Takagi-Sugeno模糊连续系统的模糊采样控制

研究了T-S模糊连续系统的模糊采样控制问题．利用广义系统的描述方法、Lyapunov-Krasovikii泛函以及线性矩阵不等式(LMI)方法,建立了LMIs形式的依赖于采样时间间隔的模糊采样镇定条件,同时给出了模糊采样控制律的设计方法．所设计的模糊采样控制律可以镇定T-S模糊系统．而且,当连续时间模糊控制律可以镇定T-S模糊系统时,对于足够小的采样时间间隔,带有同样增益矩阵的模糊采样控制律也可以镇定T-S模糊系统．最后,通过两个仿真实例说明了所给方法的有效性．     

基于粒子群算法的电力应急指挥系统自动控制方法研究

由于前期故障位置无法准确且快速的找出,导致花费的时间较长,使得电力应急指挥系统的时效性较差。提出一种基于粒子群算法的电力应急指挥系统自动控制方法。该方法将故障定位与电力应急指挥系统控制联动在一起,通过粒子群算法准确且快速地定位电网故障位置,缩短前期故障定位所花费的时间,以此为基础,作为模糊控制器的输入物理量,通过模糊控制器的模糊推理,得出故障应急控制方案,控制分段开关闭合或断开,及时隔离故障点,降低损失。结果表明：与基于PID的一般控制方法相比,所研究方法给出的控制方案应用下,开关操作次数和网损要更低,说明所研究方法更能快速完成故障隔离工作,降低故障影响程度,证明所研究控制方法的时效性更好。     

风力发电系统传感器故障诊断

针对非线性风力发电系统,提出了一种基于滑模观测器的传感器故障诊断方法.基于考虑传感器加性故障的非线性动态模型,利用T--S模糊理论建立风力发电系统全局T--S模型,设计模糊T--S系统滑模故障观测器,产生对故障具有敏感性的残差,实现故障检测.通过等价输出控制方法来维持滑模运动,直接获取故障信息,重构传感器故障.最后以三叶片水平轴风力发电系统为例,仿真验证了该方法的有效性与可靠性.     

一种基于模糊神经网络的故障分类器及其在多传感器故障诊断中的应用􀀁

提出了一种应用模糊神经网络进行故障诊断新方法．采用模糊神经网络作为故障分类器,离线地自适应从学习样本数据中提取各个用以描述故障状态的模糊参考模型．在诊断时,此模糊神经网络在线地得到当前系统的模糊模型描述,并将与各个参考模型相匹配,从而得出正确的诊断结果．它适用范围广泛,如用于控制系统的过程对象以及传感器、执行器故障的检测与诊断．通过对燃汽轮机控制系统多传感器故障诊断的仿真证明了此法的有效性和优越性．     

T-S模糊系统H2/H∞混合控制器设计的LMI方法

应用线性矩阵不等式（LMI）方法研究T-S模糊系统的H2／H∞混合控制器的设计问题．首先针对T-S模糊系统分别设计H2和H∞控制器;然后以线性矩阵不等式的形式给出T-S模糊系统H2／H∞混合控制器存在的充分条件及相应的控制器设计方法．在给定的H∞干扰约束下,通过优化H2控制性能指标实现了模糊状态反馈次优控制．最后通过例子验证了所给出的H2／H∞混合控制器设计方法的可行性和有效性．     

基于事件触发的网络化T-S模糊系统容错控制

研究了基于事件触发的网络化T-S模糊系统容错控制问题．首先针对一类具有随机执行器故障的网络化T-S模糊系统,提出一种有效减少数据传输量的事件触发机制．然后在综合考虑事件触发机制和控制器与T-S系统前件变量的异步的情况下,建立一种能同时描述事件传送策略、执行器失效、网络诱导时延和异步前件变量的新颖模型．利用李亚普诺夫泛函方法,得到保守性较小的闭环T-S系统均方渐近稳定条件和相应的容错控制器设计方法．实例表明了本文所得结果的有效性．     

执行器故障和未知控制方向系统的自适应模糊学习控制

在工业生产中,工业机器人等设备在重复运动中容易出现执行器故障,进而降低生产效率。另外,考虑到很多实际系统无法提前预知控制方向,因此,面向执行器故障和未知控制方向系统,提出了一种自适应模糊迭代学习控制(iterative learning control, ILC)算法。首先,使用模糊逻辑系统(fuzzy logic system, FLS)估计期望的控制信号,并设计额外的自适应项来补偿执行器故障和系统未知函数带来的副作用。其次,考虑到系统的控制方向是未知的,采用离散Nussbaum型函数在迭代方向对其进行辨识,并将该函数应用于自适应模糊ILC算法。最后,通过Lyapunov-like函数证明了所提自适应模糊ILC算法的可行性：当迭代次数趋于无穷大时,除t∈{0,1,…,m-1}时刻之外的ILC跟踪误差可收敛到一个可调界内,且所有系统信号保持有界。仿真结果验证了所提方法的可行性和有效性。     

执行器饱和T-S模糊系统的鲁棒耗散容错控制

研究了一类执行器饱和状态变时滞T-S模糊系统的鲁棒容错控制问题. 通过时滞相关Lyapunov函数和对状态的椭球域约束, 基于线性矩阵不等式技术, 提出了非线性系统稳定的不变集条件和模糊鲁棒耗散容错控制器存在的充分条件. 控制方案的设计结果不仅为执行器饱和状态变时滞T-S模糊系统的无源控制和H1鲁棒控制建立了统一框架, 而且保证了闭环控制系统对执行器故障的稳定性和容错性. 最后以时滞倒车系统的控制仿真验证了方法 的有效性.     

基于聚类的模糊柴油机故障诊断

在柴油机系统故障诊断背景问题的研究中,针对系统的安全准确预测故障类型,提出了一种从柴油机故障历史数据样本中提取模糊规则的方法,将隐含于样本中的专家知识转化为更易于理解的模糊规则,并以此建立模糊故障分类器和模糊故障诊断系统.先利用减法聚类获得故障数据中具有代表性的样本,以样本为基础,生成模糊规则,进行优化后,通过规则综合...     

四旋翼无人机时延模糊自抗扰容错控制

针对四旋翼无人机系统执行器故障问题，为改善飞行控制系统性能，提出一种时延模糊自抗扰容错控制。首先，根据四旋翼无人机系统非线性数学模型和执行器故障模型，选择模糊自抗扰控制器作为基准控制器，在未发生执行器故障的情况下，使飞行控制系统保持稳定；其次，在发生执行器故障的情况下，利用时延控制技术估计故障信息，并与模糊自抗扰控制相结合，实现容错控制；最后，对所研究的容错控制算法进行数值仿真分析，仿真结果表明：把时延控制与模糊自抗扰控制相结合，能有效调节执行器故障，使飞行控制系统对故障产生的干扰具有良好的鲁棒性。     

Fault accommodation for nonlinear systems using fuzzy adaptive sliding control

An active fault accommodation control law is developed for a class of nonlinear systems to guarantee the closed-loop stability in the presence of a fault, based on a fuzzy logic system representation of the dynamics due to faults. It uses fuzzy logic system to approximate the dynamic caused by the fault. Through the adaptive process of the parameters, the dynamics caused by the fault is counteracted. The fuzzy sliding mode control is introduced to attenuate the fuzzy approximation error. Simultaneity, the closed-loop system is stable in Lyapunov sense and the tracking error converges to a neighbourhood of zero. The example of the proposed design indicates that the fault accommodation control law is effective for a nonlinear system.     

Observer-based fuzzy adaptive fault control for a class of MIMO nonlinear systems

In this paper, the fault-tolerant control (FTC) problem is investigated for a class of multi-input multiple output nonlinear systems with time-varying delays, and an active FTC method is proposed. The controlled system contains unknown nonlinear functions, unknown control gain functions and actuator faults, which integrates time-varying bias and gain faults. Then, fuzzy logic systems are used to approximate the unknown nonlinear functions and unknown control gain functions, fuzzy adaptive observers are used for fault detection and isolation. Further, based on the obtained information, an accommodation method is proposed for compensating the actuator faults. It is shown that all the variables of the closed-loop system are semi-globally uniformly bounded, the tracking error converges to an arbitrary small neighbourhood of the origin. A simulation is given to demonstrate the effectiveness of the proposed approach.     

基于模糊逼近的一类不确定非线性系统的容错控制

针对一类不确定非线性系统,提出了一种模糊容错控制方案.采用模糊T-S模型来逼近非线性系统,由线性矩阵不等式设计模糊模型的控制律.构建了模糊逻辑系统作为补偿器来抵消对非线性系统的建模误差和因故障引起的不确定性,并证明了闭环系统能够满足期望的跟踪性能.仿真实例表明了所提出容错控制方案的有效性.     

A fault accommodation control for nonlinear systems

Based on the use of neural networks for representation of the dynamics of faults, an active fault accommodation control law is proposed that guarantees the closed-loop stability for a class of nonlinear systems with faults. An example of using the control design proposed demonstrates the efficiency of this law for a typical nonlinear system. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 10–18, January–February 2006.     

Adaptive actuator fault compensation for linear systems with matching and unmatching uncertainties

The problem of process systems subject to actuator faults (partial loss of actuator effectiveness) is considered. An active fault compensation control law is designed that utilizes compensation in a way that accounts for matching and unmatching uncertainties and the occurrence of actuator faults. The main idea is designing the robust compensation controller to guarantee closed-loop stability in the presence of faults, based on a neural network representation of the fault dynamics. Changes in the system due to faults are modeled as unknown nonlinear functions. The updating control law is derived such that all the parameters of the closed-loop system are bounded. An output feedback controller is used to the “healthy” system and the adaptive feedback controller is used to compensate for the effect of the dynamics caused by the fault. The advantage of fault compensation is the dynamics caused by faults can be accommodated online. The proposed design method is illustrated on a three-tank system.     

Fault Accommodation for a Class of Nonlinear Uncertain Systems With Event-Triggered Input

The event-triggered fault accommodation problem for a class of nonlinear uncertain systems is considered in this paper.The control signal transmission from the controller to the system is determined by an event-triggering scheme with relative and constant triggering thresholds.Considering the event-induced control input error and system fault threat,a novel eventtriggered active fault accommodation scheme is designed,which consists of an event-triggered nominal controller for the time period before detecting the occurrence of faults and an adaptive approximation based event-triggered fault accommodation scheme for handling the unknown faults after detecting the occurrence of faults.The closed-loop stability and inter-event time of the proposed fault accommodation scheme are rigorously analyzed.Special cases for the fault accommodation design under constant triggering threshold are also derived.An example is employed to illustrate the effectiveness of the proposed fault accommodation scheme.     

张恩勤,施颂椒,徐立鸿

针对一类不确定非线性系统提出一种新的模糊自适应控制方法。用模糊逻辑系统逼近未知函数,并根据前一步参考误差来修正模糊逻辑系统的输入,以此对逼近误差进行补偿。该方法不但能保证闭环系统稳定,而且可使跟踪误差收敛于原点或原点的一个小领域内。仿真结果验证了此方法的有效性。     

Fault-tolerant control of nonlinear system

The design strategies of fault-tolerant control system (FTCS) are developed, which are categorized into two types: redundant design and fault compensation. In the first type, a certain degree of redundancy is introduced to controller. The resulting closed-loop system is stable not only when all actuators are operational but also only when one actuator experiences fault. In the second type, the online fault-tolerant control (FTC) scheme is developed based on the fuzzy logic system. The closed-loop stability is established based on Lyapunov’s sense. The resulting closed-loop system is stable by using the corrective control law. Compared with the existing results, the fault is accommodated by the fault compensator. The updating control law is so derived that all the parameters of the closed-loop system are bounded. The advantage of redundant design is that it is unnecessary to know the position and magnitude of the fault and is performed without FDI, which reduce the computing time and avoid the false alarms, non-detection and delay due to FDI. The advantage of fault compensation is the dynamics caused by faults that can be accommodated online. Examples of the proposed design indicate that the approaches are effective.     

连续搅拌反应釜的固定时间命令滤波跟踪控制

针对一类连续搅拌反应釜系统的跟踪控制问题,提出一种基于反步法和模糊逻辑系统的自适应固定时间命令滤波控制方法.利用命令滤波器引入误差补偿机制消除滤波误差的影响,并解决反步法虚拟控制信号重复求导的问题;采用模糊逻辑系统对系统中存在的非线性部分进行逼近;利用固定时间控制方法使系统跟踪误差更迅速收敛至较小邻域内,且收敛时间不依赖系统初始状态;通过Lyapunov定理证明连续搅拌反应釜系统的闭环稳定性;利用Matlab/Simulink仿真实验验证所提出控制方法的有效性.与现有控制方法相比,该控制方法具有控制器结构简单、收敛速度快、控制精度高、无超调等优点.     

Fault accommodation of a class of multivariable nonlinear dynamicalsystems using a learning approach

Presents a learning approach for accommodating faults occurring in a class of nonlinear multi-input-multi-output (MIMO) dynamical systems. Changes in the system dynamics due to a fault are modeled as unknown nonlinear functions of the measurable state variables. The closed-loop stability of the robust fault accommodation scheme is established using Lyapunov redesign methods. A simulation example, based on a model of a jet engine compression system, is used to illustrate the fault accommodation design procedure