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.     

基于自适应动态规划的多设定值跟踪控制方法

针对一类典型的带有控制约束的非线性离散时间系统,提出了一种基于自适应动态规划(adaptive dynamic programmmg,ADP)算法的多设定值跟踪控制方法,并对其收敛性和稳定性做了严格分析.在ADP迭代跟踪控制的基础上,根据多模型控制的思想,设置阶梯状的参考轨迹,使得系统状态逐渐地跟踪到最终设定值,保证了系统的稳定性,极大地减小超调量,加快了响应时间,改善控制品质;同时由于控制器约束的存在,引入非二次型的性能指标函数,使得控制量始终在有界的范围内变化.最后对仿真结果进行了分析,结果表明了此方法的可行性和有效性.     

Robust adaptive control of uncertain force/motion constrained nonholonomic mobile manipulators

In this paper, force/motion tracking control is investigated for nonholonomic mobile manipulators with unknown parameters and disturbances under uncertain holonomic constraints. The nonholonomic mobile manipulator is transformed into a reduced chained form, and then, robust adaptive force/motion control with hybrid variable signals is proposed to compensate for parametric uncertainties and suppress bounded disturbances. The control scheme guarantees that the outputs of the dynamic system track some bounded auxiliary signals, which subsequently drive the kinematic system to the desired trajectory/force. Simulation studies on the control of a wheeled mobile manipulator are used to show the effectiveness of the proposed scheme.     

A unified symplectic pseudospectral method for motion planning and tracking control of 3D underactuated overhead cranes

In this paper, a unified symplectic pseudospectral method for motion planning and tracking control of 3D underactuated overhead cranes is proposed. A feasible reference trajectory taking constraints into consideration is first generated offline by the symplectic pseudospectral optimal control method. Then, a trajectory tracking model predictive controller also based on the symplectic pseudospectral method is developed to track the reference trajectory. At each sampling instant, the trajectory tracking controller works by solving an open‐loop optimal control problem where linearized system dynamics is used instead to improve the computational efficiency. Since the symplectic pseudospectral optimal control method is the core algorithm for both offline trajectory planning and online trajectory tracking, constraints on state variables and control inputs can be easily imposed and hence theoretically guaranteed in solutions. By selecting proper weighted matrices on tracking error and control, the developed controller could achieve control objectives in both accurate trolley positioning and fast suppressing of residual swing angles. Simulations for 3D overhead crane systems in the presence of perturbations in initial conditions, an abrupt variation of system parameter, and various external disturbances demonstrate that the developed controller is robust and of excellent control performance.     

Neurodynamic programming and tracking control scheme of constrained-input systems via a novel event-triggered PI algorithm

In this paper, a new event-triggered approach for neurodynamic programming and optimal tracking control problem of constrained-input systems is proposed, where the desired trajectory can be generated as a large class of useful command trajectories. Firstly, the complex tracking problem is converted to a stabilizing control optimization problem by reconstructing a novel augmented tracking system with discounted performance index. Secondly, instead of the conventional time-driven control, an event-triggered policy iteration (PI) algorithm is designed to drive the system dynamic to track the reference trajectory, which requires less computation and fewer transmissions during the solving. Thirdly, the novel tracking control can be bounded as desired, which overcomes the unconstrained steady-state control from the general adaptive dynamic programming based tracking solution. Moreover, only critic neural network is used in the implementation of iteration learning, which simplifies the actor-critic architecture and reduces computational load. And by the means of Lyapunov method, the ultimately boundedness of the tracking system under the event-triggered PI algorithm is proved. Finally, the developed approach is applied to track a sinusoidal waveform and a periodic rectangular step signal in the simulations, where the effectiveness is also demonstrated.     

无人车辆轨迹规划与跟踪控制的统一建模方法

无人车辆的轨迹规划与跟踪控制是实现自动驾驶的关键.轨迹规划与跟踪控制一般分为两个部分,即先根据车辆周边环境信息以及自车运动状态信息规划出参考轨迹,再依此轨迹来调节车辆纵横向输出以实现跟随控制.本文通过对无人车辆的轨迹规划与跟踪进行统一建模,基于行车环境势场建模与车辆动力学建模,利用模型预测控制中的优化算法来选择人工势场定义下的局部轨迹,生成最优的参考轨迹,并在实现轨迹规划的同时进行跟踪控制.通过CarSim与MATLAB/Simulink的联合仿真实验表明,该方法可在多种场景下实现无人车辆的动态避障.     

六自由度机械臂约束预测控制系统的设计

本文提出了一种基于约束预测控制的机械臂实时运动控制方法.该控制方法分为两层,分别设计了约束预测控制器和跟踪控制器.其中,约束预测控制器在考虑系统物理约束的条件下,在线为跟踪控制器生成参考轨迹;跟踪控制器采用最优反馈控制律,使机械臂沿参考轨迹运动.为了简化控制器的设计和在线求解,本文采用输入输出线性化的方式简化机械臂动力学模型.同时,为了克服扰动,在约束预测控制器中引入前馈策略,提出了带前馈一反馈控制结构的预测控制设计.因此,本文设计的控制器可以使机械臂在满足物理约束的条件下快速稳定地跟踪到目标位置.通过在PUMA560机理模型上进行仿真实验,验证了预测控制算法的可行性和有效性.     

基于模糊不确定观测器的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的四旋翼飞行器,提出了一种基于模糊不确定观测器（Fuzzy uncertainty observer,FUO）的自适应动态面轨迹跟踪控制方法.通过将四旋翼飞行器系统分解为位置、姿态角和角速率三个动态子系统,使得各子系统虚拟控制器能够充分考虑欠驱动约束;采用一阶低通滤波器重构虚拟控制信号及其一阶导数,实现四旋翼跟踪控制设计的迭代解耦;设计了一种模糊不确定观测器,用以估计和补偿未知外界扰动与系统不确定性,从而确保闭环系统的稳定性和跟踪误差与其他系统信号的一致有界性.仿真研究验证了所提出的控制方法的有效性和优越性.     

Time-optimal reorientation for rigid satellite with reaction wheels

This article introduces a time-optimal reorientation manoeuvre controller with saturation constraints on both reaction wheels’ torques and angular momentum. The proposed control scheme consists of two parts. The first part is an open-loop time-minimum reorientation trajectory generated by the Legendre pseudospectral method. Actuator dynamics, saturations on control torques and angular momentums of reaction wheels are taken into account in generating the open-loop optimal trajectory. The second part is a closed-loop tracking control law to track the optimised reference trajectory based on attitude error dynamics with reaction wheel dynamics. Numerical simulations show that reaction wheel dynamics play an important role in attitude manoeuvres. The proposed controller performs better for rest-to-rest reorientation manoeuvre than other existing methods.     

带有输出约束的水面船舶实际有限时间控制

考虑带有输出约束的水面船舶系统,提出一种自适应神经网络航迹跟踪实际有限时间控制算法.基于反步法设计有限时间控制律,构造障碍李雅普诺夫函数处理输出约束问题,采用神经网络逼近船舶模型中的不确定信息.在控制算法递推过程中,通过设计一个关于跟踪误差的可微幂函数来避免控制器中的奇异问题.借助李雅普诺夫稳定性分析理论,证明了航迹跟踪误差在有限时间内收敛到有界的邻域内.最后,以一艘1:70的比例模型船作为仿真对象,来验证所提出的航迹跟踪实际有限时间控制算法的有效性.     

Robust formation control without velocity measurement of the leader robot

In this paper a control problem of leader–follower motion coordination of multiple nonholonomic mobile robots is addressed and subsequently in the proposed scheme, a reference trajectory generated based on the information from the leader is tracked by the follower robots. To alleviate demanded information on the leader, specifically to eliminate the measurement requirement or estimation of the leader's velocity and dynamics, a virtual vehicle is constructed whereby its trajectory converges to the reference trajectory of the follower. Trajectory tracking controller is then designed to allow the follower robot to track the virtual vehicle using neural network approximation, in combination with the backstepping and Lyapunov direct design technique and finally the performance and effectiveness of the controller is verified throughout the experiments.     

基于模型预测的自动导引车区间轨迹跟踪控制

针对自动导引车(AGV)轨迹跟踪问题,在确定其可行驶区域的基础上,考虑自动导引车的大小和形状,本文设计了一种基于模型预测控制理论的轨迹跟踪控制方法.首先,将车辆运动学模型进行线性化处理,得到车辆动力学线性模型;其次,运用模型预测控制方法,利用预测路径与期望路径之间的误差,通过优化得到使性能指标最优的控制序列;最后,在MATLAB软件上对轨迹跟踪控制器进行仿真.实验结果表明,AGV可以稳定地跟踪参考轨迹,且距离偏差和角度偏差都在给定的可行范围内,证明了提出的基于模型预测控制的轨迹跟踪算法具有良好的跟踪性能.     

Supervised coverage control of multi-agent systems

In this paper, we consider a dynamic coverage problem for multi-agent systems, where the main objective of a group of mobile agents is to explore a given compact region. We propose a novel control scheme, where we introduce a supervisor that assists a group of agents with the centralized coverage control law and the global trajectory tracking control law. The coverage control law ensures the coverage task is done until the agents end up in local minima, and when they do, the global trajectory tracking control law ensures that the agents are deployed to uncovered regions. Our control scheme is designed to be decoupled such that only one control law is active at a given time. In addition to the coverage objective, we design control laws for coverage agents to avoid collisions and maintain proximity to a supervisor. Moreover, we utilize feedback linearization to use the proposed control scheme for coverage control of kinematic unicycle agents. We validate our approach via numerical simulations.     

水下机器人的神经网络自适应控制

研究了水下机器人神经网络直接自适应控制方法,采用Lyapunov稳定性理论,证明了存在有界外界干扰和有界神经网络逼近误差条件下,水下机器人控制系统的跟踪误差一致稳定有界.为了进一步验证该水控制方法的正确性和稳定性,利用水下机器人实验平台进行了动力定位实验、单自由度跟踪实验和水平面跟踪实验等验证实验.     

Flat trajectory design and tracking with saturation guarantees: a nano-drone application

Abstract

This paper deals with the problem of trajectory planning and tracking of a quadcopter system based on the property of differential flatness. First, B-spline characterisations of the flat output allow for optimal trajectory generation subject to waypoint constraints, thrust and angle constraints while minimising the trajectory length. Second, the proposed tracking control strategy combines feedback linearisation and nested saturation control via flatness. The control strategy provides bounded inputs (thrust, roll and pitch angles) while ensuring the overall stability of the tracking error dynamics. The control parameters are chosen based on the information of the a priori given reference trajectory. Moreover, conditions for the existence of these parameters are presented. The effectiveness of the trajectory planning and the tracking control design is analysed and validated through simulation and experimental results over a real nano-quadcopter platform, the Crazyflie 2.0.     

Dynamic average consensus with topology balancing under a directed graph

In this paper, the distributed average tracking problem is studied on the premise of a strongly connected directed graph. To this end, we propose a weight balance strategy that could potentially make the adjacency matrix doubly stochastic for any strongly connected directed graph. The proposed scheme is fully distributive with finite time convergence and we again prove that network connectivity (described by the first left eigenvector) is instrumental in networked control systems. Then, a discrete‐time average tracking observer is introduced to ensure that all networked systems can track the average of the reference signals with bounded error. Simulation results verify the effectiveness of the proposed methods.     

Global trajectory tracking through output feedback for robot manipulators with bounded inputs

In this work, a globally stabilizing output feedback scheme for the trajectory tracking of robot manipulators with bounded inputs is proposed. It achieves the motion control objective avoiding input saturation and excluding velocity measurements. Moreover, it is not defined using a specific sigmoidal function, but any one on a set of saturation functions. Consequently, the proposed scheme actually constitutes a family of globally stabilizing output feedback bounded controllers. Furthermore, the control gains are not tied to satisfy any saturation‐avoidance inequality and may consequently take any positive value, which may be considered beneficial for performance adjustment/improvement purposes. Further, a class of desired trajectories that may be globally tracked avoiding input saturation and excluding velocity measurements is completely characterized. Global asymptotic stabilization of the closed‐loop system solutions towards the pre‐specified desired trajectory is proved through a strict Lyapunov function. The efficiency of the proposed scheme is corroborated through experimental results. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Decentralized filtering adaptive constrained tracking control for interconnected nonlinear systems

This paper presents a novel decentralized filtering adaptive constrained tracking control framework for uncertain interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, a piecewise constant adaptive law will generate total uncertainty estimates by solving the error dynamics between the host system and decentralized state predictor with the neglection of unknowns, whereas a decentralized filtering control law is designed to compensate both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. In the control scheme, the nonlinear uncertainties are compensated for within the bandwidth of low‐pass filters, while the trade‐off between tracking and constraints violation avoidance is formulated as a numerical constrained optimization problem which is solved periodically. Priority is given to constraints violation avoidance at the cost of deteriorated tracking performance. The uniform performance bounds are derived for the system states and control inputs as compared to the corresponding signals of a bounded closed‐loop reference system, which assumes partial cancelation of uncertainties within the bandwidth of the control signal. Compared with model predictive control (MPC) and unconstrained controller, the proposed control architecture is capable of solving the tracking control problems for interconnected nonlinear systems subject to constraints and uncertainties.     

Motion Control of a Nonholonomic Mobile Manipulator in Task Space

In this paper, the motion control of a mobile manipulator subjected to nonholonomic constraints is investigated. The control objective is to design a computed‐torque controller based on the coupled dynamics of the mobile manipulator. The proposed controller achieves the capability of simultaneous tracking of a reference velocity for the mobile base and a reference trajectory for the end‐effector. The aforementioned reference velocity and trajectory are defined in the task space, such task setting imitates the actual working conditions of a mobile manipulator and thus makes the control problem practical. To solve this tracking problem, a steering velocity is firstly designed based on the first‐order kinematic model of the nonholonomic mobile base via dynamic feedback linearization. The main merit of the proposed steering velocity design is that it directly utilizes the reference velocity set in the task space without requiring the knowledge of a reference orientation. A torque controller is subsequently developed based on a proposed Lyapunov function which explicitly considers the coupled dynamics of the mobile manipulator to ensure the mobile base and end‐effector track the reference velocity and trajectory respectively. This proposed computed‐torque controller is able to realize asymptotic stability of both the base velocity tracking error and the end‐effector motion tracking error. Simulations are conducted to demonstrate the effectiveness of the proposed controller.     

Nonsingular predefined-time dynamic surface control of a flexible-joint space robot with actuator constraints

To achieve predefined-time trajectory tracking control of a flexible-joint space robot(FJSR) with actuator constraints, a nonsingular predefined-time dynamic surface control scheme is developed. The input saturation caused by actuator constraints is addressed via the designed predefined-time anti-saturation compensator. On this basis, two different control laws are designed for such high-order nonlinear systems by utilizing the backstepping technique, and a novel nonlinear filter is constructed to filter the virtual control signals, thus avoiding the “differential expansion” phenomenon. Moreover, a singularity-free auxiliary function is designed to solve the singularity issue generated by the derivative of fractional power terms in the predefined-time control algorithm framework. The closed-loop system is proven to be semi-globally predefined-timely uniformly ultimately bounded (SGPTUUB) via constructing the suitable Lyapunov function. The difference and effectiveness of the two designed control laws are illustrated by the conducted simulations. Both of them allow the FJSR system to track the desired trajectory in a reasonably predefined time.