不匹配不确定性系统的近似变结构输出跟踪控制

针对一类具有不匹配不确定性的非线性系统,提出一种结合变结构控制方法及自适应控制方法输出跟踪控制器。首先提出一种保证不确定性系统跟踪误差指数稳定的近似变结构控制器;进而得到一种具有不确定性范数上界估计能力的自适应近似变结构控制器,并证明了所提出的自适应近似变结构控制器使跟踪误差在时间趋于无穷时收敛于零。     

智能车辆路径跟踪控制方法

为了提高智能车辆路径跟踪控制器的可靠性和控制精度,提出一种基于误差动力学模型的路径跟踪控制方法.基于车辆运动学模型和动力学模型建立系统误差动力学模型,并在此基础上推导出车辆路径跟踪控制的稳态控制律,利用李雅普诺夫稳定性理论验证稳态控制律的正确性.为了减小外部干扰对控制性能的影响,提高控制器的可靠性,进一步设计基于车辆侧向位移误差的瞬态控制律,并利用李雅普诺夫稳定性理论验证闭环系统的稳定性.稳态控制律和瞬态控制律构成了非线性的路径跟踪控制器.通过与车辆路径跟踪常用的线性控制器和非线性控制器对比验证所提出控制方法的有效性,线性控制器选用LQR控制器,非线性控制器选用Stanley控制器.仿真结果表明,与LQR控制器相比,所提出控制方法的路径跟踪控制精度、抗干扰性和可靠性更好.与Stanley控制器相比,所提出控制方法具有更好的路径跟踪控制精度和控制收敛速度,且在大曲率路径跟踪过程中具有更好的可靠性.     

不确定移动机器人编队间接自适应模糊动力学控制

研究不确定非完整移动机器人Leader/Follower编队动力学控制问题,对Follower提出了自适应队形跟踪控制方法.首先,基于队形方程设计了运动学队形跟踪控制器,使用Backstepping技术扩展出队形跟踪误差动力学方程;然后,利用自适应模糊系统逼近其不确定项,构造了间接自适应模糊动力学队形跟踪控制器;最后,证明了队形跟踪误差可收敛到原点的小邻域内.仿真结果验证了所提出控制策略的有效性.     

基于不确定性机器人的跟踪控制策略研究

针对不确定刚体连杆机器人在动力学建模时参数不精确以及未被考虑的干扰因素可能引起的控制系统品质的恶化问题,提出一种轨迹跟踪控制方案。控制器由基于标称模型设计的计算力矩控制器和基于不确定性因素设计的鲁棒跟踪补偿控制器组成,结构比较简单。计算力矩控制器使标称系统跟踪期望轨迹;鲁棒补偿控制器则用于消除参数误差带来的不确定性影响。理论分析和仿真证明了控制方法的有效性。     

基于弹性能量函数的非线性不确定系统控制方法

针对非线性不确定系统的控制问题,提出一种基于弹性能量函数的扰动观测方法和弹性跟踪控制方法.该方法以弹性能量函数为核心,将其分别应用于扰动观测器、虚拟跟踪指令以及弹性跟踪控制器的设计.该控制方法的突出优势是只根据误差来消除误差,不涉及误差的微分运算,控制器增益参数完全根据积分步长来整定.理论研究表明,所提出的弹性跟踪控制方法不仅可从理论上保证各级子控制器的稳定性,有效解决高阶SISO非线性不确定系统的控制问题,而且可有效避免反步控制方法出现的微分爆炸问题.此外,每个子控制器只有一个由积分步长即可整定的增益参数,因而控制器结构简单、计算量较小.仿真结果表明:所提出的控制方法不仅具有快的响应速度、高的控制精度以及强的抗扰动能力,而且不依赖于被控对象模型,在非线性不确定系统控制领域具有广泛的应用前景.     

基于改进Smith预估控制结构的二自由度PID控制

针对工业过程中的二阶不稳定时滞过程, 基于改进史密斯预估控制结构提出了一种简单的两自由度控制方案.设定值跟踪控制器和扰动抑制控制器采用同一设计程序, 并基于内模控制原理提出了控制器解析设计方案.设定值跟踪控制器和抗扰动控制器可分别通过单性能参数独立调节和优化, 每个控制器都具有PID形式, 给出了控制器调整参数的选择范围和扰动抑制闭环保证鲁棒稳定性的条件.仿真实例验证了提出方法对于近期其他方法的优越性.     

自由漂浮空间机器人末端轨迹优化自适应控制

惯性参数不确定情况下的自由漂浮空间机器人(FFSR)轨迹跟踪控制是当前FFSR自主控制研究的重点与难点之一.针对该问题,提出一种FFSR末端轨迹优化自适应跟踪控制方法.该方法首先基于离散状态依赖黎卡提方程(DSDRE),设计两级DSDRE优化跟踪控制器,然后在控制器输出基础上,通过求解有约束条件下的非线性优化问题实现FFSR惯性参数的辨识,进而根据辨识结果调整控制器相关参数,实现FFSR末端轨迹的优化自适应跟踪控制.最后,采用平面两连杆FFSR模型进行仿真,验证了所提出方法的有效性.     

具有不确定性的线性系统可靠跟踪控制

针对一类不确定线性定常系统，提出了考虑执行器故障的可靠跟踪控制器设计问题。在更一般、更实际的执行器故障模型的基础上，给出了系统输出渐近跟踪参考输入信号的可靠跟踪控制存在的充分条件。通过求解LMI完成状态反馈可靠控制器的设计。利用数例仿真验证了所设计方法的可行性，并且通过可靠跟踪系统与不考虑故障的标准跟踪控制系统的比较．进一步说明对系统进行可靠跟踪控制的必要性。     

基于模糊PID控制的太阳能电池板跟踪系统

由于太阳能电池板跟踪系统具有非线性的特点,使得利用简单模糊控制和传统PID控制精度不高,因此,文中提出利用模糊PID控制器实现对跟踪系统的控制,并设计了模糊PID控制器。通过SIMULINK对系统进行仿真,其结果表明：该控制方法调节精度较高、动态响应快、超调较小。     

微型扑翼飞行器的自适应位置跟踪控制器

微型扑翼飞行器是飞行器发展的重要方向,其位置跟踪控制成为该研究面对的首要问题.本文针对微型扑翼飞行器(flapping wing micro aerial vehicle,FWMAV)的位置跟踪控制问题展开研究,提出了一种可以避免控制系统陷入奇异且理论跟踪误差为零的自适应控制器.具体而言,首先提出了零梯度位置跟踪控制器.而后,理论分析表明其在解决FWMAV位置跟踪控制问题时存在局限性,即该控制器总是存在理论位置跟踪误差.为了弥补这一缺点,对零梯度控制器进行改进,提出了一种理论位置跟踪误差为零的自适应控制器,并利用非线性激励函数加快了位置跟踪误差的收敛速度.最后,仿真实验验证了该控制器的优越性.     

Robust adaptive motion/force tracking control design for uncertain constrained robot manipulators

In the presence of uncertain constraint and robot model, an adaptive controller with robust motion/force tracking performance for constrained robot manipulators is proposed. First, robust motion and force tracking is considered, where a performance criterion containing disturbance and estimated parameter attenuations is presented. Then the proposed controller utilizes an adaptive scheme and an auxiliary control law to deal with the uncertain environmental constraint, disturbances, and robotic modeling uncertainties. After solving a simple linear matrix inequality for gain conditions, the effect from disturbance and estimated parameter errors to motion/force errors is attenuated to an arbitrary prescribed level. Moreover, if the disturbance and estimated parameter errors are square-integrable, then an asymptotic motion tracking is achieved while the force error is as small as the inversion of control gain. Finally, numerical simulation results for a constrained planar robot illustrate the expected performance.     

Finite‐Time Sliding Mode Trajectory Tracking Control of Uncertain Mechanical Systems

The problem of finite‐time tracking control is studied for uncertain nonlinear mechanical systems. To achieve finite‐time convergence of tracking errors, a simple linear sliding surface based on polynomial reference trajectory is proposed to enable the trajectory tracking errors to converge to zero in a finite time, which is assigned arbitrarily in advance. The sliding mode control technique is employed in the development of the finite‐time controller to guarantee the excellent robustness of the closed‐loop system. The proposed sliding mode scheme eliminates the reaching phase problem, so that the closed‐loop system always holds the invariance property to parametric uncertainties and external disturbances. Lyapunov stability analysis is performed to show the global finite‐time convergence of the tracking errors. A numerical example of a rigid spacecraft attitude tracking problem demonstrates the effectiveness of the proposed controller.     

Fixed‐time adaptive sliding mode trajectory tracking control of uncertain mechanical systems

An adaptive fixed‐time trajectory tracking controller is proposed for uncertain mechanical systems in this study. The polynomial reference trajectory is planned for trajectory tracking error. Fractional power of linear sliding mode is applied to design the nonlinear controller, adaptive laws are used to adjust controller parameters. Trajectory planning and fractional power are combined to ensure the tracking‐error convergence in a fixed time. The boundary layer technique is used to suppress the model uncertainties and decrease the chattering phenomenon. The closed‐loop system stability is proved strictly in the Lyapunov framework to show that the trajectory tracking errors and adaptive parameters tend to zero in a fixed time set in advance. Numerical simulation results of robotic manipulators illustrate the effectiveness of the proposed controller.     

非线性积分滑模控制方法

针对一类不确定非线性系统的滑模控制,提出了一类具有"小误差放大,大误差饱和"功能的光滑非线性饱和函数来改进传统的积分滑模控制,以形成非线性积分滑模控制.在保持传统积分滑模控制跟踪精度的同时获得更好的暂态性能.应用Lyapunov稳定性理论和LaSalle不变性原理证明了对最终常值干扰可以完全抑制.考虑控制受限时,所设计...     

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。     

船舶航向非线性系统鲁棒跟踪控制

对船舶航向非线性系统, 提出了一种基于神经网络方法的鲁棒跟踪控制器. 系统由船舶运动非线性响应模型和舵机伺服系统串联构成, 其中运动响应模型考虑了建模误差和外界干扰力等非匹配不确定性. 对建模误差和期望舵角的一阶导数项应用在线二层神经网络予以辨识和补偿, 不确定性干扰项处理应用L2增益设计. 采用Lyapunov函数递推法, 得到包括神经网络权值算法在内的跟踪控制器. 跟踪误差和神经网络权值误差的一致终值有界性保证了系统的鲁棒稳定性, 合理的控制器参数选择保证了控制精度. 仿真结果验证了控制器的有效性.     

基于终端滑模机器人模糊自适应路径跟踪控制

对质心位置未知的移动机器人系统设计了基于快速终端滑模的模糊自适应路径跟踪控制方法。该方法采用模糊逻辑系统逼近控制器中的未知函数,基于李亚普诺夫稳定性分析方法对未知参数设计自适应律,并设计鲁棒控制器来补偿逼近误差。该方法不但可以保证闭环系统中的所有信号有界,而且可使跟踪误差在有限时间内收敛到原点的小邻域内。仿真结果验证了方法的有效性。     

Task-space fully distributed tracking control of networked uncertain robotic manipulators without velocity measurements

This paper investigates the task-space synchronised tracking problem of uncertain networked manipulators interconnected on directed graphs, where the dynamic leader is available to only a subset of followers and followers have only local interaction. A fully distributed tracking controller is proposed, which is composed of a distributed desired trajectory estimator, a joint-space velocity observer and an adaptive cooperative control algorithm. Specifically, the proposed controller allows each manipulator to track the dynamic leader solely using local task-space position measurements. Besides, in the presence of both dynamic and kinematic uncertainties, the adaptive cooperative control algorithm indeed improves the system's robustness. Furthermore, it is strictly proved that the proposed control scheme ensures that both task-space position and velocity tracking errors converge to zero as time tends to infinity. In the end, simulation results are provided to demonstrate the effectiveness of the proposed controller.     

Adaptive Jacobian force/position tracking for space free-flying robots with prescribed transient performance

This paper presents a tracking control with guaranteed prescribed performance (PP) for space free-flying robots with uncertain kinematics (Jacobian matrix) and dynamics, uncertain normal force parameter, and bounded disturbances in a compliant contact with a planar surface. Given the orientation of the surface and a nonlinear model of the elastic force, a controller is designed requiring no information on the robot parameters and the disturbances. This controller will guarantee that the tracking errors satisfy PP indexes such as the maximum steady-state errors and overshoots, and the minimum convergence rates. Thus, contact maintenance can be ensured as prescribed. An approximation of the Jacobian is utilized in the presence of uncertain robot kinematics, and PP position/attitude tracking of the free-flying base is achieved in addition to the PP force/position tracking of the manipulator’s fingertip. The proposed controller is based on an error transformation technique, and a directly tunable gain for the transformed error feedback is introduced in the control to trade off between the tracking performance and control effort. Numerical simulations and comparisons demonstrate the effectiveness and superiority of the proposed controller.     

Adaptive fuzzy control for multi-input multi-output nonlinear systems with unknown dead-zone inputs

This paper presents an adaptive fuzzy control scheme for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with the nonsymmetric control gain matrix and the unknown dead-zone inputs. In this scheme, fuzzy systems are used to approximate the unknown nonlinear functions and the estimated symmetric gain matrix is decomposed into a product of one diagonal matrix and two orthogonal matrices. Based on the decomposition results, a controller is developed, therefore, the possible controller singularity problem and the parameter initialization condition constraints problem are avoided. In addition, a dynamic robust controller is employed to compensate for the lumped errors. It is proved that all the signals in the proposed closed-loop system are bounded and that the tracking errors converge asymptotically to zero. A simulation example is used to demonstrate the effectiveness of the proposed scheme.