随机多源干扰系统的复合DOBC和容错控制

针对一类带有多源干扰和常值故障的随机系统,研究其抗干扰和故障诊断问题.多源干扰包括由外源系统生成的部分信息已知的干扰和白噪声干扰两类.第1类干扰包含状态和干扰耦合,不仅可以代表一类部分信息已知的干扰,还可以代表一类随机干扰,且耦合增加了系统的复杂性,导致必然等价原则的无效.为了解决这个问题,提出复合极点配置和线性矩阵不等式(LMI)方法相结合的策略.首先,设计随机干扰观测器来估计第1类干扰;其次,设计随机故障诊断观测器来估计系统故障.基于此,结合容错控制和随机控制,提出基于观测器的复合容错控制策略,在满足一定条件下,该策略可以保证复合系统满足依均方渐近有界.最后,通过仿真验证所提出策略的正确性与有效性.     

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.

     

基于干扰观测器的终端滑模控制研究

针对一类非线性不确定系统,提出一种带干扰观测器的终端滑模控制TSMC方案.在不考虑外部干扰的影响下,设计了终端滑模控制,保证系统状态在有限时间内收敛到零;当存在干扰时,构造了非线性干扰观测器系统,以在线逼近未知外部干扰,消除其影响.考虑输人通道的不确定性,采用自适应方法在线逼近不确定的上界,并采用Lyapunov方法严格证明了自适应闭环系统的稳定性.对一级倒立摆系统进行仿真,仿真结果表明了所设计控制方案的有效性.     

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.     

载人潜水器的干扰特性分析与自适应滑模控制

针对在实际运行中会受到未知外部环境干扰和模型不确定性等因素影响的蛟龙号载人潜水器系统,本文设计了一种基于干扰特性指标的新型自适应滑模控制方法,实现对有益干扰的利用和有害干扰的补偿.首先,文章给出载人潜水器系统的运动学和动力学模型;然后,本文设计非线性干扰观测器估计系统所受的集总扰动,并提出一种扇形区域干扰特性指标,用于判断干扰对系统的影响;其次,文章设计一种基于干扰特性指标的自适应滑模控制方法,并且根据李雅普诺夫理论进行严格的稳定性分析;最后,通过数值仿真,验证所设计的滑模控制方法的优越性.其优越性主要体现在:不仅能够有效缓解抖振现象,并且避免控制增益高估的问题.     

基于干扰观测器的非线性不确定系统自适应滑模控制

本文研究了一类基于非线性干扰观测器的多输入多输出非线性不确定系统的边界层自适应滑模控制方法并应用于近空间飞行器高精度姿态控制.考虑系统存在不确定性和外部干扰上界未知的情况,设计了基于干扰观测器的边界层自适应滑模控制器,以消除传统滑模控制中的"抖振"现象,使跟踪误差趋近于零.同时,利用李雅普洛夫方法严格证明了闭环系统的稳定性.最后将所研究的自适应滑模控制方法,应用于某近空间飞行器的姿态控制中,仿真结果表明在不确定性和外部干扰作用下能保证姿态控制的稳定性,对参数不确定具有较好的鲁棒性.     

双事件触发下非匹配干扰系统积分滑模抗干扰跟踪控制

对于带有不匹配干扰的动态系统,设计具有高资源利用率的抗干扰控制算法具有重要意义.本文在双事件触发机制框架下,研究了非匹配干扰系统的积分滑模抗干扰控制以及动态性能分析问题.首先,基于增广模型构建干扰观测器,实现对未知不匹配干扰的动态估计.为了降低数据冗余并保证传输的同步性,以反馈状态及干扰估计的单触发条件为基础,本文构建了“先到同触发”的双事件触发理论框架.在此框架下,设计积分滑模面和对应的双触发抗干扰控制器,保证被控系统的状态收敛到滑模面.基于Lyapunov稳定性分析方法,计算控制器和观测器增益,保证增广闭环系统具有良好的稳定性和动态跟踪性能.进一步分析了由触发引起的Zeno现象将不会发生.最后,基于典型的A4D模型进行仿真验证,仿真结果表明本文所提的方法具有良好的抗干扰性能.     

带有执行器饱和的变时滞Markovian 跳变系统的DOBC控制

针对一类转移概率部分未知的Markovian跳变系统,考虑系统中存在时变时滞以及执行器饱和的情况,研究此类系统基于干扰观测器的抗干扰控制(Disturbance-observer-based-control,DOBC)问题.首先,分析带有扰动估计误差的闭环系统的随机稳定性,通过构建适当的模态依赖型Lyapunov-Krasovskii(L-K)泛函并引入自由权矩阵,给出闭环系统的随机稳定性判据;然后,将控制器增益以及观测器增益的求解问题转化为带有线性矩阵不等式约束的可行性问题,并通过迭代优化算法得到最大吸引域的估计值;最后,通过仿真算例,验证所提出方法的正确性和有效性.     

微纳卫星姿态控制系统的精细抗干扰容错控制方法

本文针对一类微纳卫星姿态控制系统飞轮突变故障提出了一种具有干扰抑制和补偿能力的精细故障诊断及容错控制方法.针对反作用飞轮的突变故障,本文不仅考虑了星体转动惯量变化导致的系统参数不确定性,而且考虑了姿态控制系统中飞轮振动带来的干扰影响,设计基于干扰观测器和故障诊断观测器的复合抗干扰容错控制器,并基于线性矩阵不等式对控制器进行求解,使复合系统稳定并满足一定的鲁棒H∞性能.仿真结果表明,基于微纳卫星姿态控制系统的精细故障诊断方法在有效诊断系统时变故障的同时,可有效抵消与抑制干扰.     

基于高阶观测器和干扰补偿控制的模型预测控制方法

针对状态不可测、外部干扰未知, 并且状态和输入受限的离散时间线性系统, 将高阶观测器、干扰补偿控制与标准模型预测控制(Model predictive control, MPC)相结合, 提出了一种新的MPC方法. 首先利用高阶观测器同步观测未知状态和干扰, 使得观测误差一致有界收敛;然后基于该干扰估计值设计新的干扰补偿控制方法, 并将该方法与基于状态估计的标准MPC相结合, 实现上述系统的优化控制. 所提出的MPC方法克服了利用现有MPC方法求解具有外部干扰和状态约束的优化控制问题时存在无可行解的局限, 能够保证系统状态在每一时刻都满足约束条件, 并且使系统的输出响应接近采用标准MPC方法控制线性标称系统时得到的输出响应. 最后, 将所提控制方法应用到船舶航向控制系统中, 仿真结果表明了所提方法的有效性和优越性.     

Adaptive disturbance observer‐based control for stochastic systems with multiple heterogeneous disturbances

Antidisturbance control problem is discussed for stochastic systems with multiple heterogeneous disturbances, which include the white noise and the disturbance with unknown frequencies and amplitudes. An adaptive disturbance observer is designed to estimate the disturbance with unknown frequencies and amplitudes, based on which, an adaptive disturbance observer‐based control scheme is proposed by combining adaptive technique and linear matrix inequality method. It is proved that the closed‐loop system is asymptotically bounded in mean square when multiple heterogeneous disturbances exist simultaneously and that the equilibrium is globally asymptotically stable in probability as additive disturbance disappears. Finally, two simulation examples, including a wind turbine system, are given to show the effectiveness of the proposed scheme.     

一种新的随机多变量自适应极点配置控制器

本文提出的随机多变量自适应极点配置控制器,由于采用了一种新的极点配置结构,它不仅可以避免求解伪交换矩阵方程而实现任意极点配置,跟踪时变参考输入,而且可以抑制随机噪声干扰.该控制器不仅可以控制开环不稳定或非最小相位系统,而且还可以控制具有任意、未知或变化的延时结构和具有任意输入输出个数的随机多变量系统。     

On convergence of active disturbance rejection control for a class of uncertain stochastic nonlinear systems

In this paper, the practical mean-square convergence of active disturbance rejection control for a class of uncertain stochastic nonlinear systems modelled by the Itô-type stochastic differential equations with vast stochastic uncertainties is developed. We first design an extended state observer (ESO) to estimate both the unmeasured states and the stochastic total disturbance which includes unknown internal system dynamics, external stochastic disturbance without known statistical characteristics, unknown stochastic inverse dynamics, and uncertainty caused by the deviation of control parameter from its nominal value. The stochastic total disturbance is then cancelled (compensated) in the feedback loop. An ESO-based output-feedback control is finally designed analogously as for the system without uncertainties. The practical mean-square reference tracking and practical mean-square stability of the resulting closed-loop system are achieved. The numerical experiments are carried out to illustrate the effectiveness of the proposed approach.     

Intelligent control of nonlinear systems with application to chemical reactor recycle

The dynamic surface control technique can simplify the backstepping design for the control of nonlinear systems by overcoming the problem of “explosion of complexity.” In this paper, we incorporate this design technique into a neural network-based adaptive control design framework for a class of nonlinear stochastic systems. The time delays exist in the gain of the stochastic disturbance in the systems, and the neural networks are employed to compensate for all unknown nonlinear terms depending on the delayed output. The proposed approach is able to eliminate the problem of “explosion of complexity” inherent in the existing method. It can be proven that all the signals are semi-globally uniformly ultimately bounded in probability, and the system output tracks the reference signal to a bounded compact set. A simulation example is given to verify the effectiveness of the proposed approach.     

Identification Recurrent Type 2 Fuzzy Wavelet Neural Network and L2‐Gain Adaptive Variable Sliding Mode Robust Control of Electro‐Hydraulic Servo System (EHSS)

An electro‐hydraulic servo system (EHSS) is a kind of system with the characteristics of time‐variant, serious nonlinearity, parameter and structural uncertainty, and uncertain load disturbance in most cases. These characteristics make it very difficult to realize highly accurate control by conventional methods. In order to solve the above problems, this paper introduces a recurrent type 2 fuzzy wavelet neural network to approximate the unknown nonlinear functions of the dynamic systems through tuning by the desired adaptive law. Based on the identification by recurrent type 2 fuzzy wavelet neural network, a L2 gain design method, combining gain adaptive variable sliding mode control with H infinity control, is proposed for load disturbance, thereby accommodating uncertainties that are the main factors affecting system stability and accuracy in EHSS. In this algorithm, a recurrent type 2 fuzzy wavelet neural network is employed to evaluate the unknown dynamic characteristics of the system and gain adaptive variable sliding mode control to compensate for evaluating errors, and H infinity control to suppress the effect on system by load disturbance. The experiment results show that the proposed system L2 gain design method can make the system exhibit strong robustness to parameter variation and load disturbance.     

Composite DOBC with fuzzy fault‐tolerant control for stochastic systems with unknown nonlinear dynamics

A class of stochastic nonlinear systems with fault and multisource disturbances is concerned. The fault is a general bounded actuator fault, and the multiple disturbances include partial‐known information disturbance and white noise. A stochastic adaptive disturbance observer is constructed to estimate the partial‐known information disturbance, based on which the partial‐known information disturbance can be compensated in the feed‐foreword channel immediately. Also, the multiplicative white noise can be attenuated by the designed feedback controller. To make the composite system is satisfactory, a composite disturbance based‐observer control with fuzzy fault‐tolerant control is proposed. The pole placement and LMI method is applied to attenuate and reject the disturbance. Furthermore, the fault can be compensated simultaneously. To verify the feasibility and availability of the designed control scheme, a simulation example is shown finally.     

Sliding mode control with disturbance observer for a class of nonlinear systems

This paper is concerned with the stabilization problem for a class of nonlinear systems with disturbance. The disturbance model is unknown and the first derivative of disturbance is bounded. Firstly, a general disturbance observer is proposed to estimate disturbance approximatively. Secondly, since the bound of the disturbance observer error is unknown, an adaptive sliding mode controller is designed to guarantee that the state of system asymptotically converges to zero and the unknown bound can be adjusted by an adaptive law. Finally, an example is given to illustrate the effectiveness of the proposed method.     

输出约束的有限时间自适应区间二型模糊输出反馈PMSM伺服控制

针对永磁同步电机驱动的伺服系统在不确定性摩擦和未知负载的影响下难以达到高精度的控制效果,提出一种基于区间二型模糊系统的带有输出约束的有限时间自适应输出反馈控制方案.首先,构建一个基于非线性扰动观测器的区间二型模糊状态观测器,分别完成对于未知扰动和速度的估计,区间二型模糊系统完成对于非线性摩擦的逼近;然后,在此基础上,结合滤波误差补偿机制和有限时间技术,引入障碍Lyapunov函数和反步控制技术设计输出约束的自适应区间二型模糊输出反馈控制器;最后,根据Lyapunov稳定性理论提出严格的稳定性分析,保证闭环系统的所有信号均是有限时间内有界的,并通过数值仿真和实验验证了所提出方法的有效性.