Dynamic control and coupling of a free-flying space robot system

In this article we discuss the problem of dynamic coupling and control of a space robot with a free-flying base, which could be a spacecraft, space station, or satellite. We formulate the dynamics of the system systematically and demonstrate nonlinearity of parameterization of the dynamics structure. We study the dynamic coupling of the robot and base system, and propose a concept, i.e., coupling factor, to illustrate the motion and force dependencies. Based on the coupling factor, we define a measure to characterize the degree of the dynamic coupling. The measure can be considered as a performance index in planning robot motion, or in evaluating robot trajectory for minimizing base motion, or in optimizing the robot configuration design and selecting the robot base location. Based on the dynamics analysis, we propose control schemes for position regulation and trajectory tracking problems. The regulation controller is simple to implement and will be useful in regular material transporting tasks. The tracking controller uses a dynamic model and provides more accurate and faster motion, and will be feasible for tracking moving objects or structural inspection tasks. A simulation study is shown at the end of the article. © 1994 John Wiley & Sons, Inc.     

自由飞行空间机器人的遥操作分数阶PID控制

作为空间操控的重要手段, 空间遥操作将趋向于更精细和更灵活. 然而传统的空间遥操作控制方法难以兼 顾操作的精细性和灵活性. 针对这一问题, 本文阐述了一种面向自由飞行空间机器人的遥操作分数阶PID控制方法. 首先根据自由飞行空间机器人的动力学模型, 设计了空间遥操作分数阶PID控制系统. 其次, 针对空间遥操作时滞 系统和系统的鲁棒性和抗干扰性要求, 基于系统的参数稳定域, 对分数阶PID控制器的参数进行整定. 最后, 数值仿 真和地面遥操作实验验证了分数阶PID控制器的跟踪性能、抗干扰性、鲁棒性和抗时延抖动性能. 因此, 本文设计的 分数阶PID控制器不仅适合于空间遥操作复杂时滞系统, 而且可以满足未来空间遥操作任务的发展需求.     

Robust adaptive tracking control of an underactuated ship with guaranteed transient performance

In this paper, a robust adaptive controller for a underactuated ship is proposed to make the ship follow a predefined path with guaranteed transient performance and arbitrarily small steady-state position error and orientation error, despite the presence of environmental disturbances induced by wave, wind and ocean current and unknown system parameters. We design a new adaptive state feedback controller and parameter estimators to guarantee converging exponentially by assuming all states are available. It is shown that the mean-square tracking errors are of order of an arbitrarily small design parameter, and the position error and the orientation error also decrease at a pre-specified exponential rate. Simulations with a commercial monohull ship using Matlab also demonstrate the effectiveness of the controllers.     

Robust adaptive control for robot manipulators

A composite adaptive control law for robot manipulators in task space, which uses both the tracking error and the prediction error to drive parameter estimation, is developed in this paper. It is shown that global stability and convergence can be achieved for the adaptive control algorithm in the ideal case, and furthermore that the algorithm can be easily modified by using parameter projection to achieve robustness with respect to a class of unmodelled dynamics. In addition, the algorithm has the advantage that no requirement is needed for the inverse of the jacobian matrix or for the bounded inverse of the estimated inertia matrix. A simulation example is provided for performance demonstration.     

Robust adaptive decentralized control of robot manipulators

The authors proposes a robust adaptive decentralized control algorithm for trajectory tracking of robot manipulators. The controller is designed based on a Lyapunov method, which consists of a PD (proportional plus derivative) feedback part and a dynamic compensation part. It is shown that, without any prior knowledge of manipulator or payload parameters and possibly under deterioration of parameter variation with time or state-independent input disturbances, the tracking error is bound to converge to zero asymptotically. In particular, the algorithm does not require explicit system parameter estimation and therefore makes the controller structurally simple and computationally easy. Moreover, the controller is implemented in a decentralized manner, i.e. a subcontroller is independently and locally equipped at each joint servoloop. To illustrate the performance of the controller, a numerical simulation example is provided     

Robust chattering-free sliding mode control of space robot in task space

This paper studies the tracking control problem of a free-floating space robot in a task space. Considering the model uncertainties and external disturbance, a robust sliding mode controller is proposed using the Lyapunov direct method and dissipative theory. To eliminate the chattering phenomenon, an radial basis function （RBF） neural network is applied to replace the discontinuous part of the control signal. A novel on-line learning method of the weights and parameters of the RBF neural network established using Lyapunov function assures the stability of the system. It is proved that the proposed controller can guarantee that the L2 gain from disturbance to tracking error is lower than the given index y. Simulation results show that the control method is valid.     

Robust chattering-free sliding mode control of space robot in task space

This paper studies the tracking control problem of a free-floating space robot in a task space. Considering the model uncertainties and external disturbance, a robust sliding mode controller is proposed using the Lyapunov direct method and dissipative theory. To eliminate the chattering phenomenon, an radial basis function (RBF) neural network is applied to replace the discontinuous part of the control signal. A novel on-line learning method of the weights and parameters of the RBF neural network established using yapunov function assures the stability of the system. It is proved that the proposed controller can guarantee that the L(/sub 2) gain from isturbance to tracking error is lower than the given index γ. Simulation results show that the control method is valid.     

Some issues of controlling the free-flying manipulative space robot

A brief review of the state-of-the-art in the control of free-flying space robots in the modes of manipulative target lockon by planning the gripper trajectory was presented. For the class of feedback systems, an alternative approach to this problem was proposed. Within the framework of this approach, consideration was given to the problems of constructing the working zone of the space manipulative robot and generating an algorithm to control the manipulative positioning of the load at the desired point of the inertial space with the availability of information about the direction to the target and the distance to it which is acquired using a camcorder mounted at the end link of the manipulator. Examples were presented of computer-aided construction of the working zone and modeling the space robot dynamics which corroborate operability of the proposed algorithm.     

Robust adaptive path following of underactuated ships

Robust path following is an issue of vital practical importance to the ship industry. In this paper, a nonlinear robust adaptive control strategy is developed to force an underactuated surface ship to follow a predefined path at a desired speed, despite the presence of environmental disturbances induced by wave, wind and ocean-current. The proposed controller is scalable and is designed using Lyapunov's direct method and the popular backstepping and parameter projection techniques. Along the way of proving closed-loop stability, we obtain a new stability result for nonlinear cascade systems with non-vanishing uncertainties. Interestingly, it is shown in this paper that our developed control strategy is easily extendible to situations of practical importance such as parking and point-to-point navigation. Numerical simulations using the real data of a monohull ship are provided to illustrate the effectiveness of the proposed methodology for path following of underactuated ships.     

Robust adaptive control of a bio-inspired robot manipulator using bat algorithm

This paper proposes a novel adaptive fractional order PID sliding mode controller (AFOPIDSMC) using a Bat algorithm to control of a Caterpillar robot manipulator. A fractional order PID (FOPID) control is applied to improve both trajectory tracking and robustness. Sliding mode controller (SMC) is one of the control methods which provides high robustness and low tracking error. Using hybridization, a new combined control law is proposed for chattering reduction by means of FOPID controller and high trajectory tracking through using SMC. Then, an adaptive controller design motivated from the SMC is applied for updating FOPID parameters. A metaheuristic approach, the Bat search algorithm based on the echolocation behavior of bats is applied for optimal design of the Caterpillar robot in order to tune the parameter AFOPIDSMC controllers (BA-AFOPIDSMC). To study the effectiveness of Bat algorithm, its performance is compared with five other controllers such as PID, FOPID, SMC, AFOPIDSMC and PSO-AFOPIDSMC. The stability of the AFOPIDSMC controller is proved by Lyapunov theory. Numerical simulation results completely indicate the advantage of BA-AFOPIDSMC for trajectory tracking and chattering reduction.     

Robust adaptive path-following control of underactuated marine vessel with off-track error constraint

In this paper, a new robust adaptive controller is investigated to force an underactuated surface marine vessel to follow a predefined parameterised path at a desired speed, despite actuator saturation and the presence of model uncertainties as well as environmental disturbances induced by waves, wind and sea-currents. To ensure robustness of the path-following controller, time-varying constraint on the off-track error (i.e. the maximal distance from the ship to the reference path) is considered. To address the off-track error constraint the tan-barrier Lyapunov function is incorporated with the control scheme, where the idea of auxiliary design system introduced in Chen, Sam, and Ren (2011) is adopted and its states are used in combination with backstepping and Lyapunov synthesis to adaptive tracking control design with guaranteed stability. Furthermore, the command filters are adopted to implement physical constraints on the virtual control laws so that analytic differentiation of the virtual control laws is avoided. We show that the proposed robust adaptive control law is able to guarantee semi-global uniform ultimate bounded stability of the closed-loop system. Numerical simulations and experimental results are carried out to demonstrate the effectiveness of the proposed algorithm.     

Robust adaptive control for a nonholonomic mobile robot with unknown parameters

A robust adaptive controller for a nonholonomic mobile robot with unknown kinematic and dynamic parameters is proposed. A kinematic controller whose output is the input of the relevant dynamic controller is provided by using the concept of backstepping. An adaptive algorithm is developed in the kinematic controller to approximate the unknown kinematic parameters, and a simple single-layer neural network is used to express the highly nonlinear robot dynamics in terms of the known and unknown parameters. In order to attenuate the effects of the uncertainties and disturbances on tracking performance, a sliding mode control term is added to the dynamic controller. In the deterministic design of feedback controllers for the uncertain dynamic systems, upper bounds on the norm of the uncertainties are an important clue to guarantee the stability of the closed-loop system. However, sometimes these upper bounds may not be easily obtained because of the complexity of the structure of the uncertainties. Thereby, simple adaptation laws are proposed to approximate upper bounds on the norm of the uncertainties to address this problem. The stability of the proposed control system is shown through the Lyapunov method. Lastly, a design example for a mobile robot with two actuated wheels is provided and the feasibility of the controller is demonstrated by numerical simulations.     

Robust tracking control of an electrically driven robot: adaptive fuzzy logic approach

This paper is concerned with the robust tracking control of an electrically driven robot with the model uncertainties in the robot dynamics and the motor dynamics. The motors driving the joints of the robot are assumed to be equipped with only the joint position and the current measurement devices. Adaptive fuzzy logic and adaptive backstepping method are employed to provide the solution to the control problem. The suggested method does not require the measurement of the velocity nor the acceleration. Simulation results from a two-link electrically driven robot show the satisfactory performance of the proposed control scheme even in the presence of internal model uncertainties in both the robot and motor dynamics and external disturbances.     

考虑关节柔性的绳驱动空中机械臂关节空间鲁棒控制

空中机械臂在外部环境交互作业方面表现出很强的研究和应用价值,但当前系统位姿控制性能较弱、负载能力不足以及续航时间短的问题严重制约其作业能力的提升.鉴于此,设计一种带有绳驱动机械臂的新型空中机械臂系统,并将引入绳驱动机制带来的柔性效应等价到关节处,建立考虑关节柔性的刚柔耦合动力学模型.首先,针对系统在集总干扰下的关节空间轨迹跟踪控制,采用线性扩张状态观测器对集总干扰进行估计和补偿,并采用超螺旋算子和分数阶非奇异终端滑模以保证系统在到达阶段和滑模阶段均有较好的控制性能;然后,在Lyapunov稳定性框架下验证所设计控制器的稳定性;最后,通过可视化仿真和地面实验对所设计控制器的有效性进行验证.实验结果表明,所设计的鲁棒控制器比其他两种现有的控制器具有更快的响应速度、更强的抗干扰能力以及更高的跟踪精度,能够满足绳驱动空中机械臂的控制需求.     

不确定性自由漂浮空间机器人神经自适应控制

针对具有模型不确定性以及外部干扰下的自由漂浮空间机器人,采用一种整体逼近的神经网络自适应控制方法。该方法采用RBF神经网络对不同重力环境下系统模型的不确定项进行整体逼近,对系统的不确定项进行在线自适应学习。神经网络的逼近误差以及外界干扰由鲁棒项进行消除。该方法不依赖于系统模型,简化了控制系统的结构,在考虑重力等不确定项的情况下不用改变控制器也能进行控制,并且根据李亚普诺夫理论证明了所设计控制器使系统渐进稳定。在不同重力环境下进行了仿真,验证了控制方案的有效性。     

Robust adaptive trajectory tracking control of underactuated autonomous underwater vehicles with prescribed performance

In this paper, a novel robust adaptive trajectory tracking control scheme with prescribed performance is developed for underactuated autonomous underwater vehicles (AUVs) subject to unknown dynamic parameters and disturbances. A simple error mapping function is proposed in order to guarantee that the trajectory tracking error satisfies the prescribed performance. A novel additional control based on Nussbaum function is proposed to handle the underactuation of AUVs. The compounded uncertain item caused by the unknown dynamic parameters and disturbances is transformed into a linear parametric form with only single unknown parameter called virtual parameter. On the basis of the above, a novel robust adaptive trajectory tracking control law is developed using dynamic surface control technique, where the adaptive law online provides the estimation of the virtual parameter. Strict stability analysis indicates that the designed control law ensures uniform ultimate boundedness of the AUV trajectory tracking closed‐loop control system with prescribed tracking performance. Simulation results on an AUV in two different disturbance cases with dynamic parameter perturbation verify the effectiveness of our adaptive trajectory tracking control scheme.     

欠驱动两足步行机器人侧向稳定控制方法研究

以欠驱动两足步行机器人为对象研究其侧向运动稳定控制问题。首先分析引起机器人侧向运动不稳定的原因,然后提出步宽控制和侧向力矩补偿两种控制策略。步宽控制通过控制机器人侧向落脚位置,使其侧向运动周期与前向周期趋于一致实现侧向运动稳定。力矩补偿控制通过在踝关节引入侧向控制力矩,使侧向运动与前向运动协调一致实现侧向运动稳定。仿真实验表明,机器人实现了稳定的3D动态行走,达到了预期的控制效果。     

漂浮基空间机器人的径向基神经网络鲁棒自适应控制

针对一类同时具有参数及非参数不确定性的自由漂浮空间机器人系统的轨迹跟踪问题,采用了一种RBF神经网络的自适应鲁棒补偿控制策略.对于系统的参数不确定性,通过对径向基神经网络来自适应学习并补偿,逼近误差通过滑模控制器消除,神经网络权重的自适应修正规则基于Lyapunov函数方法得到;而非参数不确定通过鲁棒控制器来实时自适应...     

Robust variable structure model reference adaptive control

A new variable structure model reference adaptive control scheme is proposed in this paper to achieve robustness to bounded disturbance. A key feature of this scheme is that the knowledge of neither the upper bound on the disturbance nor the upper bound on the norm of the matching controller parameters is required. Another advantage of the scheme is its zero output error tracking     

Hierarchical control structure of a multilegged robot for environmental adaptive locomotion

We propose a biomimetic, two-layered, hierarchical control structure for adaptive locomotion of a hexapod robot. In this structure, the lower layer consists of six uniform subsystems. Each subsystem interacts locally with its neighboring subsystems, and autonomously controls its own leg movements according to the weighted sum of three basic vector fields that represent the three basic motion patterns of the robot body. The upper-layer controller decides the intended body movement, and sends the lower-layer controllers three variables as the weights of each basic vector field. This approach greatly reduces the communication between the two layers, and contributes to real-time adaptive locomotion. 3D dynamic simulations, as well as experiments with a real modularized hexapod robot, show the effectiveness of this hierarchical structure. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001