基于滑模观测器的永磁同步电机变结构鲁棒控制

提出一种由一个变结构控制器和一个滑模观测器组成的控制系统,用于永磁同步电机的无传感器鲁棒控制.首先利用Lyapunov稳定性原理分析得到观测器的收敛条件及自适应率,并证明了其稳定性;然后以转速误差为参量建立滑模面,构造出变结构速度控制器,推导出自适应速度控制律,并得到速度控制的参考电流和参考电压.该方案的控制性能不依赖于电机参数和干扰变化,具有较强的鲁棒性.仿真结果验证了该方案的有效性与正确性.

     

基于滑模与自适应观测器的感应电机非线性控制新策略

提出一种结合滑模变结构和自适应观测技术的感应电机非线性控制新方法. 以定子电流与定子磁链为状态变量建立感应电机模型, 采用非线性分析方法建立转矩与磁链误差方程, 使用自适应滑模技术设计转矩与磁链控制器, 推导出定子电压控制量. 基于模型参考技术设计自适应观测器, 向控制器提供准确的转速辨识与磁链观测值,并给出了控制系统的稳定性证明. 该方法具有转矩脉动小、定子磁链畸变不明显的优点, 低速时也具有良好的控制性能, 且对参数与负载变化有较强的鲁棒性. 仿真与实验结果证明了该控制策略的正确性与有效性.     

改进滑模模型参考自适应的PMSM无传感控制

针对MRAS（模型参考自适应）观测器对PMSM（永磁同步电机）参数变化和外部干扰敏感的缺点,设计了一种用于PMSM无传感控制的软开关滑模模型参考自适应观测器。该观测器将滑模控制与MRAS相结合,并构造了边界层可变的正弦饱和函数,以抑制由于滑模控制引起的系统抖动,增强系统鲁棒性。同时引入sigmoid函数,以提高滑模软切换速度控制器的稳定性。实验仿真结果表明,软开关滑模模型参考自适应控制不仅可以实现边界层内的快速收敛、弱化抖动,而且跟踪能力强。     

永磁同步电动机无速度传感器矢量调速系统的积分反步控制

基于永磁同步电动机(PMSM)的数学模型, 设计了由积分反步控制和滑模变结构模型参考自适应系统组成的无速度传感器矢量控制系统. 其中带有积分作用的反步控制作为矢量系统的速度和电流控制器, 实现给定速度和电流的无静差跟踪; 而滑模变结构模型参考自适应方法作为速度辨识器估计电机速度, 能够快速准确的跟踪实际速度. 通过Lyapunov定理证明了所设计的速度控制器和辨识器的稳定性. 仿真结果验证了所设计的无速度传感器矢量调速系统良好的速度跟踪性能和抗扰动性能.     

自适应模糊滑模软切换的PMSM无速度传感器鲁棒无源控制

针对永磁同步电机(PMSM)转速调节和估计问题,提出一种无速度传感器的PMSM调速系统.利用双曲正切函数代替符号函数,设计了自适应模糊滑模软切换控制器,实现了软切换连续控制,削弱了抖动现象.通过设计鲁棒无源控制器,得到了旋转坐标系下的u_d和u_q.建立了自适应滑模观测器,并给出了速度辨识律,观测器的增益通过求解线性矩阵不等式得到.仿真结果表明了该控制策略与观测器配合的有效性,且控制系统具有良好的动、稳态性能.     

神经网络自适应滑模控制的不确定机器人轨迹跟踪控制

提出一种针对机器人跟踪控制的神经网络自适应滑模控制策略。该控制方案将神经网络的非线性映射能力与滑模变结构和自适应控制相结合。对于机器人中不确定项,通过RBF网络分别进行自适应补偿,并通过滑模变结构控制器和自适应控制器消除逼近误差。同时基于Lyapunov理论保证机器手轨迹跟踪误差渐进收敛于零。仿真结果表明了该方法的优越性和有效性。     

基于双滑模变结构MRAS的PMSM矢量控制研究

永磁同步电机(PMSM)传统的模型参考自适应系统(MRAS)存在负载扰动、响应速度慢、跟踪精度差等问题.针对上述问题,提出了一种双滑模变结构的MRAS方法.通过把传统MRAS观测器中的PI环节和PI速度调节器用滑模变结构控制器代替,提高了系统的抗干扰能力,采用Sigmoid连续函数代替滑模变结构控制中的符号函数,削弱了...     

基于改进型非线性干扰观测器的爬壁机器人轨迹跟踪

针对爬壁机器人建模不准确及容易受外部扰动的影响造成位置及姿态误差的问题,提出了一种基于改进型非线性干扰观测器的轨迹跟踪控制方案.首先通过反演控制设计了一个运动学控制器为机器人动力学控制提供参考质心速度与角速度.其次应用改进型非线性扰动观测器作为前馈控制对建模误差及外部扰动进行估计,并保证扰动误差以指数形式收敛.最后针对引入干扰观测器的动力学模型设计了滑模控制器.该方案对外界干扰进行了快速补偿,并通过Lyapunov定理证明了其稳定性.仿真结果表明该控制方法对于克服建模误差及外界干扰具有较好的效果.     

基于滑模模型参考自适应观测器的无速度传感器三相永磁同步电机模型预测转矩控制

针对三相永磁同步电机(PMSM)驱动系统,基于滑模变结构模型参考自适应(MRAS)技术,提出了一种新颖的无速度传感器模型预测转矩控制(MPTC)策略.采用滑模变结构模型参考自适应方法构造电机转速观测器,以改善速度估计精度并提高系统鲁棒性;利用模型预测转矩控制策略,以达到减小转矩和磁链纹波并提高系统控制性能的目的.仿真结果表明:就滑模MRAS观测器与MRAS观测器比较而言,基于前者的PMSM无速度传感器MPTC系统比基于后者的PMSM无速度传感器MPTC系统具有较强的鲁棒性和更好的动态性能;就MPTC与直接转矩控制(DTC)和磁场定向控制(FOC)比较而言,采用前者策略的无速度传感器电机驱动系统能够降低逆变器开关频率、减少相电流总谐波失真(THD),从而提高系统可靠性.     

非线性系统的反演自适应动态滑模控制

为削弱非线性系统中由滑模控制引起的抖振现象,提出自适应动态滑模控制方案.动态滑模方法是通过设计新的切换函数或将常规滑模变结构控制中的切换函数s通过微分环节构成新的切换函数,该切换函数与系统控制输入的一阶或高阶导数有关,可将不连续项转移到控制的一阶或高阶导数中去,得到在时间上本质连续的动态滑模控制律.该方案利用自适应技术和反演法,设计动态滑模控制器,有效地削弱了系统的抖振.最后仿真结果证明了该方案是正确的.     

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.     

Robust adaptive backstepping control for a class of uncertain nonlinear systems based on disturbance observers

In this paper, a novel robust adaptive control scheme for a class of uncertain nonlinear systems is proposed using disturbance observer and backstepping method.Firstly, a disturbance observer is developed using radial basis function(RBF) neural network.The parameter updated law of the RBF neural network is given for monitoring subsystem disturbance well.The robust adaptive control scheme is then presented with backstepping method based on the designed disturbance observer.Semiglobal uniform ultimate bounded...     

Robust Tracking Control for Self-balancing Mobile Robots Using Disturbance Observer

In this paper, a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances. A desired velocity control law is firstly designed using the Lyapunov analysis method and the arctan function. To improve the tracking control performance, a nonlinear disturbance observer is developed to estimate the unknown disturbance of the self-balancing mobile robot. Using the output of the designed disturbance observer, the robust tracking control scheme is presented employing the sliding mode method for the selfbalancing mobile robot. Numerical simulation results further demonstrate the effectiveness of the proposed robust tracking control scheme for the self-balancing mobile robot subject to external unknown disturbances.      

An extended observer-based robust nonlinear speed sensorless controller for a PMSM

This work focuses on the problem of observer-based robust speed sensorless control of a 3-phase permanent magnet synchronous motor (PMSM). Nonlinear design techniques are employed for designing robust speed controller and observer that are able to withstand the effects of modelling uncertainties and load variations. A new cascaded observer scheme is proposed comprising a continuous sliding mode observer (SMO) and an extended high-gain observer (EHGO). The proposed cascaded observer reduces chattering, exhibits reasonable insensitivity to modelling inaccuracies and is capable of withstanding errors due to the finite boundary layer of continuous SMO. For the robust speed control, an integral sliding mode controller is designed that yields fast and accurate speed tracking performance even in the presence of bounded uncertainties and external disturbances. The complete scheme has been evaluated using simulations and experiments.     

Robust moving horizon estimation based output feedback economic model predictive control

In this work, we develop an economic model predictive control scheme for a class of nonlinear systems with bounded process and measurement noise. In order to achieve fast convergence of the state estimates to the actual system state as well as the robustness of the observer to measurement and process noise, a deterministic (high-gain) observer is first applied for a small time period with continuous output measurements to drive the estimation error to a small value; after this initial small time period, a robust moving horizon estimation scheme is used on-line to provide more accurate and smoother state estimates. In the design of the robust moving horizon estimation scheme, the deterministic observer is used to calculate reference estimates and confidence regions that contain the actual system state. Within the confidence regions, the moving horizon estimation scheme is allowed to optimize its estimates. The output feedback economic model predictive controller is designed via Lyapunov techniques based on state estimates provided by the deterministic observer and the moving horizon estimation scheme. The stability of the closed-loop system is analyzed rigorously and conditions that ensure the closed-loop stability are derived. Extensive simulations based on a chemical process example illustrate the effectiveness of the proposed approach.     

A Robust Backstepping Sensorless Control for Interior Permanent Magnet Synchronous Motor Using a Super‐Twisting Based Torque Observer

In order to achieve high‐performance speed regulation for sensorless interior permanent magnet synchronous motors (IPMSMS), a robust backstepping sensorless control is presented in this paper. Firstly, instead of a real mechanical sensor, a robust terminal sliding mode observer is used to provide the rotor position. Then, a new super‐twisting algorithm (STA) based observer is designed to obtain estimates of load torque and speed. The proposed observer ensures finite‐time convergence, maintains robust to uncertainties, and eliminates the common assumption of constant or piece‐wise constant load torque. Finally, a sensorless scheme is designed to realize speed control despite parameter uncertainties, by combining the robust backstepping control with sliding mode actions and the presented sliding mode observers. The stability of the observer and controller are verified by using Lyapunov's second method to determine the design gains. Simulation results show the effectiveness of the proposed approach.     

Model reference resilient control for the helicopter with time‐varying disturbance

In this paper, the problem of model reference resilient control is investigated for the helicopter system with the time‐varying disturbance and unmeasurable states. Firstly, a disturbance observer and a state observer are built to estimate the time‐varying disturbance and unmeasurable states. Then, combining the methods of model reference control and disturbance observer–based control, the state feedback robust resilient control scheme and the dynamic output feedback robust resilient control method are proposed, respectively. Under the two developed robust resilient control schemes, sufficient conditions are obtained to guarantee that the helicopter system asymptotically tracks the reference model with H_∞ performance. Finally, simulation results are presented to show the effectiveness of the model reference resilient control method.     

High-order sliding mode observers and integral backstepping sensorless control of IPMS motor

This paper presents a robust high-order sliding mode interconnected observer and an integral backstepping controller for a sensorless interior permanent magnet synchronous motor. To limit the chattering phenomenon on the observed state, a super twisting algorithm is combined with an interconnected observer to design a new high-order sliding mode observer which will be used for multiple-input multiple-output systems. The proposed observer is used to estimate in finite time the rotor position, the speed and the stator resistance. Moreover, a robust nonlinear controller based on the backstepping algorithm is designed where integral actions are introduced step by step. This controller allows to track a desired reference which is computed by using a maximum-torque-per-ampere strategy. Simulation results are shown to illustrate the performance of the proposed scheme by using significant trajectories including the zero speed and under parametric uncertainties.     

Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.     

Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model （GFHM）. Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.