一类线性时变系统的输出反馈控制

基于线性时不变系统能控能观标准型变换及非线性系统高增益观测器方法,本文研究了一类线性时变系统 的输出反馈控制问题. 通过引入时变的状态变量坐标变换,分别设计了线性时变系统的状态反馈控制器、状态观测器以及基于 状态观测器的输出反馈控制器. 进一步地,本文分别证明了观测器动态误差是渐近收敛于零的,而状态反馈控制器以及输出反馈控制器可以 保证闭环系统的渐近稳定性.     

基于扩展卡尔曼滤波的移动机器人变结构线性化复合跟踪控制

研究了移动机器人轨迹跟踪控制问题,通过坐标变换将轨迹跟踪问题转化为误差系统的镇定问题.基于反馈线忡化和变结构控制思想提出一种复合有限时间变结构线性化跟踪控制算法,其首先使误差系统驶向角初始误差伙速收敛到滑模边界层,然后采用连续状态反馈控制律来实现驶向角议差的无抖振快速镇定,同时将原误差系统转化为低阶系统;其次针对低阶系统设计了位置误差的状态反馈控制律,实现了位置误差的有限时间镇定.针对有系统噪声和量测噪声的误差系统,利用扩展卡尔曼滤波(EKF)进行误差状态估计,并以估计值构成反馈控制律.通过数值仿真验证了控制策略的有效性.     

基于输出反馈的非完整链式系统跟踪控制研究

针对非完整链式系统设计了基于输出反馈的全局跟踪控制律. 首先, 利用时变坐标变换和非自治系统的级联控制方法构造了状态观测器;然后对于时变坐标变换以后的误差系统继续利用非自治系统的级联控制方法设计了输出跟踪控制律. 区别于已有文献对于非完整链式系统跟踪控制问题的研究, 设计得到的输出跟踪控制律放松了参考轨迹所必需满足的不趋于零条件或持续激励条件. 结论表明在非完整链式系统跟踪控制问题 的研究中, 参考轨迹所必须满足的不趋于零的条件或者持续激励条件是不必要的. 最后的仿真结果验证了所给控制方法的有效性.     

具有参数不确定性的非线性系统的鲁棒输出跟踪

研究具有非线性参数化的非线性系统的输出跟踪问题.采用时变状态反馈控制律, 指数镇定输出跟踪误差,并保证非线性系统的所有状态是有界的.为了实现时变状态反馈控 制律,设计高增益鲁棒观测器观测构造该控制律所需要的状态,使得整个闭环系统的输出能 渐近跟踪期望输出,且该闭环系统中所有信号都是有界的.     

直流直线电机保证精度的自适应全维状态观测器极点配置

直流直线电机在加速动态过程以及稳态时,有较大的速度跟踪误差和稳态误差.提出一种保证动态跟踪精度和稳态精度的自适应全维状态观测器极点配置方法,以提高直流直线电机在运动过程中的加速动态跟踪精度及稳态精度.其主要思想是在直流直线电机系统中安装直线测速装置及位置传感器,用来获取电机的速度状态和位移状态,结合电机输出构造全维状态观测器,配置控制系统期望的零极点,同时,在整个系统之前加入增益矩阵,对其稳态误差进行补偿,最后通过自适应调节器根据电机运行状态不断调节全维状态观测器、反馈控制律及增益矩阵,用以减小系统动态跟踪误差和稳态误差.将设计出的算法用于二段式风机叶片拼装系统激光引导定位装置中,Matlab仿真及实际应用结果表明:该控制算法能够更好地跟踪电机的速度,提高了系统的动态跟踪精度和稳态精度,闭环系统鲁棒性更强.     

基于神经网络的不确定机器人自适应滑模控制

提出一种机器人轨迹跟踪的自适应神经滑模控制。该控制方案将神经网络的非线性映射能力与变结构控制理论相结合,利用RBF网络自适应学习系统不确定性的未知上界,神经网络的输出用于自适应修正控制律的切换增益。这种新型控制器能保证机械手位置和速度跟踪误差渐近收敛于零。仿真结果表明了该方案的有效性。     

任务空间内空间机械臂的自适应控制

对于本体姿态受控而位置不受控的空间机械臂系统,本文在任务空间内给出了一种自适应控制算。证明了当系统存在参数不确定性时,该算汉不但可以保证末端招待器在任务空间内的位置轨迹跟踪误差渐近收敛,而且还可保证在关节空间的角偏差及角偏差速率渐近收敛。仿真结果验证了算法的有效性。     

一类纯反馈非线性系统的反推控制

研究了一类纯反馈非线性系统的输出跟踪问题.通过引入一个新的坐标变换,提出了一种基于反推设计的状态反馈控制算法.所得控制算法不仅保证了系统跟踪误差全局渐近稳定,同时使得闭环系统所有信号有界.最后,一个仿真实例验证了本文控制算法的有效性.     

仿人机器人相似性运动轨迹跟踪控制研究

提出一种基于带观测器的条件状态反馈控制的仿人机器人相似性运动轨迹跟踪控制方法.首先,分析了7连杆双足机器人动力学模型,阐述了其运动能量方程与动力学特征方程; 其次,基于带观测器的状态反馈控制器原理,构建起三维倒立摆平衡控制模型; 最后,由线性二次型调节器确定状态反馈增益矩阵,使机器人轨迹跟踪误差最小化,以复现出较高相似度的双足步行运动效果.实验验证了该方法的有效性.     

基于观测器跟踪非一致轨迹的迭代学习控制器设计

针对状态难以直接测量的一类不确定非线性系统,基于状态观测器进行相应的迭代学习控制设计,可实现在给定区间上对变轨迹的全局精确跟踪．当任意两次迭代的目标轨迹完全不同,并且系统状态信息不完全已知时,通过引入能量函数的方法,可以证明随迭代次数增加,跟踪误差渐近收敛至零．仿真结果验证了结果的有效性．     

On the adaptive control of robot manipulators with velocity observers

To achieve accurate tracking control of robot manipulators many schemes have been proposed. A common approach is based on adaptive control techniques, which guarantee trajectory tracking under the assumption that the robot model structure is perfectly known and linear in the unknown parameters, while joint velocities are available. Despite tracking errors tend to zero, parameter errors do not unless some persistent excitation condition is fulfilled. There are few works dealing with velocity observation in conjunction with adaptive laws. In this note, an adaptive control/observer scheme is proposed for tracking position of robot manipulators. It is shown that tracking and observation errors are ultimately bounded, with the characteristic that when a persistent excitation condition is matched then they, as well as the parameter errors, tend to zero. Simulation results are in good agreement with the developed theory.     

Neural network-based sliding mode adaptive control for robot manipulators

This paper addresses the robust trajectory tracking problem for a robot manipulator in the presence of uncertainties and disturbances. First, a neural network-based sliding mode adaptive control (NNSMAC), which is a combination of sliding mode technique, neural network (NN) approximation and adaptive technique, is designed to ensure trajectory tracking by the robot manipulator. It is shown using the Lyapunov theory that the tracking error asymptotically converge to zero. However, the assumption on the availability of the robot manipulator dynamics is not always practical. So, an NN-based adaptive observer is designed to estimate the velocities of the links. Next, based on the observer, a neural network-based sliding mode adaptive output feedback control (NNSMAOFC) is designed. Then it is shown by the Lyapunov theory that the trajectory tracking errors, the observer estimation errors asymptotically converge to zero. The effectiveness of the designed NNSMAC, the NN-based adaptive observer and the NNSMAOFC is illustrated by simulations.     

Tracking control for VTOL aircraft with disabled IMUs

This article focuses on the design of an output feedback controller able to achieve the asymptotic tracking of a reference trajectory for vertical take off and landing aircraft with disabled inertial measurement units (IMUs). Roll angle and roll rate cannot be measured directly when IMUs are disabled. A dynamic linear observer is designed to estimate the tracking errors of the roll angle and equivalent roll angular velocity with respect to their desired states. Moreover, based on the centre manifold theory and on the equivalent control, the closed-loop system is asymptotically convergent. The theoretical results are confirmed by computer simulations.     

Robust tracking control for wheeled mobile robot based on extended state observer

This paper presents a new control scheme on trajectory tracking of wheeled mobile robot with nonholonomic constraints. Extended state observer is introduced to estimate unknown disturbances and velocity information. A robust tracking controller is designed to implement the accurate trajectory tracking and disturbance compensation. By theoretical, position and velocity tracking errors of wheeled mobile robot are proven uniformly ultimately asymptotically stable. Simulation results are given to illustrate the effectiveness of the developed technique.     

基于观测器的机械手神经网络自适应控制

提出了一种基于观测器的机械手神经网络自适应轨迹跟随控制器设计方法,这里机 械手的动力学非线性假设是未知的,并且假设机械手仅有关节角位置测量.文中采用一个线 性观测器重构机械手的关节角速度,用神经网络逼近修正的机械手动力学非线性,改进系统 的跟随性能.基于观测器的神经网络自适应控制器能够保证机械手角跟随误差和观测误差的 一致终结有界性以及神经网络权值的有界性,最后给出了机械手神经网络自适应控制器-观 测器设计的主要理论结果,并通过数字仿真验证了所提方法的性能.     

Trajectory tracking optimization of mobile robot using artificial immune system

In this paper, an optimization method that provides quick response using artificial immune system, is proposed and applied to a mobile robot for trajectory tracking. The study focuses on the immune theory to derive a quick optimization method that puts emphasis on immunity feedback using memory cells by the expansion and suppression of the test group rather than to derive a specific mathematical model of the artificial immune system. Various trajectories were selected in mobile environment to evaluate the performance of the proposed artificial immune system. The global inputs to the mobile robot are reference position and reference velocity, which are time variables. The global output of mobile robot is a current position. The tracking controller makes position error to be converged to zero. In order to reduce position error, compensation velocities on the track of trajectory are necessary. Input variables of fuzzy are position errors in every sampling time. The output values of fuzzy are compensation velocities. Immune algorithm is implemented to adjust the scaling factor of fuzzy automatically. The results of the computer simulation proved the system to be efficient and effective for tracing the trajectory to the final destination by the mobile robot.

     

Synchronization of multiple autonomous underwater vehicles without velocity measurements

In this paper,we investigate the synchronization control of multiple autonomous underwater vehicles (AUVs),considering both state feedback and output feedback cases.Treating multiple AUVs as a graph,we define the tracking error of each AUV with both its own tracking error and the relative position errors with respect to its neighbors taken into account.Lyapunov analysis is used to derive the control law for each AUV.For the output feedback case,a passive filter is used to compensate for the unknown relative velocity errors among AUVs,and an observer is employed to estimate the velocity of the AUV itself.Rigid mathematical proof is provided for the proposed algorithms for both state feedback and output feedback cases.Simulations are provided to demonstrate the effectiveness of the proposed approach.It is shown that,the synchronization error is smaller in the case of considering the relative errors between AUVs than in the case of considering the tracking error of the single AUV only.     

Underactuated ship tracking control: Theory and experiments

We consider complete state tracking feedback control of a ship having two controls, namely surge force and yaw moment. The ship model has similarities with chained form systems but cannot directly be transformed in chained form. In particular, the model has a drift vector field as opposed to the drift-free chained form systems. It is shown here that methods developed for tracking control of chained form systems still can be used for developing a tracking control law for the ship. Through a coordinate transformation the model is put in a triangular-like form which makes it possible to use integrator backstepping to develop a tracking control law. The control law steers both the position variables and the course angle of the ship, providing exponential stability of the reference trajectory. Experimental results are presented where the control law is implemented for tracking control of a model of an offshore supply vessel, scale 1:70. In the experiments the ship converges exponentially to a neighbourhood of the reference trajectory, and stays close with errors depending on factors as unmodelled dynamics, parameter uncertainty, measurement noise, thruster saturation, waves, currents and position measurement failures.     

Robust finite-time tracking control of nonholonomic mobile robots without velocity measurements

The problem of robust finite-time trajectory tracking of nonholonomic mobile robots with unmeasurable velocities is studied. The contributions of the paper are that: first, in the case that the angular velocity of the mobile robot is unmeasurable, a composite controller including the observer-based partial state feedback control and the disturbance feed-forward compensation is designed, which guarantees that the tracking errors converge to zero in finite time. Second, if the linear velocity as well as the angular velocity of mobile robot is unmeasurable, with a stronger constraint, the finite-time trajectory tracking control of nonholonomic mobile robot is also addressed. Finally, the effectiveness of the proposed control laws is demonstrated by simulation.