of a manipulator with three revolute elastic joints.     

Robust cooperative control for a group of mobile robots with quantized information exchange

In this paper we investigate the cooperative tracking control problem with quantized time delay information exchange for a group of wheeled mobile robots networked through a connected graph modeling the underlying communication topology. A cooperative controller is proposed using a combination of backstepping technique, graph theory and neural network radial basis functions. We show, using the small gain theorem, that the states of each mobile robot in the group converge to and remain inside a tube centered around its assigned trajectory to form a desired geometric pattern whose centroid is assumed to move along a predefined trajectory. Experimental results on a group of three mobile robots forming a triangular shape are presented to demonstrate the good performance of the proposed cooperative controller.     

Model predictive tracking control with disturbance compensation for wheeled mobile robots in an environment with obstacles

This paper explores the trajectory tracking control problem for a wheeled mobile robot (WMR) in an environment with obstacles and unknown disturbances. A fixed-time extended state observer is presented, which is utilized to estimate unknown disturbances and improve the convergence speed of estimation errors. By introducing the obstacle avoidance cost, a model predictive controller with disturbance compensation is proposed to guarantee desired tracking performance in the presence of obstacles. The proposed method is analyzed for recursive feasibility and closed-loop system stability subject to unknown disturbances and obstacles. Finally, both simulation and experiment are conducted to express the satisfactory tracking effect of the developed approach.     

Leader-following consensus control of multiple nonholomomic mobile robots: An iterative learning adaptive control scheme

In this paper, the distributed iterative learning control for nonholonomic mobile robots with a time-varying reference is investigated, in which the mobile robots are with parametric uncertainties and are not fully actuated. Besides, the control gains of mobile robots are unknown. The leader is with a time-varying reference trajectory, and there is no need to assume that the time-varying reference is linearly parameterized by a set of known functions. A distributed control scheme is designed for each mobile robot based on a set of local compensatory filters designed by its neighborhood information. Stability analysis is established through a set of composite energy function. The uniform convergence of the consensus errors can be guaranteed. An example is given to show that our designed control law is effective.     

Adaptive perturbation rejection control and driving voltage circuit designs of wheeled mobile robots

This paper addresses the robust trajectory tracking control problem for a class of wheeled robotic systems with perturbations caused by measurement errors, internal uncertainties, and exogenous disturbances. An adaptive technique is utilized to estimate the effects of perturbations. Then, on the basis of the adaptive estimations, perturbation rejection control schemes are developed to construct the kinematic control and dynamic control strategies. By utilizing Lyapunov stability theory, bounded tracking of the desired trajectory and asymptotic tracking of auxiliary azimuthal angular velocity and forward speed of the robot can be achieved respectively in the fact of perturbations. Furthermore, the adaptive perturbation rejection control (APRC) strategies are implemented physically by analog circuits to generate driving voltages of DC motors in the robot reality. The efficiency of the proposed trajectory tracking control method is validated by a robotic system.     

Adaptive neural finite-time control for space circumnavigation mission with uncertain input constraints

This paper explores the design of an anti-saturation adaptive finite-time control strategy with the neural network (NN) technique for the space circumnavigation mission. Before executing the controller design, the analytical solutions of the desired angular velocity and its derivative of the active spacecraft are calculated. Since there are uncertain saturation constraints on control forces and moments in the actual propulsion system, an auxiliary system compensated by an adaptive NN is adopted. The modified auxiliary system no longer needs the precise output values of the actuators. Besides, the hyperbolic tangent function is introduced to design the weight update law for the NN compensator, so that the derivative of the weight estimator will not be amplified by the quadratic of states when the system states are large. It is proved that tracking errors of the system states can converge to a residual set of the origin in finite time. Simulation results show that the maximum amplitudes of the control signals are greatly reduced compared to the classical non-singular terminal sliding-mode control scheme, and that the neural-based compensator can significantly weaken the overshoot and chattering.     

Effects of emotion control and task on Web searching behavior

The study investigated how users’ emotion control and search tasks interact and influence the Web search behavior and performance among experienced Web users. Sixty-seven undergraduate students with substantial Web experience participated in the study. Effects of emotion control and tasks were found significant on the search behavior but not on the search performance. The interaction effect between emotion control and tasks on the search behavior was also significant: effects of users’ emotion control on the search behavior varied depending on search tasks. Profile analyses of search behaviors identified and contrasted the most commonly occurring profiles of search activities in different search tasks. Suggestions were made to improve information literacy programs, and implications for future research were discussed.     

Simulation of small humanoid robots for soccer domain

In this paper, we illustrate the development of a realistic simulation of a humanoid robot model in a virtual environment using USARSim (Urban Search and Rescue Simulator). USARSim provides an accurate 3D simulation of a virtual environment with a detailed rendering and a realistic physics. Moreover, USARSim allows users to observe the virtual environment from different views. One of these is the egocentric view, which can simulate the camera mounted on the robot. The small humanoid robot presented in this work is Robovie-M, developed by VStone Ltd. (Japan). This robot is used by our team Artisti in the RobotCup soccer competitions.Reported experiments compare the behaviors of a real robot and of its virtual model, when controlled by the same control software to asses the possibility to faithfully simulate a robot with 22 degrees of freedom in USARSim. Moreover, we discuss the possibility to close the control loop of the robot in simulation, by simulating also the main robot sensor, i.e. the camera.The experiments show that USARSim, despite being a simple simulator based on a low cost computer game, provides an accurate enough simulation of the physics and a realistic rendering of the 3D scene enabling a faithful simulation of a small humanoid robot at low cost. Thus, one can entirely test the robot software modules in the simulation (namely: the motion control modules, the vision system modules and, by closing the robot control loop in simulation, the behavior and behavior-selection modules).     

Discrete-time synchronization strategy for input time-delay mobile robots

This paper considers a synchronization strategy for a group of differentially driven mobile robots subject to input time-delayed control signals. The continuous time model of the vehicles is exactly discretized in order to obtain a larger dimension representation free of delays. The control strategy is based on the concept of synchronization, under two main assumptions: a specific formation for the group of robots and the tracking of a particular desired trajectory. The control strategy proposed in this work allows the consideration of causal feedback laws avoiding the use of an additional prediction strategy that counteracts the undesired input time-delay effects. The performance of the synchronization strategy is evaluated by real-time experiments with the help of a group of three mobile robots and an indoor absolute localization system based on artificial vision.     

Composite fuzzy voltage-based command-filtered learning control of electrically-driven robots with input delay using disturbance observer

This paper presents an improved composite fuzzy learning control for uncertain electrically-driven robot manipulators with input delay and the external disturbances. In the framework of the backstepping algorithm, fuzzy systems are employed to approximate the unknown terms where the accuracy of fuzzy learning is also considered by defining prediction errors. With the aid of integral technique and the dynamic surface control, a variable is engendered for the system in such a way that the input-delayed robotic system is converted to the non-delayed robotic system. Besides, the command-filtered control is used to cope with the complexity explosion of the backstepping-based design. In order to improve the robust behavior of the control system, the proposed control scheme is equipped with disturbance observers (DOBs). Different from the previous works, the information of the input-delayed, the compensated error surfaces (obtained from the command-filtered approach), the prediction errors and the disturbance estimations (derived from DOBs) are unified to construct the proposed control framework. The stability of the overall system is verified by the Lyapunov theorem. The efficiency of the proposed concept is illustrated using various simulations for an electrically-driven robot manipulator in the presence of uncertainties.     

Predictive motion control for autonomous capture of a tumbling target with a space manipulator

In this study, an autonomous capture framework was proposed for a tumbling target satellite with a space manipulator. First, the motion model of a tumbling target was constructed and the motion properties were analyzed. Subsequently, a predictive motion control method was introduced to compensate for the time delay owing to image processing and to predict the tumbling motion of the target. Stability analysis was conducted using a Lyapunov function. To address the problem of large position and attitude deviations of the tumbling target, different autonomous capture strategies, that is, non-fixed-point position-based capture and area-based capture, were proposed to capture different parts of the target, such as the docking ring and side surfaces, which are important for practical applications. The capture conditions were created and compared, where the non-fixed-point position capture strategy and area-based capture strategy had a larger pose tolerance than the traditional fixed-point position methods. Finally, the framework was tested using Adams/Simulink co-simulations. The results validated the autonomous capture process and proposed alternatives for practical applications.     

空间通信网中音视频传输的应用层QoS控制与测试方法

分析了无线局域网、因特网和Ku频段卫星通信网的互联互通及服务质量(QoS)性能参数,采用视频帧率、分辨率自适应算法,提出了一种空间通信网中音视频传输的应用层QoS控制与测试方法.仿真实验结果表明,该方法提高了网络利用率,并具有良好的QoS自适应帧率调整能力.