不同种混沌系统之间的同步

为实现不同种混沌系统之间的同步问题,提出一种基于高增益观测器的滑模控制混沌同步方法.该方法以混沌同步误差系统的标准型为模型,将两个混沌系统之间的结构差异扩张成系统的状态,尽可能少地利用可测的系统信息来构造高增益观测器估计系统的所有状态,设计出物理上可实现的滑模控制策略,有效地解决了不同种系统之间的混沌同步问题.理论分析和仿真结果都验证了该方法的可行性和有效性.该方法在基于混沌同步的保密通信中有很好的应用前景.     

基于干扰观测器的储能反步控制

当直流侧电压波动较大时,基于反步法设计的储能变流器无法依靠自身的鲁棒性平抑功率和直流电压波动.文章提出了一种基于干扰观测器的储能变流器反步控制算法,可提升控制器抗干扰的性能,有效抑制直流电压波动.首先建立双级式储能变流器数学模型并分析其工作原理;然后采用基于干扰观测器的反步法设计了储能变流器的控制器;最后,在Matla...     

基于LSSVM的卫星姿态控制系统故障诊断

提出了一种基于最小二乘支持向量机(LSSVM)非线性观测器的卫星姿态控制系统故障诊断方法。与标准的支持向量机回归算法相比,最小二乘支持向量机回归算法收敛速度快,适用于在线训练。该方法利用其回归逼近非线性函数的能力,设计基于最小二乘支持向量机的非线性系统状态观测器,在线训练最小二乘支持向量机回归,并用于估计卫星姿态控制系统故障。最后,通过仿真验证了这种方法可以快速准确地估计出卫星姿态控制系统的故障。     

基于观测器的卷绕物收卷张力控制系统的研究

本文以一类卷绕系统的收卷过程为研究对象,建立了其动态数学模型,提出了一种基于张力观测器的新型控制方案。笔者根据辊的动态转矩平衡方程式,利用系统原有的电机控制和速度检测信号,将观测的张力值作为反馈,构成张力闲环,从而实现无传感器反馈控制。最后,对这种方案进行了仿真。结果表明,本文提出的方案完全可以达到常规规方案的动态性能,具有较高的稳态精度。这充分说明了该算法是可行的。     

Force,orientation and position control in redundant manipulators in prioritized scheme with null space compliance

This paper addresses the problem of executing multiple prioritized tasks for robot manipulators with compliant behavior in the remaining null space. A novel controller–observer is proposed to ensure accurate accomplishment of various tasks based on a predefined hierarchy using a new priority assignment approach. Force control, position control and orientation control are considered. Moreover, a compliant behavior is imposed in the null space to handle physical interaction without using joint torque measurements. Asymptotic stability of the task space error and external torque estimation error during executing multiple tasks are shown. The performance of the proposed approach is evaluated on a 7R light weight robot arm by several case studies.     

Global Practical Mittag Leffler Stabilization by Output Feedback for a Class Of Nonlinear Fractional‐Order Systems

In this paper, the problem of a global practical Mittag Leffler feedback stabilization for a class of nonlinear fractional order systems by means of observer is described. The linear matrix inequality approach is used to guarantee the practical stability of the proposed feedback fractional order system. An illustrative example is given to show the applicability of the results.     

关节型工业机器人扭转振动的伺服补偿技术研究

针对工业机器人用RV减速机传动误差所引起的动态失稳现象,在建立由驱动电机-RV减速机-负载所构成的机电耦合系统的基础上,同时考虑负载侧不宜安装传感器的限制条件,依据转矩波动引起转速波动的原理,将由状态观测器间接得到的能够反映转矩波动变化的状态变量——负载加速度变化率作为反馈控制量,对电磁转矩进行实时补偿。经系统的时频域性能分析证明,补偿后的电机转矩命令值抵消了转矩波动的影响,负载侧转速波动得到了很好的抑制,能够极大提高工业机器人在变工况下的动态工作精度。     

Adaptive neural prescribed performance output feedback control of pure feedback nonlinear systems using disturbance observer

In this study, an adaptive output feedback control with prescribed performance is proposed for unknown pure feedback nonlinear systems with external disturbances and unmeasured states. A novel prescribed performance function is developed and incorporated into an output error transformation to achieve tracking control with prescribed performance. To handle the unknown non-affine nonlinearities and avoid the algebraic loop problem, the radial basis function neural network (RBFNN) is adopted to approximate the unknown non-affine nonlinearities with the help of Butterworth low-pass filter. Based on the output of the RBFNN, the coupled design between sate observer and disturbance observer is presented to estimate the unmeasured states and compounded disturbances. Then, the adaptive output feedback control scheme is proposed for unknown pure feedback nonlinear systems, where a first-order filter is introduced to tackle with the issue of “explosion of complexity” in the traditional back-stepping approach. The boundedness and convergence of the closed-loop system are proved rigorously by utilizing the Lyapunov stability theorem. Finally, simulation studies are worked out to demonstrate the effectiveness of the proposed scheme.     

Robust fault estimation based on learning observer for Takagi-Sugeno fuzzy systems with interval time-varying delay

This paper studies the problem of robust fault estimation for a class of Takagi-Sugeno(T-S) fuzzy systems which subject to interval time-varying delay, external disturbance, and actuator fault. The designed learning observer can achieve simultaneous estimation of system state and time-varying or constant actuator fault. Then, we construct a new Lyapunov-Krasovskii functional including the information of the lower and upper delay bounds; compared with the time-varying delay, the interval time-varying delay is the less conservative form. Furthermore, one less conservative delay-dependent condition for the existence of learning observer is given in terms of linear matrix inequalities. In addition, the results for the systems with interval time-varying delay are simplified when the delay is not concluded. Finally, simulation results of two examples are presented to show the effectiveness of the proposed method.     

Nonlinear observer design for two-time-scale systems

A two-time-scale system involves both fast and slow dynamics. This article studies observer design for general nonlinear two-time-scale systems and presents two alternative nonlinear observer design approaches, one full-order and one reduced-order. The full-order observer is designed by following a scheme to systematically select design parameters, so that the fast and slow observer dynamics are assigned to estimate the corresponding system modes. The reduced-order observer is derived based on a lower dimensional model to reconstruct the slow states, along with the algebraic slow-motion invariant manifold function to reconstruct the fast states. Through an error analysis, it is shown that the reduced-order observer is capable of providing accurate estimation of the states for the detailed system with an exponentially decaying estimation error. In the last part of the article, the two proposed observers are designed for an anaerobic digestion process, as an illustrative example to evaluate their performance and convergence properties.