Motion/force tracking control of nonholonomic mechanical systems via combining cascaded design and backstepping

This paper considers motion/force tracking control of a class of Lagrange mechanical systems with classical nonholonomic constraints. A tracking control method is proposed by combining cascaded methods and backstepping techniques. The main results of this paper include three parts: (1) error dynamics between the kinematic system and the desired paths are transformed into a cascaded system consisting of two subsystems and an interconnection function; (2) under the framework of cascaded methods, virtual controllers for the subsystems are designed to stabilize the error dynamics; (3) the tracking controller is designed for the overall mechanical systems using backstepping techniques.     

Mu-based trajectory tracking control for a quad-rotor UAV

In this paper, the design and application of a robust mu-synthesis-based controller for quad-rotor trajectory tracking are presented. The proposed design approach guarantees robust performance over a weakly nonlinear range of operation of the quad-rotor, which is a practical range that suits various applications. The controller considers different structured and unstructured uncertainties, such as unmodeled dynamics and perturbation in the parameters. The controller also provides robustness against external disturbances such as wind gusts and wind turbulence. The proposed controller is fixed and linear; therefore, it has a very low computational cost. Moreover, the controller meets all design specifications without tuning. To validate this control strategy, the proposed approach is compared to a linear quadratic regulator (LQR) controller using a high- fidelity quad-rotor simulation environment. In addition, the experimental results presented show the validity of the proposed control strategy.     

基于扰动观测器的机器人自适应神经网络跟踪控制研究

为解决机器人动力学模型未知问题并提升系统鲁棒性,本文基于扰动观测器,考虑动力学模型未知的情况,设计了一种自适应神经网络（Neural network,NN）跟踪控制器.首先分析了机器人运动学和动力学模型,针对模型已知的情况,提出了刚体机械臂通用模型跟踪控制策略;在考虑动力学模型未知的情况下,利用径向基函数（Radial basis function,RBF）神经网络设计基于全状态反馈的自适应神经网络跟踪控制器,并通过设计扰动观测器补偿系统中的未知扰动.利用李雅普诺夫理论证明所提出的控制策略可以使闭环系统误差信号半全局一致有界（Semi-globally uniformly bounded,SGUB）,并通过选择合适的增益参数可以将跟踪误差收敛到零域.仿真结果证明所提出算法的有效性并且所提出的控制器在Baxter机器人平台上得到了实验验证.     

Distributed adaptive control for consensus tracking with application to formation control of nonholonomic mobile robots

In this paper, we investigate the output consensus problem of tracking a desired trajectory for a class of systems consisting of multiple nonlinear subsystems with intrinsic mismatched unknown parameters. The subsystems are allowed to have non-identical dynamics, whereas with similar structures and the same yet arbitrary system order. And the communication status among the subsystems can be represented by a directed graph. Different from the traditional centralized tracking control problem, only a subset of the subsystems can obtain the desired trajectory information directly. A distributed adaptive control approach based on backstepping technique is proposed. By introducing the estimates to account for the parametric uncertainties of the desired trajectory and its neighbors’ dynamics into the local controller of each subsystem, information exchanges of online parameter estimates and local synchronization errors among linked subsystems can be avoided. It is proved that the boundedness of all closed-loop signals and the asymptotically consensus tracking for all the subsystems’ outputs are ensured. A numerical example is illustrated to show the effectiveness of the proposed control scheme. Moreover, the design strategy is successfully applied to solve a formation control problem for multiple nonholonomic mobile robots.     

具有未知动态的船舶编队输出反馈控制

研究了仅利用相对位置信息和相对航向信息的船舶编队输出反馈控制问题.首先使用leader-follower策略,建立了船舶编队的运动学模型.然后应用微分同胚变换将系统解耦成3个子系统.根据船舶低频运动的特点,在跟随船水动力学模型中粘性水动力和力矩未知以及所有船舶速度都不可测量的假定下,提出了一种高增益广义比例积分观测器来估计这些未知和不可测量动态.在高增益广义比例积分观测器的基础上,分别设计了线性输出反馈控制器和输入饱和受限的输出反馈控制器,并分析了闭环系统的稳定性.最后仿真结果表明了方法的有效性.     

无人直升机航向自抗扰控制

针对无人直升机系统航向通道扰动大等问题,本文设计了一种自抗扰控制算法来实现其高性能控制.首先分析了航向通道的动态模型,并通过数学变换,将其转化为一类二阶系统;在此基础上,本文设计了适用于无人机航向通道的自抗扰控制策略,它由跟踪微分器、扩展状态观测器、控制器3个环节构成.本文对所设计的自抗扰控制策略进行了仿真和实验测试,并与常见的串级控制方法进行了对比分析.仿真与实验结果表明:这种自抗扰控制策略具有对扰动抑制能力强、控制精度高等优点,其控制性能明显优于常规的串级比例–积分–微分控制方法.     

Dynamic Modeling and Tracking Control of a Nonholonomic Wheeled Mobile Manipulator with Dual Arms

This paper presents methodologies for dynamic modeling and trajectory tracking of a nonholonomic wheeled mobile manipulator (WMM) with dual arms. The complete dynamic model of such a manipulator is easily established using the Lagrange’s equation and MATHEMATICA. The structural properties of the overall system along with its subsystems are also well investigated and then exploited in further controller synthesis. The derived model is shown valid by reducing it to agree well with the mobile platform model. In order to solve the path tracking control problem of the wheeled mobile manipulator, a novel kinematic control scheme is proposed to deal with the nonholonomic constraints. With the backstepping technique and the filtered-error method, the nonlinear tracking control laws for the mobile manipulator system are constructed based on the Lyapunov stability theory. The proposed control scheme not only achieves simultaneous trajectory and velocity tracking, but also compensates for the dynamic interactions caused by the motions of the mobile platform and the two onboard manipulators. Simulation results are performed to illustrate the efficacy of the proposed control strategy.     

基于Lyapunov方法和快速终端滑模的轨迹跟踪控制

针对移动机器人的运动学模型,提出一种具有全局渐近稳定性的跟踪控制器。该跟踪控制器的设计分为两部分：第一部分是采用全局快速终端滑动模态的思想设计了角速度的控制律,用来渐近镇定移动机器人跟踪的前向角误差;第二部分是采用Lyapunov方法设计了线速度的控制律,用来渐近镇定移动机器人跟踪的平面坐标误差。采用Lyapunov稳定性定理,证明了移动机器人在满足这些控制律条件下,实现了对参考轨迹的全局渐近跟踪。实验结果表明移动机器人能够有效地跟踪期望轨迹,有利于在实际应用中推广。     

Global asymptotic tracking of asymmetrical underactuated surface vessels with parameter uncertainties

In this work, we investigate the tracking control problem of asymmetrical underactuated surface vessels with parameter uncertainties. The tracking error model is first derived via appropriate coordinate transformations, and is considered as a cascade structure composed of two subsystems. The Lyapunov redesign approach is employed to construct the control laws separately to stabilize the two subsystems with unknown model parameters. The cascade system theory is applied to prove the global uniform asymptotic convergence of the state trajectory to the reference one provided the desired yaw velocity is not vanishing. The effectiveness of the proposed control laws is verified by simulation examples.     

Trajectory linearization based output tracking control of an unmanned tandem helicopter with variance constraints

An output tracking control problem for an unmanned tandem rotor helicopter with variance constraints is investigated in this paper. A modified Trajectory Linearization Control (TLC) is proposed to stabilize a nonlinear continuous-time flight dynamics system of the tandem helicopter. The tracking controller structure of TLC is designed by using two-time-scale nonlinear dynamic inversion. The base control law of the translational and attitude loops is designed in a pseudo-inversion feedforward controller to deal with nonlinear features of the plant and a proportional integral controller to stabilize the linear slowly time-variant error system resulted from the nonlinear flight system. Furthermore, a feasible TLC strategy is designed to meet a performance index set including steady trajectory tracking error variance and desired Parallel D-spectrum (PD-) eigenvalues to achieve good flight quality. The Variance-constrained Trajectory Linearization Control (VCTLC) is designed to realize the desired steady tracking precision and agile capability. Flight simulation results show the VCTLC method is feasible and effective in attitude and altitude tracking.     

基于神经滑模的柔性连杆机械手末端位置控制

：为了提高柔性机械手末端位置控制的鲁棒性和精度,提出了一种基于神经滑模的控制策略．首先采 用输入/输出线性化方法将动力学模型部分线性化,使之分成输入/输出子系统与内动态子系统．输入/输出子系统 采用神经滑模控制,内动态子系统采用状态反馈控制器镇定．随后,对控制系统内动态稳定性进行了分析,并在 两自由度柔性连杆机械手控制的仿真试验中得到了满意的结果．试验结果表明,在存在模型不确定性时,该控制 策略提高了控制系统的鲁棒性和控制精度．     

A composite adaptive control with flexible quantity feedback for flexible-link manipulators

This article presents a mixture of joint subsystem-based adaptive control and simple flexible quantity feedback for flexible-link manipulators. The complex full flexible-arm system is composed of two severely coupling subsystems called the joint subsystem and flexible subsystem. Linear parametrization is first used to design an adaptive law for identifying the unknown parameters of a flexible manipulator based only on the joint subsystem. Joint-angle trajectory tracking can thus be achieved using the derived stable nonlinear adaptive control with the estimates of unknown parameters. To stabilize the flexible subsystem, we can simply add the feedback of transversal acceleration or deflection at the end point and/or along the flexible beam. The suggested approach is much simpler than those based on the full dynamics model of a flexible arm in required computations. Computer simulations on a single-link and a two-link flexible arm are tested to illustrate the validity of the strategy for both trajectory tracking and active damping. © 1996 John Wiley & Sons, Inc.     

共轴式无人直升机建模与鲁棒跟踪控制

针对共轴式无人直升机非线性、强耦合的动力学特性,本文提出了一种基于动态反馈线性化方法的鲁棒跟踪控制策略.首先根据叶素理论、Pitt-Peters动态入流模型、上下旋翼气动干扰分析建立了共轴式无人直升机的数学模型.然后对于高度-姿态子系统,通过扩展状态变量对其进行了动态反馈线性化,分析了零动态特性.根据内环期望跟踪特性对解耦后的子系统进行极点配置.通过设计鲁棒补偿器实现了对高度与姿态指令的鲁棒跟踪.在此基础上,针对水平面内的位置子系统设计了外环比例微分(proportional-derivative,PD)控制器以实现位置跟踪.最后,通过内环跟踪仿真验证了反馈线性化方法良好的解耦特性,通过干扰条件下的轨迹跟踪仿真验证了所设计控制器具有较好的控制性能与鲁棒性.     

Adaptive Iterative Learning Control of Non-uniform Trajectory Tracking for Strict Feedback Nonlinear Time-varying Systems

In this paper, an iterative learning control strategy is presented for a class of nonlinear time-varying systems, the timevarying parameters are expanded into Fourier series with bounded remainder term. The backstepping design technique is used to deal with system dynamics with non-global Lipschitz nonlinearities and the approach proposed in this paper solves the non-uniform trajectory tracking problem. Based on the Lyapunov-like synthesis, the proposed method shows that all signals in the closed-loop system remain bounded over a pre-specified time interval [0, T ]. And perfect non-uniform trajectory tracking of the system output is completed. A typical series is introduced in order to deal with the unknown bound of remainder term. Finally, a simulation example shows the feasibility and effectiveness of the approach.     

四旋翼飞行器自适应动态面轨迹跟踪控制

针对具有未知外界扰动和系统不确定性集总未知非线性的四旋翼飞行器,提出了一种采用自适应不确定性补偿器的自适应动态面轨迹跟踪方法.通过将四旋翼飞行器系统分解为位置、欧拉角和角速率3个动态子系统,使各子系统虚拟控制器设计能充分考虑欠驱动约束;结合动态面控制技术,通过采用一阶低通滤波器,避免对虚拟控制信号求导;进而设计自适应不确定性补偿器,处理未知外界扰动和系统不确定性,最终确保闭环控制系统的稳定性、跟踪误差一致最终有界和系统所有状态信号有界.仿真研究和实验结果验证了本文提出控制方法的有效性和优越性.     

Event-triggered adaptive consensus control of nonlinear multi-agent systems with unknown control directions and actuator saturation

This article addresses the event-triggered adaptive consensus control of nonlinear multi-agent systems with unknown control direction and actuator saturation. A new robust adaptive control algorithm based on an event-triggered mechanism is designed. The smooth Lipschitz function approximates the saturated nonlinear function, while the Nussbaum function handles unknown control directions and residual terms. The event-triggered mechanism is designed to determine the time of communication, significantly reducing the communication burden. An additional estimator is utilized to deal with unknown parameters involved in neighbor dynamics and prevent information exchange to consistency errors between connected subsystems. The results show that all the signals of the closed-loop system are uniformly bounded, and the consensus tracking error converges to a bounded set. Meanwhile, Zeno's behavior is eliminated. Simulation results confirm the superiority of the proposed method.     

多无人机目标追踪自适应控制

针对多无人机自动驾驶仪速度与航向角通道系数未知的目标轨迹追踪问题,提出一种自适应追踪控制方法.通过对自动驾驶仪通道系数进行在线估计,解决了系数未知所造成的设计困难.为克服外界干扰及系统内部误差因素对无人机运动控制系统的影响,设计了补偿项来消除干扰项的影响.采用Lyapunov定理证明了轨迹追踪误差最终可收敛于任意小的区域内.仿真结果验证了所设计方法的有效性.     

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.     

A Neural Net Predictive Control for Telerobots with Time Delay

This paper extends the Smith Predictor feedback control structure to unknown robotic systems in a rigorous fashion. A new recurrent neural net predictive control (RNNPC) strategy is proposed to deal with input and feedback time delays in telerobotic systems. The proposed control structure consists of a local linearized subsystem and a remote predictive controller. In the local linearized subsystem, a recurrent neural network (RNN) with on-line weight tuning algorithm is employed to approximate the dynamics of the time-delay-free nonlinear plant. The remote controller is a modified Smith predictor for the local linearized subsystem which provides prediction and maintains the desirable tracking performance. Stability analysis is given in the sense of Lyapunov. The result is an adaptive compensation scheme for unknown telerobotic systems with time delays, uncertainties, and external disturbances. A simulation of a two-link robotic manipulator is provided to illustrate the effectiveness of the proposed control strategy.     

大射电望远镜馈源指向系统轨迹跟踪自抗扰控制

采用独立控制策略实现新一代大射电望远镜馈源指向跟踪系统的高精度轨迹跟踪 .将两组成子系统之间的动力学耦合及其他扰动视为对精调Stewart平台子系统的未知扰动 ,设计了强鲁棒自抗扰控制器实现扰动补偿 .大射电望远镜馈源指向系统 5 0m缩比模型实验 ,验证了独立控制策略和自抗扰控制器的工程有效性和可行性 .为将来建造新一代大射电望远镜工程奠定了坚实的基础