一种反向递推正弦干扰观测器的设计方法

在多源干扰环境下,考虑一种基于输出信号的正弦干扰估计方法.引入低通滤波器激励干扰特性,得到一组级联关系的不可测信号,并将其分解为标准正弦虚拟干扰、等价有界干扰以及衰减项;在频率已知条件下,设计辅助滤波器,建立干扰频率与虚拟干扰之间关系,从而将外部正弦扰动表示为关于虚拟干扰的参数形式,利用虚拟干扰的估计值逐次降阶反推输入干扰.该干扰观测器设计方法独立于控制器结构,不需要估计等效干扰状态,可很大程度上降低计算复杂度.当不存在等价有界干扰时,这种反向递推方式可以渐近跟踪正弦干扰.在多源干扰环境下,通过调节辅助滤波器参数可以保证干扰误差动态一致最终有界特性.仿真和实验验证了该干扰观测结构的有效性.     

一类非最小相位系统未知频率正弦干扰的观测器设计

近年来,前馈补偿技术得到广泛研究,其可以提高系统的控制精度.对于非最小相位系统,很难给出干扰和可测信息的直接关系,此外,频率的不确定性以及估计值之间的耦合会导致大量冗余参数的运算.现有的自适应方法存在估计值之间的耦合,会增加干扰估计误差收敛性能分析难度.而基于干扰观测器控制(DOBC)通过调节控制器和观测器参数,可以同时对多源不确定进行补偿和抑制.基于此,提出一种分步式观测器设计方法.首先设计一种辅助滤波器和观测器对未知频率正弦干扰参数进行估计,同时给出干扰的等效形式;然后利用估计值构造观测器得到输入干扰状态,从而将这类非线性系统的干扰抵消问题转换为线性系统的观测器设计问题;最后通过李雅普诺夫定理和数值仿真验证所提出方法的有效性.     

一类随机系统基于干扰观测器的抗干扰控制

针对一类带有多源干扰的随机系统,研究其抗干扰控制问题.针对可以由未知参数的外源系统产生,代表频率、振幅和初相都未知的干扰,构建随机自适应干扰观测器对其进行估计.基于此,结合自适应控制和随机控制的方法,提出基于干扰观测器的抗干扰控制策略,保证复合系统的所有信号均为均方渐近有界.仿真结果验证了所提出方法的正确性和有效性.     

基于扩张观测器的欠驱动船舶轨迹跟踪低频学习自适应动态面输出反馈控制

针对速度不可测的三自由度欠驱动船舶轨迹跟踪控制问题,考虑船舶存在模型参数不确定项以及外界环境干扰未知情况,提出一种基于扩张观测器的欠驱动船舶轨迹跟踪低频学习自适应动态面输出反馈控制策略.该策略构造扩张观测器估计船舶速度向量,利用神经网络算法逼近模型参数不确定项,然后采用动态面控制技术避免对虚拟控制律直接求导,简化控制律计算过程,并引入低频增益学习技术消除外界扰动导致控制信号产生高频振荡,最后选取李雅普诺夫函数证明该控制律能够保证船舶跟踪闭环系统中所有误差信号一致最终有界.仿真结果表明,本文所设计控制器对船舶模型参数不确定项及外界环境干扰具有较强的鲁棒性,能够实现对船舶轨迹的有效跟踪.     

非线性关联大系统的鲁棒自适应观测器设计

针对一类存在未知参数、干扰和未建模动态的非线性关联大系统,提出了一种鲁棒自适应观测器.在观测器中对每个子系统引入一个动态信号来独立抑制未建模动态,同时用自适应非线性阻尼项来克服系统关联.用此观测器不需要估计未知参数及求解线性矩阵不等式.本文从理论上证明了所设计的观测器误差一致有界,并且通过恰当选择有关设计参数可使估计误差任意小.     

基于神经网络的欠驱动水下机器人三维同步跟踪和镇定控制

研究了欠驱动水下机器人的三维同步跟踪和镇定控制问题,并考虑了模型参数不确定性、未知外界干扰和输入饱和限制的影响.针对不同类型期望轨迹的特性,构造了新的辅助虚拟信号以实现对欠驱动方向的控制.基于反步法和Lyapunov直接法,设计了一种饱和自适应统一动力学控制律,使得AUV的状态误差最终收敛至零点附近的有界区域内,其中未知模型参数和外部干扰通过基于神经网络的更新律进行估计.仿真结果表明该控制方法是有效的且具有较好的控制效果.     

短时延网络控制系统的鲁棒H 2 öH ∞状态观测器设计

针对受白噪声干扰的短时延网络控制系统,将随机时延对系统的影响转化为未知有界不确定项,在不改变闭环系统结构的前提下,利用鲁棒控制理论提出了系统的H2/H∞状态观测器设计方法;证明了所设计状态观测器估计输出对随机时延引起的不确定项的H∞鲁棒性,给出了估计输出对白噪声干扰的鲁棒H2性能指标的求解方法和观测器增益阵的确定方法.最后通过仿真实例证实了所设计状态观测器的有效性和鲁棒性.     

基于滑模观测器和广义观测器的故障估计方法

针对受未知干扰影响的一类非线性系统,提出一种基于滑模观测器和广义观测器的执行器故障和传感器故障估计方法.首先通过线性变换将原系统解耦为两个降阶的子系统,其中一个子系统受执行器故障和干扰的影响,另一个含有传感器故障和干扰,进一步将后一个子系统转化为广义系统.对两类子系统分别设计滑模观测器和广义观测器,给出估计误差一致最终有界的条件,得到系统状态和未知干扰的估计值.然后,利用等效输出控制原理重构执行器故障,引入干扰补偿保证重构算法的鲁棒性,再根据广义观测器的结果获得传感器故障的估计值.最后,通过计算机仿真验证了本文方法的有效性.     

基于预估器的一类多智能体系统神经动态面输出一致控制

本文针对一类含未知扰动与非对称输入饱和的非线性多智能体系统,提出基于预估器的神经动态面输出一致控制策略.在设计预估器的基础上构造预估误差,驱动神经网络更新权值估计系统未知动态,并将预估器与神经网络应用于非线性扰动观测器来补偿广义扰动.本文所提出的控制策略采用神经网络权值范数学习方法,减少学习参数数目.对于非对称的输入饱和,设计辅助系统,其生成的辅助变量与反步法相结合补偿输入限制.结合图论知识和Lyapunov函数等技术,证明多智能体系统的输出一致跟踪误差以及闭环系统中的所有信号最终有界.最后通过一组四旋翼飞行器和数值仿真验证提出控制策略的有效性.     

基于非线性干扰观测器的一类欠驱动系统跟踪控制

针对一类欠驱动系统的跟踪控制问题,提出一种基于非线性干扰观测器的控制策略.首先给出一种基于跟踪误差的输出函数,通过等式变形和Butterworth低通滤波器解决未知控制方向问题;其次,引入一种新型非线性干扰观测器,对系统未知模型进行补偿,使控制器的设计无需知道系统的结构和参数;再次,通过对系统的内部动态和外部动态的分析,证明闭环系统的输出收敛于原点,跟踪误差信号一致最终有界;最后,将该方法应用于小车倒立摆模型,仿真结果表明了所提出方法的有效性.     

Rejection and Attenuation of Multiple Disturbances for a Class of Uncertain Systems

A novel anti-disturbance strategy for a class of uncertain systems is investigated. Besides the unknown frequency sinusoidal, the controlled plant is subjected to bounded noise and unknown nonlinear term simultaneously. Through the construction of auxiliary observer, the sinusoidal is represented in a parametric uncertainty form. Only one unknown scalar needs estimating to construct compensation signal, meanwhile the unwanted nonlinear operation between frequency and equivalent disturbance can be removed. By integrating a feedback control law, all the unexpected dynamics can be rejected and attenuated respectively, where the conditions on the stability and optimal performance are also provided. Finally, a computer simulation example is presented to illustrate the effectiveness and the applicability of the suggested method.

     

Disturbance‐prediction–based control of input time delay systems for rejection of unknown frequency disturbances

In this paper, a novel disturbance rejection approach is presented for a class of input time‐delay systems subject to sinusoidal disturbances with unknown frequency. In particular, an auxiliary observer is proposed to represent the periodic disturbance in a parametric uncertainty form, where the unknown factor related to disturbance frequency can be estimated. Furthermore, the correlation between the future disturbance and the auxiliary observer output is analyzed, such that the future disturbances can be predicted and rejected through the input channel. Based on the aforementioned observer and predictor structure, the overall control architecture can be established as a framework of disturbance‐prediction–based control for systems with input time delays, where the conditions on the asymptotic stability of the closed‐loop systems are also derived. Finally, numerical examples are provided to illustrate the effectiveness of the proposed control approach.     

Hybrid dead-beat observers for a class of nonlinear systems

This paper studies both the full order and the reduced order dead-beat observer problem for a class of nonlinear systems, linear in the unmeasured states. A novel hybrid observer design strategy is proposed, with the help of the notion of strong observability in finite time. The proposed methodology is applied for the estimation of the frequency of a sinusoidal signal. The results show that accurate estimation can be provided even if the signal is corrupted by high frequency noise. A brief discussion of the robustness properties of the proposed observer with respect to measurement errors is also provided.     

A novel robust adaptive control algorithm with finite-time online parameter estimation of a humanoid robot arm

A novel robust adaptive control algorithm is proposed and implemented in real-time on two degrees-of-freedom (DOF) of the humanoid Bristol-Elumotion-Robotic-Torso II (BERT II) arm in joint-space. In addition to having a significant robustness property for the tracking, the algorithm also features a sliding-mode term based adaptive law that captures directly the parameter estimation error. An auxiliary filtered regression vector and filtered computed torque is introduced. This allows the definition of another auxiliary matrix, a filtered regression matrix, which facilitates the introduction of a sliding mode term into the adaptation law. Parameter error convergence to zero can be guaranteed within finite-time with a Persistent-Excitation (PE) condition or Sufficient Richness condition for the demand. The proposed scheme also exhibits robustness both in the tracking and parameter estimation errors to any bounded additive disturbance. This theoretical result is then exemplified for the BERT II robot arm in simulation and for experiments.     

基于状态集员估计的主动故障检测

对于现代复杂控制系统, 微小故障往往很难发现. 在系统过程干扰和测量噪声未知但有界的前提下, 提出了一种新的基于状态集员估计的主动故障检测方法. 首先设计全对称多胞形卡尔曼滤波器对系统状态进行估计, 并利用全对称多胞形对受未知干扰影响的状态集合进行描述, 然后设计辅助输入信号使得加入辅助输入信号后正常模型的状态集合与故障模型的状态集合交集为空, 从而实现主动故障检测. 为了使得所设计的辅助输入信号对原系统影响最小, 需要求得最小的辅助输入信号, 本文将最优化问题转化为混合整数二次规划问题进行求解. 最后, 与基于输出集合的辅助输入信号设计方法对比, 仿真验证本文所提出的基于状态集合的主动故障检测方法由于未受下一时刻测量噪声的影响, 所求得的辅助输入信号更小, 保守性更低.     

A new nonlinear robust disturbance observer

This paper presents a new nonlinear robust disturbance observer by using only the input–output information for minimum phase dynamical systems with arbitrarily relative degrees. The model uncertainties, the nonlinear parts of the system are merged into the disturbance term, and are regarded as a part of the disturbance. The disturbance is assumed bounded. However, the upper and lower bounds are assumed unknown. The new disturbance observer is inspired by the VSS control theory, whereas the upper and lower bounds of the disturbance are adaptively updated. The estimation error of the disturbance can be made as small as necessary by choosing the design parameters. The attraction of the proposed method lies in its robustness to disturbance and easiness to be implemented. Example and simulation results show the effectiveness of the proposed algorithm.     

Robust State‐and‐Disturbance Observer Design for Linear Non‐minimum‐phase Systems

When there are external disturbances acting on the system, the conventional Luenberger observer design for state estimation usually results in a biased state estimate. This paper presents a robust state and disturbance observer design that gives both accurate state and disturbance estimates in the face of large disturbances. The proposed robust observer is structurally different from the conventional one in the sense that a disturbance estimation term is included in the observer equation. With this disturbance estimation term, the robust observer design problem is skillfully transformed into a disturbance rejection control problem. We then can utilize the standard H_∞ control design tools to optimize the robust observer between the disturbance rejection ability and noise immune ability. An important advantage of the proposed robust observer is that it applies to both minimum‐phase systems and non‐minimum phase systems.     

Adaptive disturbance estimation and cancelation for ships under thruster saturation

This work addresses the problem of disturbance estimation and cancelation for ships with ocean disturbances and modeling uncertainties under thruster saturation effects. The ocean disturbances are expressed as the multiple sinusoidal disturbances with unknown frequencies, amplitudes, and phases. By means of a parametric exogenous system and a canonical model with unknown disturbances being inputs, the ocean disturbances are represented as the multivariate regression model with unavailable regressors and regression parameters. An observer is employed to provide the regressor estimation, such that the disturbance estimation and cancelation are converted to the adaptive control problem. The robust control term with the adaptive technique attenuates the modeling uncertainties. The thruster saturation effects are reduced using the state vectors from the auxiliary dynamic filter to online correct the control errors. The ship disturbance cancelation controller is derived via the adaptive backstepping. The closed‐loop tracking system is guaranteed to be uniformly ultimately stable and the ship's position and heading navigate along with desired trajectories. The proposed adaptive control scheme is validated by simulations with comparisons on a 1:70 scaled model ship CyberShip II in different cases.