柔性臂杆、柔性关节空间机械臂TS模糊轨迹跟踪及双柔振动并行综合控制

针对存在参数不确定和外界干扰的柔性臂杆、柔性关节空间机械臂追踪期望运动的问题,设计了基于TS模糊模型的滑模鲁棒控制方案和双柔性振动并行控制方案。首先,设计了关节柔性补偿器以提高系统的等效关节刚度。其次,利用反馈线性化技术建立了系统追踪期望轨迹的误差动力学方程,通过对系统Lyapunov稳定性证明来选择滑模控制参数;简化并改进TS模糊推理规则,提出了模糊滑模鲁棒控制方法,可解决滑模控制的抖振问题并具有计算量少、控制力矩小的优点。再次,提出了柔性臂杆振动模态的直接反馈控制方案,解决了双柔性并行综合控制的问题。最后,运用逐步仿真的方法,对比仿真结果,证实了所设计轨迹跟踪、双柔性并行综合控制方案的有效性和稳定性。     

H∞方法在振动主动鲁棒控制中的应用

研究了振动系统频域不确定和参数不确定两种情形的Ｈ∞鲁棒控制设计问题,文中对参数不确定情形提出了结构摄动鲁棒稳定与灵敏度函数设计相结合的设计方法。对一个实例的数值仿真结果证实了所提方法的有效性,并且表明Ｈ∞方法能够较满意地处理振动控制中的确定性,因而在振动主动鲁棒控制设计中有着较大的应用潜力。     

基于事件触发和扩展状态观测器的液压位置跟踪系统控制研究

基于网络控制技术的液压控制系统具有远程控制、模块化、资源共享等优点。然而，液压控制系统本身具有强非线性和参数不确定性等特点，结合网络控制系统具有的通信带宽受限等问题，导致控制效果不好而限制了应用。针对以上问题，提出一种具有事件触发机制和扩展状态观测器(Extended state observer, ESO)的自适应鲁棒控制策略。通过引入事件触发机制过滤大量的冗余数据，提高通信带宽的利用率。基于模型设计出一种扩展状态观测器，同时对速度值和不匹配外干扰进行估计。通过自适应算法在线估计液压控制系统的不确定参数。通过Lyapunov稳定性理论分析闭环系统的全局稳定性。试验表明所设计的算法在减少了大量数据传输量的同时，具有良好的位置跟踪控制性能。     

一种双滑模观测器的异步电机转矩闭环控制方法研究

为了提高异步电机的转矩控制精度,提出了一种基于双滑模观测器的异步电机转矩闭环控制方法。首先构建了一种反电动势滑模观测器的数学模型,该模型实现了反电动势的观测;同时,设计了一种磁链滑模观测器并采用数学模型表达,实现了磁链观测。然后,根据李雅普诺夫稳定性理论分析了所设计的滑模观测器的稳定性,并进一步研究了所设计的观测器的参数鲁棒性。然后对其进行仿真研究,其仿真表明,所设计的磁链观测方法和转矩闭环控制系统具有较强的参数鲁棒性,能够为异步电机的工程应用提供一定参考。     

应用证据理论的三缸发动机悬置系统设计及稳定性分析

针对基于不确定性参数条件下三缸发动机悬置系统不满足稳健性设计要求问题,提出了一种基于证据理论的悬置系统优化及稳定性分析方法.在考虑了悬置系统参数不确定性的条件下,首先基于证据理论原理并结合遗传算法,对悬置系统参数进行优化设计.然后分析优化后的参数在不确定性条件下悬置系统满足稳定性设计要求的概率累计分布曲线.最后,在不确定参数区间存在波动时验证优化参数的最优性.     

应用证据理论的三缸发动机悬置系统设计及稳定性分析

针对基于不确定性参数条件下三缸发动机悬置系统不满足稳健性设计要求问题,提出了一种基于证据理论的悬置系统优化及稳定性分析方法.在考虑了悬置系统参数不确定性的条件下,首先基于证据理论原理并结合遗传算法,对悬置系统参数进行优化设计.然后分析优化后的参数在不确定性条件下悬置系统满足稳定性设计要求的概率累计分布曲线.最后,在不确定参数区间存在波动时验证优化参数的最优性.     

X-Y定位平台自适应神经网络的摩擦补偿控制

针对X-Y定位平台中摩擦等非线性部分对控制精度的影响问题,提出了基于自适应神经网络的鲁棒控制策略。设计神经网络控制器对摩擦及干扰等不确定部分进行补偿,其网络逼近误差作为外界扰动通过鲁棒控制器消除,保证X-Y平台的定位精度;设计神经网络参数学习算法,保证权值的在线自适应实时调整。基于H∞的HJI理论证明了控制系统的稳定性,并保证了系统L2增益小于给定的指标。试验结果表明所提控制方法能够很好补偿摩擦模型,提高了定位精度,具有重要工程应用价值。     

电液位置伺服系统的自适应滑模鲁棒跟踪控制

针对存在参数不确定性的电液位置伺服系统的跟踪控制问题，基于滑模控制理论，提出了一种具有参数自适应能力的自适应滑模控制方法。通过自适应方法，来消除参数不确定性对系统控制性能的影响，进而实现鲁棒控制。基于李雅普诺夫稳定性理论证明了自适应滑模控制系统的渐近稳定性。将该方法应用于某疲劳试验机电液伺服系统的跟踪控制，仿真和实时控制结果证明了该方法的有效性。     

四旋翼飞行器非线性轨迹跟踪控制

针对四旋翼飞行器在复杂飞行条件下速度不可测的轨迹跟踪控制问题,考虑系统存在外界未知干扰和模型参数不确定的情况,提出了一种基于扩张观测器的轨迹跟踪控制方法。该方法设计了积分型反步法跟踪控制器,以降低系统的稳态误差,并引入了状态扩张观测器,来估计系统未知速度信息,同时对干扰和模型参数不确定因素进行实时估计并给予补偿;最后,选取李雅普诺夫函数证明了该控制系统的稳定性。以Quanser公司的Qball2四旋翼飞行器为研究对象和飞行实验平台,对所设计的控制器进行验证。实验结果表明,本文所设计的基于扩张观测器的轨迹跟踪控制器,能够有效地估计轨迹跟踪控制过程中的未知速度信息,解决外界未知干扰和模型参数不确定的问题,增强对环境的适应能力,有效提高了飞行器对未知干扰的鲁棒性和轨迹跟踪控制的精确性。     

汽车电子节气门RBF神经网络控制方法

针对汽车电子节气门模型参数不精确和外界干扰等不确定条件下的控制问题,提出了一种RBF神经网络控制方法,解决传动控制方法需要精确建模的问题。首先,对电子节气门的工作特性进行分析,并充分考虑参数不精确和外界干扰等不确定性,建立其数学模型的状态空间表达形式。而后,基于传统滑模控制理论,提出了抗外部干扰的滑模控制方法。进而,利用RBF神经网络对控制器不确定部分进行在线逼近,提出一种局部逼近的神经网络控制方法,并通过Lyapunov方法证明了控制系统的稳定性。最后,基于Matlab/Simulink平台进行对比仿真实验。实验结果表明,所提控制方法能够有效克服外部干扰以及模型参数带来的不确定性,实现电子节气门实际开度对目标开度的精确跟踪。     

Adaptive MRAC-based direct torque control with SVM for sensorless induction motor using adaptive observer

This paper presents an improved direct torque control (DTC) method for induction motor (IM) drive. The main drawback of the conventional DTC is the use of hysteresis comparators which leads to high torque and flux ripples. The improvement in this paper includes using the space vector modulation to preserve a constant switching frequency and to reduce totally flux and torque ripples. Besides, the torque and stator flux regulation will be done based on model reference adaptive control (MRAC) strategy to ensure a robust control against external disturbance and less sensitivity from machine parameter variation unlike the conventional proportional-integral (PI) controllers. Furthermore, a design of an adaptive observer based on Lyapunov stability is presented for speed/flux and load torque estimation. The observer can improve the control performances and decrease the cost and increase reliability of the global control system by reducing the number of sensors. The proposed strategy will be examined under simulation tests using Matlab/Simulink and experimental implementation with real-time interface (RTI) based on dSpace 1104 board.     

ROBUST STABILITY ANALYSIS FOR RAILWAY VEHICLE SYSTEMS

The lateral stability for railway vehicle dynamic system with uncertain parameters and nonlinear uncertain force vector is studied by using the Lyapunov stability theory. A robust stability condition for the considered system is derived, and the obtained stability bounds are not necessarily symmetric with respect to the origin in the parameter space. The lateral stability analysis for a railway bogie model is analyzed by using the proposed approach. The symmetric and asymmetric results are both given and the influence of the adjustable parameter β on the stability bounds is also discussed. With the help of the proposed method, the robust stability analysis can provide a reference for the design of the railway vehicle systems.     

QFT Parameter-Scheduling control design for linear Time-Varying systems based on RBF networks

For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly, by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory (QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter uncertainties. However, if these methods are applied to the approximated linear time-invariant (LTI) plants with large uncertainty, the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper, as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks.     

Research on the effects of coordinate deformation on radial-axial ring rolling process by FE simulation based on in-process control

The boundary layer approach is the most popular method to reduce the chattering phenomenon in sliding mode control (SMC) for uncertain nonlinear systems. This paper applies the fuzzy sliding mode structure based on the boundary layer theory which is used as speed controller of an indirect field-oriented control (IFOC) of an induction motor (IM) drive. A fuzzy inference system is assigned for reaching the controller part of the fuzzy sliding mode controller (FSMC) to eliminate the chattering phenomenon in spite of the small and large uncertainties in the system. The applied fuzzy system acts like a saturation function technique in a thin boundary layer near the sliding surface so that the stability of the system is guaranteed. Also, the equivalent control part is estimated to avoid the computational burden by an averaging filter. On the other hand, the averaging filter assists to improve the tracking performance despite the possibility of large uncertainties in the system so that the stability of the system is guaranteed. The main advantages of the proposed chattering-free speed controller are robustness to parameter variations and external load disturbance. The simulation results are shown to verify the effectiveness of the proposed speed controller, and its advantages are shown in comparison with the FSMC system and the conventional SMC.     

具有状态约束的电液伺服系统模型参考鲁棒自适应控制

针对电液伺服系统中的模型不确定性和状态约束问题,设计了一种模型参考鲁棒自适应控制(MRRAC)方法。将电液伺服系统的近似模型作为模型预测控制(MPC)的设计对象,在设计过程中考虑状态约束,并生成受约束的状态期望,作为后续伺服控制方法的参考指令。为了克服液压系统中的模型不确定性,基于反步法设计了鲁棒自适应控制器(RAC),实现了兼顾模型不确定性和状态约束的伺服控制。基于Lyapunov稳定性理论证明了所设计控制策略的闭环渐近稳定性,且系统所有信号均有界。仿真结果表明,控制器对于系统模型不确定性具有较强的鲁棒性,且可实现对指定状态的有效约束,充分验证了该控制策略的有效性。     

Identification of uncertain nonlinear systems for robust fuzzy control

In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi-Sugeno (T-S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe the nominal model and the uncertainty in the nonlinear system respectively. The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices. It has been observed that our method yields less conservative results than the other existing method proposed by S?krjanc et al. (2005) [11] and [12]. With the obtained fuzzy model, we showed the robust stability condition which provides a basis for different robust fuzzy control design. Finally, different simulation examples are presented for identification and control of uncertain nonlinear systems to illustrate the utility of our proposed identification method for robust fuzzy control.     

A novel sliding-mode control of induction motor using space vector modulation technique

This paper presents a novel sliding-mode control method for torque control of induction motors. The control principle is based on sliding-mode control combined with space vector modulation technique. The sliding-mode control contributes to the robustness of induction motor drives, and the space vector modulation improves the torque, flux, and current steady-state performance by reducing the ripple. The Lyapunov direct method is used to ensure the reaching and sustaining of sliding mode and stability of the control system. The performance of the proposed system is compared with those of conventional sliding-mode controller and classical PI controller. Finally, computer simulation results show that the proposed control scheme provides robust dynamic characteristics with low torque ripple.     

基于无速度传感器异步电机的风力机模拟研究

风力机模拟系统使在实验室内开展风力发电技术的各项研究成为可能。分析了风力机特性,建立了风力机模型。通过对异步电机间接磁场定向矢量控制技术的研究,考虑到安装速度传感器具有诸多缺陷,提出基于模型参考自适应（MRAS）转速辨识理论的无速度传感器异步电机的风力机模拟控制方法,并且考虑到转子时间常数对矢量控制系统的影响,采用同时辨识电机转速和转子时间常数,使系统辨识转速同时,对电机参数变化具有较强的鲁棒性。利用MATLAB/SIMULINK搭建了基于无速度传感器异步电机的风力机模拟系统,通过对风力机特性,最大风能捕获和电机参数对矢量控制系统影响的仿真,证明了系统的可行性。     

Adaptive output feedback tracking of nonlinear systems with uncertain nonsymmetric dead-zone input

In this paper, the problem of adaptive practical tracking is investigated by output feedback for a class of uncertain nonlinear systems subject to nonsymmetric dead-zone input nonlinearity with parameters of dead-zone being unknown. Instead of constructing the inverse of dead-zone nonlinearity, an adaptive robust control scheme is developed by designing an output compensator including two dynamic gains based respectively on identification and non-identification mechanism. With the aid of dynamic high-gain scaling approach and Backstepping method, stability analysis of the closed-loop system is proceeded using non-separation principle, which shows that the proposed controller guarantees that all closed-loop signal is bounded while the output of system tracks a broad class of bounded reference trajectories by arbitrarily small error prescribed previously. Finally, two examples are given to illustrate our controller effective.     

漂浮基柔性空间机械臂协调运动的非线性鲁棒自适应控制

针对具有外部扰动与参数不确定或未知的情况,讨论漂浮基柔性空间机械臂系统的协调控制与柔性振动抑制问题。基于假设模态法对柔性臂杆进行近似描述,并利用第二类拉格朗日方程与系统动量守恒关系,推导带外部扰动的漂浮基柔性空间机械臂系统的动力学方程。以此为基础,提出漂浮基柔性空间机械臂系统协调运动的非线性鲁棒控制与非线性鲁棒自适应控制方案。此两种控制方案均可克服外部扰动对系统的影响,控制漂浮基柔性空间机械臂系统载体姿态与机械臂各关节铰完成期望的协调运动,同时有效地抑制了臂杆的柔性振动。除此之外,非线性鲁棒自适应控制方案还可以解决系统惯性参数不确定或未知的问题。系统数值仿真结果证实了所提控制方案的有效性和可行性。