Sliding mode control combined with extended state observer for an ankle exoskeleton driven by electrical motor

A novel sliding mode control combined with extended state observer (ESO) is proposed for an ankle exoskeleton driven by electrical motor. During the process of assisting, it is necessary to design an effective controller for assisting torque of ankle exoskeleton. However, the parameter uncertainty of complex dynamics model and the irregular motion of human ankle may affect the torque control accuracy. For a high control precision of assisting torque when facing the modeling uncertainty, the sliding mode control is employed, but a large switching gain is usually needed in order to suppress the disturbance, which cause the control signal vibrate greatly. ESO can observe and suppress the disturbance and modeling uncertainty, but its tracking performance needs to be improved. Therefore, the proposed complex controller takes the advantages of sliding mode control and extended state observer, which can not only improve torque tracking performance but also overcome the disturbance force caused by the change of human joint angle without increasing chattering of control signal. Experimental studies are carried out to validate the effectiveness of the proposed control. The results show the presented controller have better torque tracking performance and robustness stability, and the proposed controller can reduce the chattering compared with the tradition sliding mode control.     

Automatic disturbances rejection controller for precise motion control of permanent-magnet synchronous motors

A highly robust automatic disturbances rejection controller (ADRC) is developed to implement high-precision motion control of permanent-magnet synchronous motors. The proposed ADRC consists of a tracking differentiator (TD) in the feedforward path, an extended state observer (ESO), and a nonlinear proportional derivative control in the feedback path. The TD solves the difficulties posed by low-order reference trajectories which are quantized at the sensor resolution, and the ESO provides the estimate of the unmeasured system's state and the real action of the unknown disturbances only based on a measurement output of the system. Simulations and experimental results show that the proposed ADRC achieves a better position response and is robust to parameter variation and load disturbance. Furthermore, the ADRC is designed directly in discrete time with a simple structure and fast computation, which make it widely applicable to all other types of derives.     

基于扩张状态观测器的永磁同步电机无差拍电流预测控制

针对永磁同步电机预测控制中电机参数扰动偏差造成的输出电流静差及振荡问题,采用基于扩张状态观测器的无差拍电流预测控制算法,构建相应的扰动观测器来观测参数偏差造成的系统扰动,为传统预测控制算法提供实时性扰动补偿。采用有功阻尼概念对转速PI参数进行设计,并针对控制系统的延时进行了补偿。仿真结果表明所提出的算法能够快速无静差地观测系统扰动,有效避免参数扰动偏差对电流预测系统的影响,同时转速环也具有良好的动态性能。     

Vibration reduction of seat suspension using observer based terminal sliding mode control with acceleration data fusion

In this work, a disturbance observer and state observer based terminal sliding mode (TSM) controller with acceleration data fusion is proposed for the active control of a seat suspension. In practical applications, the driver's body and the friction forces are difficult to be accurately described with a mathematical model; for this reason, the proposed controller is designed based on a model simplified from a 6-degree-of-freedom (6-DOF) seat-driver model with nonlinear friction. The disturbance observer and state observer are designed together with Linear Matrix Inequality (LMI) method. For improving the observer's performance, a complementary filter is applied to fuse the estimation of the seat suspension velocity from the acceleration measurement and the state observer. The proposed controller is validated using simulations with various bump excitations applied, and the conventional state feedback TSM controller is implemented for comparison. The proposed controller is also implemented in a practical active seat suspension prototype, and a well-tuned commercial heavy duty vehicle seat suspension is applied for comparison. The power spectral density (PSD) value and ISO 2631–1 standard are used to evaluate the active seat suspension system's performance under random vibration. Both the simulation and the experimental results indicate that with the proposed controller, the vibration magnitude caused by a rough road can be greatly reduced, and the driver ride comfort is greatly improved.     

基于ESO的导引头稳定平台双积分滑模控制

为了提高导引头稳定平台抗扰性及速度稳态跟踪性能,提出了一种基于扩张状态观测器（Extended State Observer,ESO）的双积分滑模控制器（Double Integral Sliding Mode Controller,DISMC）。首先,采用二阶扩张状态观测器对系统的未知扰动进行估计;然后,采用了双积分滑模控制器实现了系统的低稳态误差跟踪,同时采用了改进的幂次趋近律来削弱控制系统的抖振影响;最后,采用导引头稳定平台进行目标跟踪实验和隔离度性能测试。实验结果表明,与传统基于扰动观测器（Disturbance Observer,DOB）的PI控制方法相比,跟踪3（）/s的梯形波时,在提出的控制器作用下速度跟踪快速性提高了48 ms,跟踪误差标准差提高了0.0131（）/s。同时用转台模拟弹体扰动分别为sin（t）、3sin（5t）、7sin（2t）时,系统的隔离度分别提高了2.91%、0.45%、0.7%,表明基于扩张状态观测器的双积分滑模控制器对导引头稳定平台具有较强的抗扰性和较好的跟踪性能。     

基于扩张状态观测器的直线倒立摆状态反馈控制研究

针对直线倒立摆的控制问题,利用拉格朗日方法对实际物理模型进行线性化处理建立数学模型,为了提高控制精度,将不确定外扰和未建模动态视为一个综合扰动项,运用扩张状态观测器对系统状态和综合扰动项进行观测,设计了基于扩张状态观测器的直线倒立摆状态反馈稳摆控制器;用能量反馈方法和bang-bang控制器实现倒立摆起摆到稳摆的切换。通过无干扰和有干扰状态直线倒立摆起摆到稳摆过程的实验研究,表明系统能够有效的抑制外界干扰,具有较强的鲁棒性。     

ESO在具有不确定性的混沌系统同步中的应用

根据扩张状态观测器（ESO）的思想构造“扩张系统”通过挖掘同步误差中所隐含的系统信息,对扩张系统的各个状态进行估计,在此基础上设计物理上可实现的控制器,实现了两个具有模型或参数失配的混沌系统的同步。以Lorenz系统和Duffing,Vander Pol系统为例进行仿真,同步效果很好。     

基于状态观测器的混沌动态系统跟踪控制

针对一类连续混沌动态系统,提出一种基于状态观测器的跟踪控制方法来进行混沌控制.在引入状态观测器观测混沌动力学系统状态变量的基础上,采用反馈线性化方法将非线性混沌系统转换为线性系统,再针对反馈线性化后的线性系统设计轨迹跟踪控制器,实现被控混沌系统的跟踪控制.仿真结果进一步验证了该方法的有效性.     

Output feedback nonlinear control for electro-hydraulic systems

In this paper we present an output feedback nonlinear control for position tracking of electro-hydraulic systems (EHSs). Although previous nonlinear control methods improved the position tracking performance of EHS, all of the methods require full state feedback. However, due to cost and space limitations, it is not always possible to measure the full state of the EHS. The proposed method consists of a high gain observer and a passivity-based controller. The high gain observer is designed to estimate the full state, and the passivity-based control is implemented for position tracking. In order to design the passivity-based controller with the high gain observer, a defined Lyapunov condition guarantee that the origin of the tacking error dynamics is exponentially stable by selecting the controller gain. The stability of the closed-loop is studied using the singular perturbation theorem. The performance of the proposed method is validated through simulations and experiments.     

线性扩张状态观测器的改进及在空间光通信粗跟踪的应用

针对传统自抗扰控制器的扰动补偿效果随着扰动频率增加迅速下降的问题,提出了一种基于改进的线性扩张状态观测器的自抗扰控制方法。该方法首先对粗跟踪进行系统分析、简化及辨识;然后对线性扩张状态观测器的观测原理进行详细推导与论证,从理论上指出其不足,提出了一种改进的线性扩张状态观测器;最后将改进的算法与PID调节器相结合,实现了粗跟踪的自抗扰控制。实验结果表明:针对幅度在1、频率在0.5~2.5 Hz间的外部位置扰动,传统的自抗扰控制器随着扰动频率的增加,扰动隔离度下降非常明显,2 Hz时的提升程度仅为0.5 Hz处的9.5%;而采用改进的算法使扰动隔离度至少提高了4.146 dB,且随着扰动频率的增加,扰动隔离度的提升非常稳定,2.5 Hz时的提升程度与0.5 Hz处几乎一致;此外,该方法有较好的鲁棒性,允许被控对象在20%的范围内变化。理论分析、仿真分析、物理实验均证明该方法的有效性,对类似的光电跟踪系统有一定的参考价值。     

Gearshift control system development for direct-drive automated manual transmission based on a novel electromagnetic actuator

A novel gearshift system which comprises a 2 degree-of-freedom electromagnetic actuator is introduced to simplify the structure of gearshift system of automated manual transmission (AMT), increase transmission efficiency and improve shift quality. The working principle and characteristics of the actuator are analyzed. The gearshift process is divided into the non-synchronization and the synchronization phase. Extended state observer (ESO) based inverse system method (ISM) and active disturbance rejection controller (ADRC) are designed for the two processes respectively. ISM can eliminate the nonlinearity of the actuator and ESO can estimate and compensate the uncertainties, parameter variations and external disturbances. ADRC is adopted to improve the tracking accuracy of the synchronization process. Comparative simulations and experimental results demonstrate the effectiveness of the proposed control method, and good gearshift performance has been achieved. Combined with the new designed control strategy, the novel gearshift system provides a new solution for AMT applications.     

Precise friction control for the nonlinear friction system using the friction state observer and sliding mode control with recurrent fuzzy neural networks

This paper deals with a tracking control problem of a mechanical servo system with nonlinear dynamic friction which contains a directly immeasurable friction state variable and an uncertainty caused by incomplete parameter modeling and its variations. In order to provide an efficient solution to these control problems, we propose a composite control scheme, which consists of a friction state observer, a RFNN approximator and an approximation error compensator with sliding mode control. In first, a sliding mode controller and friction state observer are designed to estimate the unknown internal state of the LuGre friction model. Next, a RFNN is developed to approximate an unknown lumped friction uncertainty. Finally, an adaptive error compensator is designed to compensate an approximation error of RFNN. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are executed. Their results give a satisfactory performance of the proposed control scheme.     

陀螺稳定平台速度环的离散自抗扰控制

针对陀螺稳定平台在高精度定位下的控制精度受到速度环电机在低速运动时非线性摩擦力影响的问题,文章设计了一种改进策略的自抗扰控制器,将原系统中的非线性摩擦力与电机不同转向时的模型误差统一视为系统扰动,采用扩张状态观测器对这个扰动进行估计,前馈到控制量中进行校正。理论分析了一阶离散系统上扩张状态观测器的推导过程和稳定性条件,并采用遗传算法工具箱对针对平台所设计的扩张状态观测器的参数进行辨识。在仿真实验中,我们首先分析了所设计的扩张状态观测器的开环性能,然后将所设计的自抗扰控制器与实际系统采用的PI控制器的控制精度进行了对比分析。文章为进一步提高陀螺稳定平台的控制性能,提供了一种新的高精度的控制策略。     

Vehicle Full-State Estimation and Prediction System Using State Observers

This paper presents a novel vehicle full-state estimation and prediction system that employs a “full-state vehicle model” together with lateral acceleration, longitudinal velocity, and suspension displacement sensors to obtain the current and future vehicle state information. The full-state vehicle model is a vehicle model with 6 degrees of freedom (DOFs) and is described by 20-state nonlinear differential equations. The proposed approach differs from those in most of the existing literatures in three aspects. First, the road angles and the nonlinear suspension systems are incorporated into the vehicle modeling. Second, the “switching observer scheme” is introduced to significantly reduce the heavy work load that is required for the mathematical derivations. Finally, the full-state vehicle model is employed to predict the vehicle dynamics at future times. The simulation results show that the proposed system can accurately estimate and predict the state values. The relative accuracy of the state estimation is 2.66% on average and 2.86% on average of the state prediction. Furthermore, the proposed system can predict whether the vehicle rollover will occur when a vehicle performs a quick turn on a slope road.      

Design and experimental research of observer-based adaptive type-2 fuzzy steering control for automated vehicles with prescribed performance

Steer-by-Wire (SbW) system is a significant electromechanical subsystem of automated vehicles. This paper proposes an observer-based type-2 fuzzy control method for the SbW system with uncertain nonlinearity, unknown modeling parameters, and unavailable state. First, an interval type-2 fuzzy logic system (IT2 FLS) and an IT2 FLS-based state observer are constructed to estimate the uncertain nonlinearity and unavailable state of SbW systems. Then, a prescribed performance control (PPC) method is proposed to achieve the prescribed tracking performance of SbW systems. Much importantly, a modified performance function is incorporated in this control method, such that the prescribed tracking performance can be guaranteed within a finite time regardless of the initial state. Finally, simulation and vehicle experiments are given to verify the effectiveness and superiority of the proposed methods.     

Robust tracking servo system considering force disturbance for the optical disk recording system

This paper proposes a new robust tracking servo system for the optical disk recording system with feedforward controller based on the prediction of the tracking error. In optical recording systems, the feedback servo system must suppress the influence of force disturbance and parameter variation. To overcome this problem, this paper designs the robust feedback control system by using coprime factorization and disturbance observer. The detecting signal of the optical disk recording system is only a tracking error. Hence, the feedforward controller of the proposed tracking control system is constructed based on both the "zero-phase-error tracking" control theory and the prediction of the tracking error. The experimental results point out that the proposed tracking servo system has a quick and precise tracking response and keeps the residual tracking error below its tolerance.     

基于扩张状态观测器的快速反射镜控制研究

为了提高快速反射镜的动态性能并降低跟踪误差,提出了利用扩张状态观测器引入反馈和灰色PID模型控制相结合的方法,该方法基于音圈电机驱动的快速反射模型,采用离散跟踪微分器对输入信号进行过渡和滤波以及对子系统零点配置,并以扩张状态观测器引入反馈和灰色PID控制,对系统的不确定因素进行了估计和补偿,并同不完全微分PID和基于跟踪微分器的零点配置方法进行了性能比较。采用随机正弦信号进行跟踪仿真,仿真结果表明,采用文中算法的跟踪效果明显优于其他算法,且跟踪误差更小,被控对象的动态性能更优,尤其在系统的模型参数发生变化时。该方法具有良好的工程应用价值。     

一种可完全线性化的不同类型混沌系统同步方法

讨论可完全线性化的不同类型混沌系统之间的同步问题.根据滑模控制原理求取混沌同步控制形式,利用扩张状态观测器对系统信息进行渐进估计,把复杂的滑模控制策略变为可实现的控制方式,以此实现具有不确定性混沌系统的同步.以Duffing和Vander Pol系统为例进行仿真,效果良好.     

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.