时延系统的自抗扰动态面控制

本文针对高阶时延系统同时存在系统不确定性和未知输入时延的情况,考虑控制器信号的复杂性问题,在动态面控制方法的基础上,引入自抗扰控制技术设计了自抗扰动态面控制器.利用反步法设计动态面控制信号,采用跟踪微分器对虚拟控制信号滤波,避免了由于对虚拟控制信号重复微分产生的"复杂性爆炸"问题;在控制信号的基础上叠加扰动补偿项,补偿项由扩张状态观测器实时在线估计产生,保证了控制信号的实时性,同时简化了控制器结构以便于实际应用.在闭环系统稳定性判别中运用李雅普诺夫理论做出详细分析.最后,数值仿真结果验证了所提出方法的有效性.     

固定翼无人机的自抗扰反步控制

针对固定翼无人机姿态和速度控制中系统存在模型不确定性和外界扰动的情况,本文设计了基于扩张状态观测器的反步控制器抑制系统扰动以提高无人机的控制性能.首先建立无人机速度误差模型和姿态误差模型,其中姿态误差模型采用四元数作为变量以避免欧拉角在描述姿态时存在的奇点问题和复杂三角运算;进而设计扩张状态观测器对系统中存在的扰动进行估计,并将扰动估计值与控制器设计相结合,分别设计出姿态控制器和速度控制器来抑制扰动的影响且使无人机姿态和速度收敛到期望值.最后基于李雅普诺夫理论证明系统的稳定性.仿真结果表明,本文所设计方法能够抑制系统中存在的扰动.     

扩展卡尔曼滤波结合前馈补偿永磁同步电机位置估计

转速和转子位置的精确估计对建立永磁同步电机(permanent magnet synchronous moter,PMSM)转速、电流双闭环矢量控制系统非常重要.本文主要研究扩展卡尔曼滤波算法(extended Kalman filter,EKF)估计转速、转子位置问题.与传统EKF估计转子位置方法不同的是,本文采用遗传算法(GA)优化EKF的协方差矩阵,并给出P,Q,R矩阵选取过程.另外将负载转矩观测器观测的负载转矩同速度调节器的输出一起作为电流调节器的控制变量.仿真及实验结果表明:文中提出的新方法有效缩短系统协方差参数选取时间,提高转速的辨识精度和抗负载扰动能力.     

连续线性切换系统的镇定慢切换设计

针对含有两个不稳定子系统的线性切换系统,设计一种包含时间驱动和状态驱动两个环节的切换法则,使线性切换系统稳定.在该切换法则下,系统的类Lyapunov函数在两个环节都不需要严格单调递减,使得系统在每个子系统有更长的驻留时间,从而有效降低系统的切换频率.在适当的假设条件下,带时变扰动的线性切换系统在该切换信号下具有良好的鲁棒稳定性.基于此,当系统可观测时,进一步设计了基于观测器的混合切换法则,实现了系统的鲁棒稳定.     

一类非线性严格反馈系统基于干扰观测器的抗干扰控制

针对一类带有干扰的非线性严格反馈系统, 研究其抗干扰控制问题. 系统干扰满足不匹配条件, 代表一类部分信息已知的干扰. 通过设计非线性干扰观测器, 提出基于非线性干扰观测器和back-stepping 的抗干扰控制方法来补偿干扰, 该方法可以保证闭环系统所有信号是半全局最终一致有界的. 最后, 通过与现有方法的对比验证了所提出方法的正确性和有效性.

     

基于扩张状态观测器的分散模型预测控制

针对复杂关联系统中分散控制方法无法有效解决子系统间的耦合和干扰问题, 提出一种基于扩张状态观测器的分散模型预测控制算法. 首先将复杂关联系统分解为多个状态维数较低、控制变量较少的子系统, 并为每个子系统设计本地预测控制器; 然后, 采用扩张状态观测器对子系统的耦合项以及干扰项进行估计, 进而利用估计值对子系统进行前馈补偿, 从而降低复杂关联系统的计算复杂度, 提高系统的稳定性和抗干扰能力; 最后, 利用液位控制系统验证了所提出算法的有效性.

     

基于广义扩张状态观测器的干扰不匹配离散系统状态反馈控制

针对一类干扰不匹配的线性离散时间系统, 研究基于广义扩张状态观测器的稳定化状态反馈控制器设计问题. 在经典的自抗扰控制器中, 扩张状态观测器主要针对干扰匹配的积分串联型系统. 然而, 在许多实际系统中往往存在干扰不匹配的情况, 例如存在采样抖动的离散时间控制系统. 针对这一问题, 基于一类存在不匹配干扰的离散时间系统, 提出广义扩张状态观测器和相应的稳定化状态反馈控制器设计方法. 最后通过永磁同步电机调速控制仿真实例验证了所设计的观测器和控制器的有效性.

     

A note on interval observer design for unknown input estimation

This paper addresses the problem of interval observer design for unknown input estimation in linear time-invariant systems. Although the problem of unknown input estimation has been widely studied in the literature, the design of joint state and unknown input observers has not been considered within a set-membership context. While conventional interval observers could be used to propagate with some additional conservatism, unknown inputs by considering them as disturbances, the proposed approach allows their estimation. Under the assumption that the measurement noise and the disturbances are bounded, lower and upper bounds for the unmeasured state and unknown inputs are computed. Numerical simulations are presented to show the efficiency of the proposed approach.     

A neural-network-based exponential H∞ synchronisation for chaotic secure communication via improved genetic algorithm

In this study, a novel approach via improved genetic algorithm (IGA)-based fuzzy observer is proposed to realise exponential optimal H^∞ synchronisation and secure communication in multiple time-delay chaotic (MTDC) systems. First, an original message is inserted into the MTDC system. Then, a neural-network (NN) model is employed to approximate the MTDC system. Next, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. Based on this LDI state-space representation, this study proposes a delay-dependent exponential stability criterion derived in terms of Lyapunov's direct method, thus ensuring that the trajectories of the slave system approach those of the master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Due to GA's random global optimisation search capabilities, the lower and upper bounds of the search space can be set so that the GA will seek better fuzzy observer feedback gains, accelerating feedback gain-based synchronisation via the LMI-based approach. IGA, which exhibits better performance than traditional GA, is used to synthesise a fuzzy observer to not only realise the exponential synchronisation, but also achieve optimal H^∞ performance by minimizing the disturbance attenuation level and recovering the transmitted message. Finally, a numerical example with simulations is given in order to demonstrate the effectiveness of our approach.     

Periodic event‐triggered observation and control for nonlinear Lipschitz systems using impulsive observers

In this paper, we investigate the observation and stabilization problems for a class of nonlinear Lipschitz systems, subject to network constraints, and partial state knowledge. In order to address these problems, an impulsive observer is designed, making use of the event‐triggered technique in order to diminish the network communications. Sufficient conditions are given to ensure a milder version of the separation principle for these systems, controlled via an event‐triggered controller. The proposed observer ensures practical state estimation, while the corresponding dynamic controller ensures practical stabilization. The sampling and the data transmission are carried out asynchronously. The dynamic controller is tested in simulation on a flexible joint. Copyright © 2017 John Wiley & Sons, Ltd.