Adaptive output feedback formation tracking for a class of multiagent systems with quantized input signals

A novel adaptive output feedback control approach is presented for formation tracking of a multiagent system with uncertainties and quantized input signals. The agents are described by nonlinear dynamics models with unknown parameters and immeasurable states. A high-gain dynamic state observer is established to estimate the immeasurable states. With a proper design parameter choice, an adaptive output feedback control method is developed employing a hysteretic quantizer and the designed dynamic state observer. Stability analysis shows that the control strategy can guarantee that the agents can maintain the formation shape while tracking the reference trajectory. In addition, all the signals in the closed-loop system are bounded. The effectiveness of the control strategy is validated by simulation.     

永磁球形电机的少保守性滑模控制

永磁球形电机轨迹跟踪控制方法常常利用高增益的控制输出来保证系统的鲁棒性及跟踪控制的快速性.但这种保守控制会带来较大的控制作用,甚至导致执行器饱和.为了减少控制的保守性,本文设计了一种带有非线性干扰观测器的模糊滑模控制器来解决球形电机的轨迹跟踪问题.利用干扰观测器对不确定性、摩擦、外界干扰、负载扰动等进行估计,并在控制输入端进行补偿实现对干扰的抑制.并利用滑模控制器抵消干扰观测器的干扰观测误差及不可观测部分的干扰,为了减少滑模的抖振,本文利用模糊逻辑对该部分进行逼近,并利用模糊的输出增益代替滑模的切换增益.此外通过Lyapunov方程证明了本文控制器的稳定性.仿真结果表明在存在模型不确定性及各种干扰的情况下,本文的轨迹跟踪控制具有良好的动静态性能和少保守性.     

高阶不确定非线性系统的线性自抗扰控制

针对一类具有内部动态和外部扰动未知的SISO高阶非线性系统,提出一种通用的线性自抗扰控制方案.该方案基于单参数调节的高增益观测器思想,分别设计线性跟踪微分器、线性扩张状态观测器和线性状态误差反馈控制律.利用Lagrange中值定理和Cauchy-Schwarz不等式将系统总扰动的微分值转化为关于系统估计和跟踪误差的函数,可以解决因系统控制增益未知所导致的控制量微分值难以预先确定的问题.在此基础上,基于Lyapunov稳定性定理证明闭环系统误差信号有界,并进一步分析得到系统估计和跟踪误差与控制器参数的定量关系,即都可以随观测器增益的增大而达到无限小.仿真比较结果验证了所提出方案的有效性,与韩式自抗扰控制方案相比,该方案结构简单,调节参数少,易于工程实现.     

线性自抗扰控制器的稳定性研究

研究了线性扩张状态观测器(Extended state observer, ESO)的估计能力,并且分析了在线性自抗扰控制(Linear active disturbance rejection control, LADRC)下闭环系统的稳定性. 对于系统模型未知的情形, 给出了线性扩张观测器估计误差有界的证明, 并通过分析得出了如下结论: 在扩张状态观测器跟踪误差趋于零的前提下, 在线性自抗扰控制下的闭环系统可以实现对设定信号的精确跟踪以及输入-输出有界(Bounded input and bounded output, BIBO)稳定.     

Output‐feedback tracking in causal nonminimum‐phase nonlinear systems using higher‐order sliding modes

Asymptotic output‐feedback tracking in a class of causal nonminimum phase uncertain nonlinear systems is addressed via sliding mode techniques. Sliding mode control is proposed for robust stabilization of the output tracking error in the presence of a bounded disturbance. The output reference profile and the unknown input/disturbance are supposed to be described by unknown linear exogenous systems of a given order. Local asymptotic stability of the output tracking error dynamics along with the boundedness of the internal states are proven. The unstable internal states are estimated asymptotically via the proposed multistage observer that is based on the method of extended system center. A higher‐order sliding mode observer/differentiator is used for the exact estimation of the input–output states in a finite time. The bounded disturbance is reconstructed asymptotically. A numerical example illustrates the efficiency of the proposed output‐feedback tracking approach developed for causal nonminimum phase nonlinear systems. Copyright © 2009 John Wiley & Sons, Ltd.     

基于扰动观测器的机械臂自适应反演滑模控制

机械臂的动力学模型通常包含一定的结构不确定性,并受到外界未知干扰的影响。针对现有模型的不确定性特点,提出了一种基于非线性扰动观测器的自适应反演滑模控制方法,解决机械臂的轨迹跟踪控制问题。对于外界干扰,利用非线性扰动观测器进行观测补偿,无需上界先验知识;对于结构不确定性,引入反演滑模控制,同时设计自适应律,保证闭环系统的稳定性并增强系统的动态适应性。仿真结果证明,所提出的方法可以有效克服系统不确定性,降低控制输入信号的抖振,最终实现期望轨迹的快速精确跟踪。     

基于神经网络观测器的船舶轨迹跟踪递归滑模 动态面输出反馈控制

针对三自由度全驱动船舶速度向量不可测问题,考虑船舶模型参数和外部环境扰动均未知的情况,提出一种基于神经网络观测器的船舶轨迹跟踪递归滑模动态面输出反馈控制方法.该方法设计神经网络自适应观测器估计船舶速度向量,且利用神经网络逼近模型参数不确定项,综合考虑船舶位置和速度误差之间关系构造递归滑模面,再采用动态面控制技术设计轨迹跟踪控制律和参数自适应律,并引入低频增益学习方法消除外界扰动导致的高频振荡控制信号.选取李雅普诺夫函数证明了该控制律能够保证轨迹跟踪闭环系统内所有信号的一致最终有界性.最后,基于一艘供给船进行仿真验证,结果表明,船舶轨迹跟踪响应速度快,所设计控制器对系统模型参数摄动及外界扰动具有较强的鲁棒性.     

Output Constrained Adaptive Controller Design for Nonlinear Saturation Systems

This paper considers the adaptive neuro-fuzzy control scheme to solve the output tracking problem for a class of strict-feedback nonlinear systems.Both asymmetric output constraints and input saturation are considered.An asymmetric barrier Lyapunov function with time-varying prescribed performance is presented to tackle the output-tracking error constraints.A high-gain observer is employed to relax the requirement of the Lipschitz continuity about the nonlinear dynamics.To avoid the"explosion of complexity",the dynamic surface control(DSC)technique is employed to filter the virtual control signal of each subsystem.To deal with the actuator saturation,an additional auxiliary dynamical system is designed.It is theoretically investigated that the parameter estimation and output tracking error are semi-global uniformly ultimately bounded.Two simulation examples are conducted to verify the presented adaptive fuzzy controller design.     

An Active Disturbance Rejection Approach to Leader‐Follower Controlled Formation

This article describes the design of a linearizing, observer‐based, robust dynamic feedback control scheme for output reference trajectory tracking tasks in a leader‐follower non‐holonomic car formation problem. The approach is based on the cars' kinematic models. A radical simplification in the form of a global ultra‐model is proposed on the follower's exact open loop position tracking error dynamics obtained via flatness considerations. This results in a system described by an additively disturbed set of two, second order integrators with non‐linear velocity dependent control input gain matrix. The unknown additive disturbances are modeled as absolutely uniformly bounded time signals which may be locally approximated by arbitrary elements of a sufficiently high degree family of Taylor polynomials. Linear high‐gain Luenberger observers of the generalized proportional integral (GPI) type may be readily designed. These observers include the self updating internal model of the unknown disturbance input vector components in the form of generic, instantaneous, time‐polynomial models. The proposed (GPI) observers, which are the dual counterpart of GPI controllers [17], achieve a simultaneous disturbance estimation and tracking error phase variables estimation. This on‐line gathered information is used to advantage on the follower's feedback controller thus allowing for a simple, yet efficient, disturbance and control input gain cancelation effort. The results are applied to have the follower track a time‐delayed version of the actual leader's trajectory. Experimental results are presented which illustrate the robustness and viability of the proposed approach.     

直线电机位置轨迹自适应渐近跟踪

针对直线电机构成的伺服系统中存在的负载扰动和端部效应等阻力扰动,设计了一个自适应的轨迹渐近跟踪控制器;控制律的实现只涉及输出位移的测量信号,而不必依赖于速度的测量;先引入一个基于K滤波器结构的降阶观测器,接着利用自适应观测器后推技术设计了轨迹跟踪控制器和扰动参数估计的自适应律;对闭环系统的稳定性和渐近跟踪能力做了理论分析,并进行了仿真研究;仿真结果表明;设计的控制器可以实现对目标轨迹的渐近跟踪;在系统持续激励的情况下,扰动参数的估计可以收敛到真正的值。     

显式抑制测量误差的改进滑模控制

反馈控制系统中模型不确定性和测量误差的同时出现, 给高精度控制器的设计带来挑战. 经典滑模控制能抵抗一定程度的模型不确定性和输入干扰, 但引入的高增益使得其性能对测量噪声极为敏感, 也容易引起系统强烈抖振. 为此, 本文针对一种典型的角度和角速率测量分别包含高频和低频测量误差条件, 提出了一种改进的基于趋近律的角度跟踪控制方案. 本方案采用低通滤波器来应对高频测量噪声, 同时采用一种新颖的基于模型的测量误差估计器, 来补偿低频测量漂移. 采用Quanser Aero平台进行两自由度角轨迹跟踪控制仿真和实验验证, 并与自抗扰控制等几种典型鲁棒控制方案进行了全面对比, 证实了本文方案性能上的优越性和调参的便捷性.     

A disturbance observer design for backlash compensation

Electromechanical systems usually have an innate backlash in their gear trains which is normally nonlinear and limits the performance of the system. In this paper, a disturbance observer is designed in order to estimate the properties of the backlash. Generally, such disturbance observers are designed with the inverse model of the nominal plant but since the backlash is an internal factor of the plant, its effect cannot be separated from the system output. In the proposed model, the plant is reconfigured to separate the effects of the backlash from the output, and a new type of disturbance observer is proposed to detect and compensate for the backlash in the remodelled plant. The suggested disturbance observer is applied to the knee joint of a humanoid robot. Using the proposed disturbance observer, it is shown that the backlash can be compensated for, and that the tracking error decreases in the knee pitch trajectory. Also, an error analysis of the input trajectory is carried out to verify the performance of the proposed disturbance observer and the validity of the proposed control scheme is discussed.     

Robust synchronisation tracking control of networked Euler–Lagrange systems using reference trajectory estimation based on virtual double-integrators

This paper considers the problem of distributed synchronisation tracking control of multiple Euler–Lagrange systems on a directed graph which contains a spanning tree with the leader node being the root. To design the high performance distributed controllers, a virtual double-integrator is introduced in each agent and is controlled by a virtual distributed linear high-gain synchronisation tracking controller, so that the position and velocity of each agent track those of the reference trajectory with arbitrarily short transient time and small ultimate tracking error. Then taking the double-integrator's position and velocity as the estimates of those of the reference trajectory, in each generalised coordinate of each Euler–Lagrange agent, a local controller with a disturbance observer and a sliding mode control term is designed, to suppress the mutual interactions among the agents and the modelling uncertainties. The boundedness of the overall signals and the synchronisation tracking control performance are analysed, and the conditions for guaranteed control performance are clarified. Simulation examples are provided to demonstrate the performance of the distributed controllers.     

永磁同步电动机的平滑跟踪伺服控制及实现

针对永磁同步电动机位置伺服控制的最小时间响应和平滑轨迹跟踪问题,提出一种改进的二阶离散非线性平滑轨迹跟踪滤波器,该滤波器的输出适合于伺服系统的前馈控制.结合永磁同步电动机的(d,q)数学模型,采用线性控制实现电流闭环使机电运动系统等效为典型的二阶系统,利用非线性平滑轨迹跟踪滤波器为电流环提供前馈输入,并设计一个降阶的扰动观测器保证了系统具有较强的鲁棒性.利用DSP(TM S320LF2407A)实现算法并与传统的PID算法进行了比较,通过仿真和实验结果证明了所提方法的正确性和有效性.     

基于干扰观测器的机械臂广义模型预测轨迹跟踪控制

为实现对多自由度机械臂关节运动精确轨迹跟踪,提出一种基于非线性干扰观测器的广义模型预测轨迹跟踪控制方法。针对机械臂轨迹跟踪运动学子系统,采用广义预测控制（Generalized Predictive Control,GPC）方法设计期望的虚拟关节角速度。对于机械臂轨迹跟踪动力学子系统,考虑机械臂的参数不确定性和未知外界扰动,利用GPC方法设计关节力矩控制输入,基于非线性干扰观测器方法实时估计和补偿系统模型中的不确定性。在李雅普诺夫稳定性理论框架下证明了机械臂关节角位置和角速度的跟踪误差最终收敛于零的小邻域。数值仿真验证了所提出控制方法的有效性和优越性。     

轮式移动机器人的位置量测输出反馈轨迹跟踪控制

针对机器人的姿态角难以精确测量的困难,本文研究基于位置测量的轮式移动机器人的轨迹跟踪问题.首先提出一种利用机器人的位置信息估计其姿态角的降维状态观测器,当机器人的线速度严格大于零时,可保证姿态角观测误差的指数收敛.然后给出一种新的状态反馈轨迹跟踪控制律,当参考轨迹满足一定的激励条件时,可以保证机器人的线速度严格大于零且跟踪误差全局渐近收敛.进一步结合姿态角观测器和状态反馈控制律,得到一种输出反馈轨迹跟踪控制算法.理论分析表明,当参考轨迹满足一定的激励条件时,所提出的输出反馈控制算法可以保证跟踪误差的全局渐近收敛.最后对所提出的姿态角观测器、状态反馈和输出反馈轨迹跟踪控制算法进行了仿真验证,证实了算法的有效性,并且当存在位置测量误差时,所提出的输出反馈轨迹跟踪控制算法仍可以保证机器人对参考轨迹的实际跟踪.     

模糊输出反馈实现动态不确定非线性系统的几乎干扰解耦

研究一类单输入单输出动态不确定非线性系统的几乎干扰解耦问题. 首先设计一类新型的模糊高增益观测器估计非线性系统的未知状态; 然后结合自适应模糊backstepping 控制、小增益定理和改变供能函数方法, 给出鲁棒自适应模糊控制器的设计. 所设计的控制器不仅可以保证整个闭环系统在输入到状态实际稳定意义下稳定, 同时抑制了干扰对输出的影响. 仿真结果表明了所提出控制方法的有效性.

     

具有输入约束和输出噪声的不确定系统级联线性自抗扰控制EI北大核心CSCD

针对一类具有输入约束和输出噪声的SISO(Single input single output)不确定非线性系统,提出了一种基于误差补偿和工程滤波的抗饱和级联线性自抗扰控制(Linear active disturbance rejection control,LADRC)方法.首先针对高频量测噪声,分析了线性扩张状态观测器(Linear extended state observer,LESO)对噪声的放大机理及其与观测器增益的定量关系,进而设计了一种基于工程滤波器的级联LADRC方法,在滤除噪声的同时有效补偿了因滤波所造成的输出幅值和相位损失,确保了闭环系统的跟踪精度.然后继续考虑输入饱和的问题,利用LADRC的实时估计/补偿能力,通过将饱和差值信号引入LESO,设计了一种基于误差补偿的抗饱和LADRC方法,有效减小了系统设计控制量,避免了系统长时间陷入饱和.通过实时仿真比较,验证了所提出方法的有效性.     

具有输入饱和的近空间飞行器鲁棒控制

针对近空间飞行器这一类存在外部扰动,输入饱和和参数不确定的多输入多输出线性系统,提出了一种基于干扰观测器的抗饱和鲁棒控制方案.将干扰观测器与抗饱和控制技术相结合,从而消除系统存在的未知外部扰动、输入饱和和不确定性对系统控制的影响.首先,设计干扰观测器对线性外部系统产生的未知扰动进行估计.然后根据干扰观测器输出,通过超前抗饱和方法设计抗饱和补偿器,并将其加入到鲁棒控制器的设计中,保证闭环系统存在输入饱和、未知外部扰动和参数不确定情况下的稳定性.为便于设计,干扰观测器、抗饱和补偿器和控制器设计矩阵均通过求解线性矩阵不等式得到.最后,将提出的鲁棒抗饱和控制方法应用于近空间飞行器,仿真结果验证了该控制方案的有效性.