基于干扰观测器的解耦控制算法

针对多变量系统之间的耦合问题,设计了一种干扰观测器与PID控制器相结合的多变量解耦控制器。而且干扰观测器可以对实际对象与名义模型之间的差异在控制中进行等量的补偿。用MATLAB软件对一个耦合系统模型进行仿真实验,结果表明加入干扰观测器的控制算法对抑制噪声和其他变量的耦合干扰有显著效果。     

Advanced disturbance observer design for mechanical positioning systems

Disturbance-observer (DOB)-based controller design is one of the most popular methods in the field of motion control. In this paper, the generalized disturbance compensation framework, named the robust internal-loop compensator (RIC) is introduced and an advanced design method of a DOB is proposed based on the RIC. The mixed sensitivity optimization problem, which is the main issue of DOB design, is also solved through the parametrization of the DOB in the RIC framework. Differently from conventional methods, the Q-filter is separated from the mixed sensitivity optimization problem and a systematic design law for the DOB is proposed. This guarantees the robustness and optimality of the DOB and enables the design for unstable plants.     

基于干扰观测器的导弹自动驾驶仪的反演设计

在分析喷流干扰的基础上,建立了含有干扰放大因子的复合控制的弹体模型.针对导弹气动参数的不确定性及外界干扰对导弹控制性能的影响,利用非线性干扰观测器对干扰的逼近特性,结合反演控制设计了非线性导弹自动驾驶仪,并基于Lyapunov方法,给出了整个系统的稳定性证明.仿真结果表明,设计的控制方案不仅提高了系统响应速度,而且能够保证系统具有良好的鲁棒性.     

Adaptive dynamic surface control with sliding mode control and RWNN for robust positioning of a linear motion stage

Ball-screw-driven system provides high precision and long stroke range for positioning and tracking control of a linear stage. Friction and backlash nonlinearities in this system act often the main obstacles for high precision control. It is difficult to achieve effective compensation of these types of nonlinearities by traditional linear control methodology without the aid of a proper compensation schemes. Here, we present an adaptive dynamic surface control scheme combined with sliding mode control to compensate for friction and backlash nonlinearities in a linear stage motion system. The adaptive laws of the recurrent wavelet neural networks and friction estimation are derived to approximate and compensate for the backlash and friction nonlinearities. The boundedness and convergence of the closed-loop system are guaranteed from a Lyapunov stability analysis. The performance of the proposed control scheme was verified through simulations and experiments on the ball-screw-driven linear stage.     

A fuzzy disturbance observer based control approach for a novel 1-DOF micropositioning mechanism

This paper presents the design, analysis, and control of a novel compact, large range 1-DOF micro manipulation mechanism. Leaf flexures were incorporated into a modular multilayer design configuration to achieve large range motion with a high natural frequency. The modular design of the proposed mechanism makes it usable as a building block to construct higher DOF-mechanisms. Computational analysis was conducted to verify the static and dynamic responses of the proposed mechanism and to ensure low flexures stress, high natural frequency, and large workspace. The mathematical model was developed to establish the derivation of a robust observer-based Sliding Mode (SM) controller. To improve the precision of tracking performance, the SM controller was augmented with adaptive Fuzzy Disturbance Observer (SM-FDO). Another robust control technique (H_∞) was implemented in this work to characterize and compare the performance of SM-FDO. The mechanism was fabricated using 3D printing technology and a Voice Coil Motor (VCM) was used to deliver the actuation for its capability to provide large displacements. Experiments were performed to verify the computational modeling of the proposed mechanism and to evaluate the performance of the developed controllers. Several experimental results showed that the adaptive nature of SM-FDO allowed this controller to have superior robustness and tracking performance over the other implemented robust controller.     

基于二阶Adaline网络的位标器自适应逆控制方法

为了提高导引头成像传感器视轴在系统参数时变时的稳定度,对基于二阶Adaline网络的位标器自适应逆控制方法进行了研究。先是对位标器的动力学模型和机电模型进行了数学推导与分析,接着通过对Adaline网络学习算法的研究,提出了一种不易受噪声影响的变步长LMS算法用于增强其学习能力。在最后设计的位标器双闭环控制系统中,电流环采用变速PID控制,速度环利用系统输出误差,按改进的二阶Adaline网络算法来实现其自适应逆控制的调节过程。内场实验表明,与PID控制相比,所提出的方法显著提高了位标器系统的控制精度,具有很强的鲁棒稳定性。     

基于非线性干扰观测器的主动队列管理

针对主动队列管理系统存在UDP流干扰的拥塞问题,本文基于非线性干扰观测器提出了一种主动队列管理算法。采用非线性干扰观测器对UDP流干扰进行估计,从而减小了主动队列管理系统的干扰。然后利用设计的非线性干扰观测器,使用反步滑模方法设计了一种主动队列管理算法。由于观测误差的界未知,设计了一种自适应律来避免必须事先知道观测误差的界。仿真结果表明,该算法对UDP流干扰具有较强的鲁棒性,能使队列长度较好地稳定在期望的队列长度附近。     

基于扰动观测器的机载云台扰动复合补偿方法

针对多旋翼无人机(mUAV)机载云台的扰动补 偿需求,提出一种基于改进的扰动观测器(IDO,improved disturbance observer)的伺服控 制器与减振装 置相结合的复合补偿方法。深入分析了IDO的扰动补偿能力和鲁棒性,构建 了基于IDO的云 台伺服控制结构;依据mUAV机载云台的振动特性,设计出减振装置的结构参数 及安装位置。飞行实验表明, 引入复合补偿方法后,视轴(LOS)指向误差减小到了0.03°,振动隔 离度提高了约15dB。复合补偿方法有效地补偿了机载云 台的扰动,完全满足了mUAV机载云台扰动补偿的需求。     

Robust speed control algorithm with disturbance observer for uncertain PMSM

This article suggests a robust cascade speed control algorithm for a permanent magnet synchronous motor (PMSM) combining the classical feedback linearising (FL) method and the disturbance observers (DOBs) without the integrators. The contributions of this method are twofold. The first one is to provide the simple DOBs for not only guaranteeing the closed-loop performance recovery property but also removing the steady-state errors without the integrators with respect to the tracking errors. The second one is to prove that the inner and outer loops are stabilised by the proposed cascade-type controller, simultaneously. The simulation and experimental results reveal that the proposed method maintains the speed tracking performance to be satisfactory for a wide operating region with the fixed control gain despite a plant-model mismatch where a 3-kW interior PMSM is utilised.     

Integral sliding mode control with a disturbance observer for next-generation servo track writing

In this paper, we propose a new control scheme that provides position and velocity profile tracking control for next-generation servo track writing (STW). Whereas conventional servo track writers require controllers that perform fast positioning control with fast track seeking and regulation, spiral servo track writers require accurate position and velocity profile tracking control to achieve high quality servo patterns on the media disk. Because STW timing eventually renders geometrically accurate servo patterns, both position and velocity error signals should be regulated within small bounds in a constant velocity region. Regulation via an integral sliding mode controller (SMC) is known to provide good tracking performance; however, use of a high switching gain is inappropriate for an actuator with resonance modes. In this paper, we therefore apply integral sliding mode control with a disturbance observer to STW. The relationship between eigenvalues and control gains is mathematically analyzed to improve dynamic tracking response. To verify the utility of the proposed position and velocity profile tracking control, we perform a comparative study between the proposed and conventional control methods and experimentally validate the performance of the proposed method.     

Adaptive robust fast control for induction motors

A new induction motor position controller that exhibits fast response and robustness is proposed. The control strategy is based on the well-known linear quadratic regulator design principle. By adaptively adjusting a penalty parameter, it is shown that the control strategy enables the induction motor system to exhibit fast convergence. Meanwhile, since the sliding mode will occur in the transient process, the fast control inherits the robustness in matched uncertainties of the sliding-mode control. In addition, to alleviate the chattering effect of the switching control signal, a low-pass filter is used to smooth the control and its design is integrated with the switching control design. The performance of the proposed control strategy is verified by experimental results     

A time-varying sliding surface for robust position control of a DCmotor drive

In this paper, a new variable-structure position control law for a DC motor is proposed. The algorithm, based on a time-varying switching line, guarantees the existence of a sliding mode from the beginning of the shaft motion. Indeed, the surface is initially designed to pass through the initial representative point and subsequently moved toward a predetermined desired surface via shifting. By this means, the reaching phase is eliminated and the motor behavior is insensitive to unknown mechanical configuration changes. The algorithm has been tested in simulation and the experiment has been performed using a low-cost 16-bit microcontroller. Then, an advanced test bed is used in order to evaluate the tracking properties and the robustness capacities of the variable-structure control law with variations of the mechanical configuration     

Adaptive model updating for robust object tracking

In this paper, we exploit features extracted from convolutional neural network (CNN) to be better utilized for visual tracking. It is observed that CNN features in higher levels provide semantic information which is robust to appearance variations. Thus we integrate the hierarchical features in different layers of a deep model to correlation filter tracking framework. More specifically, correlation filters are learned on each layer to encode the object appearance. The peak-to-sidelobe ratio (PSR) is employed to measure the differences between image patches. To leverage the robustness of our model, we develop an adaptive model updating scheme to train the correlation filters according to different response maps. Extensive experimental results on three large scale benchmark datasets show that the proposed algorithm performs favorably against state-of-the-art methods.     

Decoupling control for two-axis inertially stabilized platform based on an inverse system and internal model control

This paper describes a decoupling control scheme for a two-axis inertially stabilized platform (ISP) used in the airborne power line inspection system. The dynamic model of the ISP has been obtained by using the Newton–Euler equation first. The inverse system method combining with the internal model control has been proposed to deal with the nonlinearity and coupling of the ISP. The key idea is to design an inverse system with measured system states such as angular positions, rates and accelerations. Then a pseudo-linear system is constructed when the inverse system is connected with the original system in series. As a result, the coupled nonlinear MIMO (Multiple-Input Multiple-Output) system is converted to two linear decoupled SISO (Single-Input Single-Output) subsystems. Model uncertainties or unmeasurable disturbances existing objectively can be solved by introducing internal model control. Better decoupling effect and disturbance rejecting ability are demonstrated by numerical simulations and experiments carried out on a two-axis ISP system.     

新型混联机构结合扰动观测器的滑模控制

针对一种新型混联式汽车电泳涂装输送机构,考虑其在实际控制中存在建模误差、参数不确定性、摩擦力和外部未知干扰,为削弱其对系统产生的不利影响,提高输送机构的控制性能,提出一种结合扰动观测器的滑模控制策略。运用Lyapunov稳定性理论证明了所提出控制算法的稳定性,并对滑模控制和结合扰动观测器的滑模控制进行MATLAB仿真比较。     

Adaptive neural network output feedback robust control of electromechanical servo system with backlash compensation and disturbance rejection

In this paper, the high-performance tracking control of electromechanical servo systems is concerned. A novel neural network state observer is designed to observe the unknown states. Compared with existing neural network observers, the proposed observer has higher observation accuracy and better robustness. The addition of a fixed-weight single-node neural network can effectively improve the approximation ability of the double-layer neural network without adding a huge amount of calculation. With the addition of the new gain adjustment terms, the observer can still achieve high observation accuracy when the neural network approximation performance is poor, and the observation error can be kept arbitrarily small. To cope with the inherent explosion of the complexity problem in the classical backstepping method in controller design, a command filter is utilized. Compared with other results, the command filtering error has also been considered, and compensating signals are designed to eliminate it. The Lyapunov function is used to show the stability of the controller. Extensive comparative simulations and experimental results verify the effectiveness and advancement of the proposed control strategy compared with other controllers.     

Adaptive pseudoreduced-order flux observer for speed sensorlessfield-oriented control of IM

An adaptive pseudoreduced-order flux observer for speed sensorless field-oriented control is presented. In comparison with the adaptive full-order flux observer, the proposed method consumes less computational time and illustrates better speed performance. Simulations and experiments on a 3-hp induction motor verify the validity of the proposed method