可逆冷带轧机速度张力多变量耦合系统的建模及分散控制

针对具有多变量、非线性、强耦合和不确定性的可逆冷带轧机速度张力系统,提出了一种基于扩张状态观测器(extended state observer,ESO)的全局积分滑模自适应反步分散控制方法.首先,采用机理建模方法,建立了相对完备的可逆冷带轧机速度张力多变量耦合系统的数学模型.其次,将各子系统的耦合项和不确定项看成外扰,通过构造的ESO对其进行动态观测,并分别引入所设计的全局积分滑模自适应反步控制器中进行补偿,速度张力系统实现了有效的动态解耦和协调控制.理论分析表明,所提出的控制方法能够保证滑模面的渐近稳定和闭环系统的渐近跟踪性能.最后,基于某1422mm可逆冷带轧机速度张力系统的实际数据进行仿真,结果验证了所提方法的有效性.     

非仿射非线性离散系统的数据驱动二阶滑模解耦控制

针对传统二阶离散滑模变结构控制方法很难应用于模型未知系统的问题,提出了一种数据驱动二阶滑模解耦控制算法.该控制算法采用数据驱动的策略,运用系统的I/O数据,实时计算二阶离散滑模控制(2–DSMC)律.同时,运用观测器的思想,在控制器设计中引入离散扩张状态观测器(DESO),在线估计系统各回路间耦合、不确定性和外部扰动,进一步实现系统的解耦,改善控制品质.最后的理论分析和仿真结果表明,所提出的方法对于一般带有扰动和不确定性的非仿射非线性离散多入多出(MIMO)系统具有较好的解耦效果、渐进收敛的稳定性和较强的鲁棒性.     

参数优化配置的广义奇异摄动弹性飞机模型降阶研究

推导了广义奇异摄动法的降阶方法,介绍了其在飞机模型降阶应用中的优点,针对算法中出现的参数ξ进行了分析,以弹性飞机模型为平台提出了ξ的优化配置并进行了仿真。结果表明,采用该参数配置的广义奇异摄动模型降阶方法可以用于弹性飞机模型降阶。     

面向聚类的平面反射数据扰动方法

面向聚类的数据隐藏通常使用数据扰动技术防止敏感信息泄露。针对现有的面向聚类的数据扰动方法隐私保护度低的问题,提出一种基于平面反射的数据扰动方法,将发布对象的全部属性两两配对构成平面上的点,再随机选择一条直线,作每对属性关于直线的对称点,转换后的数据即为发布的数据。实验结果表明,这种方法具有较好的隐私保护度和聚类可用性,且对高维数据有良好的适应性。     

一类非线性随机时滞系统的故障诊断

针对一类非线性随机时滞系统提出了一种新的故障检测算法,该方法不同于传统的故障检测方法,是通过构建一种带有Consensus滤波器的故障诊断滤波器的方法来进行故障诊断.首先采用一组传感器测量系统实际输出,然后根据传感器的测量值构建一组残差生成器,将每个残差生成器看作一个小世界网络模型中的一个节点,采用动态Consensus算法计算出残差生成器的残差,并根据残差来判断系统是否有故障发生.仿真结果表明了本文所提出方法的可行性和有效性.     

Circle-criterion Based Nonlinear Observer Design for Sensorless Induction Motor Control

This paper deals with the design of a nonlinear observer for sensorless induction motor control. Based upon the circle criterion approach, a nonlinear observer is designed to estimate pertinent but unmeasurable state variables of the considered induction machine for sensorless control purpose. The observer gain matrices are computed as a solution of linear matrix inequalities(LMI) that ensure the stability conditions of the state observer error dynamics in the sense of Lyapunov concepts. Measured and estimated state variables can be exploited to perform a state feedback control of the machine system. The simulation results are presented to illustrate the effectiveness of the proposed approach for nonlinear observer design.     

Robust Unknown Input Observer Design for Linear Uncertain Time Delay Systems with Application to Fault Detection

In this paper, a novel approach is proposed to design a robust fault detection observer for uncertain linear time delay systems. The system is composed of both norm‐bounded uncertainties and exogenous signals (noise, disturbance, and fault) which are considered to be unknown. The main contribution of this paper is to present unknown input observer (UIO)‐based fault detection system which shows the maximum sensitivity to fault signals and the minimum sensitivity to other signals. Since the system contains uncertainty terms, an H_∞ model‐matching approach is used in design procedure. The reference residual signal generator system is designed so that the fault signal has maximum sensitivity while the exogenous signals have minimum sensitivity on the residual signal. Then, the fault detection system is designed by minimizing the estimation error between the reference residual signal and the UIO residual signal in the sense of H_∞ norm. A sufficient condition for the existence of such a filter is exploited in terms of certain linear matrix inequalities (LMIs). Application of the proposed method in a numerical example and an engineering process are simulated to demonstrate the effectiveness of the proposed algorithm. Simulation results show the validity of the proposed approach to detect the occurrence of faults in the presence of modeling errors, disturbances, and noise.     

On the Design of Observer for Nonlinear Time‐Delay Systems

This paper suggests a new method to design observers in a class of nonlinear time‐delay systems with delays in system states. The method is based on an extension of the well‐known state‐dependent Riccati equation (SDRE) technique. The conditions for locally asymptotic stability of the proposed observer are investigated. Some numerical simulations are provided to show the design procedure and the flexibility of the proposed observer.     

An Adaptive and Optimized Switching Observer for Sensorless Control of an Electromagnetic Valve Actuator in Camless Internal Combustion Engines

In this paper, the design and operation of a special electromagnetic actuator as a variable engine valve actuator are presented. Further, this paper describes a feasible approximated velocity switching estimator based on measurements of current and input voltage to achieve sensorless control. The proposed concept allows a reduced‐order observer to be conceived and yields a specific control strategy with an acceptable performance. In general, this approach represents a viable strategy to build reduced‐order observers for estimating the velocity of systems through the measurement of input current and voltage. The robustness of the velocity tracking is explored using a minimum variance approach. The effect of the noise is minimized, and the position can be achieved through an adaptive and optimized structure by combining this particular velocity estimator and an observer based on the electromechanical system. Position control is achieved through an inversion of the model. This approach avoids a more complex structure for the observer and yields an acceptable performance as well as eliminating bulky position‐sensor systems. In addition, a control strategy is presented and discussed. Computer simulations of the sensorless control structure are presented in which the positive effects of the observer with optimized parameter setting are visible in the closed‐loop control.     

基于梯度投影法与随机优化算法的约束优化方法

针对带有线性等式和不等式约束的无确定函数形式的约束优化问题,提出一种利用梯度投影法与遗传算法、同时扰动随机逼近等随机算法相结合的优化方法。该方法利用遗传算法进行全局搜索,利用同时扰动随机逼近算法进行局部搜索,算法在每次进化时根据线性约束计算父个体处的梯度投影方向,以产生新个体,从而能够严格保证新个体满足全部约束条件。将上述约束优化算法应用于典型约束优化问题,其仿真结果表明了所提出算法的可行性和收敛性。