Nonlinear Control of an Induction Motor Using a Reduced-Order Extended Sliding Mode Observer for Rotor Flux and Speed Sensorless Estimation

This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. Thus, as compared with a full-order sliding mode observer, in order to reduce the execution time of the estimation, a reduced-order discrete-time Extended sliding mode observer is proposed for on-line estimation of rotor flux, speed and rotor resistance in an induction motor using a robust feedback linearization control. Simulations results on Matlab-Simulink environment for a 1.8 kW induction motor are presented to prove the effectiveness and high robustness of the proposed nonlinear control and observer against modeling uncertainty and measurement noise.

Civil aircraft fault tolerant attitude tracking based on extended state observers and nonlinear dynamic inversion

For the problem of sensor faults and actuator faults in aircraft attitude control,this paper proposes a fault tolerant control(FTC)scheme based on extended state observer(ESO)and nonlinear dynamic inversion(NDI).First,two ESOs are designed to estimate sensor faults and actuator faults respectively.Second,the angular rate signal is reconstructed according to the estimation of sensor faults.Third,in angular rate loop,NDI is designed based on reconstruction of angular rate signals and estimation of actuator faults.The FTC scheme proposed in this paper is testified through numerical simulations.The results show that it is feasible and has good fault tolerant ability.

Backstepping Sliding Mode Control Based on Extended State Observer for Hydraulic Servo System

Hydraulic servo system plays an important role in industrial fields due to the advantages of high response,small size-to-power ratio and large driving force.However,inherent nonlinear behaviors and modeling uncertainties are the main obstacles for hydraulic servo system to achieve high tracking perfor-mance.To deal with these difficulties,this paper presents a backstepping sliding mode controller to improve the dynamic tracking performance and anti-interfer-ence ability.For this purpose,the nonlinear dynamic model is firstly established,where the nonlinear behaviors and modeling uncertainties are lumped as one term.Then,the extended state observer is introduced to estimate the lumped distur-bance.The system stability is proved by using the Lyapunov stability theorem.Finally,comparative simulation and experimental are conducted on a hydraulic servo system platform to verify the efficiency of the proposed control scheme.

Conventional and Added-Order Proportional Nonlinear Integral Observers

In this paper, a kind of fire new nonlinear integrator and integral action is proposed. Consequently, a conventional Proportional Nonlinear Integral (P_NI) observer and two kinds of added-order P_NI observers are developed to deal with the uncertain nonlinear system. The conditions on the observer gains to ensure the estimated error to be ultimate boundness, which shrinks to zero as the states and control inputs converge to the equilibrium point, are provided. This means that if the observed system is asymptotically stable, the estimated error dynamics is asymptotically stable, too. Moreover, the highlight point of this paper is that the design of nonlinear integral observer is achieved by linear system theory. Simulation results showed that under the normal and perturbed cases, the pure added-order P_NI observer can effectively deal with the uncertain nonlinearities on both the system dynamics and measured outputs.

Enhanced adaptive nonlinear extended state observer for pure feedback systems with matched and mismatched disturbances

In this paper, an enhanced adaptive nonlinear extended state observer (EANESO) for single-input single-output pure feedback systems in the presence of external time-varying disturbances is proposed. In this paper, a nonlinear system with matched and mismatched disturbances is considered. The conventional extended state observer (ESO) can only be applied to systems that are in the form of integral chains. Moreover, this method has limitations in the face of mismatched disturbances. In the presence of time-varying disturbances, the traditional ESOs cannot estimate the disturbances accurately. To overcome this limitation, an EANESO is proposed in this paper. The main idea is to design the nonlinear ESO (NESO) to estimate the states of the system and multiple disturbances simultaneously. The observer gains are considered time-varying and adjusted with adaptation laws to improve the estimation accuracy and overcome the peaking phenomenon. Next, the proposed controller is designed based on output feedback to eliminate the effects of multiple disturbances and stabilize the closed-loop system. Subsequently, the stability analysis of the closed-loop system and convergence of the observer error are discussed. Finally, the proposed method is applied to the inverted pendulum system. The simulated results show good performance of the proposed method as compared with a recently published scheme in the related literature.

光电稳定平台的分数阶降阶自抗扰控制设计

为了提高光电稳定平台的动态性能与抗干扰能力,提出一种分数阶降阶自抗扰控制(FO-RADRC)算法。首先,利用系统输出信号的可测性和可靠性,采用降阶线性扩张状态观测器,提高观测效率和精度;然后,采用分数阶PD(FOPD)作为控制律,从而增强系统的稳定性和控制性能。通过数值仿真实验,与线性自抗扰算法和降阶线性自抗扰算法进行了对比分析。结果表明,所提算法在动态性能指标上均优于对比算法,且在不同频率的等效扰动作用下具有更强的扰动抑制能力。这些结果验证了所提改进算法在提升光电稳定平台控制效果方面的有效性和创新性。

Full-Order Sliding Mode Control for High-Order Nonlinear System Based on Extended State Observer

In this paper, a full-order sliding mode control based on extended state observer(FSMC+ESO) is proposed for high-order nonlinear system with unknown system states and uncertainties.The extended state observer(ESO) is employed to estimate both the unknown system states and uncertainties so that the restriction that the system states should be completely measurable is relaxed,and a full-order sliding mode controller is designed based on the ESO estimation to overcome the chattering problem existing in ordinary reduced-order sliding mode control. Simulation results show that the proposed method facilitates the practical application with respect to good tracking performance and chattering elimination.

Extended state observer for uncertain lower triangular nonlinear systems subject to stochastic disturbance

The extended state observer （ESO） is the most important part of an emerging control technology known as active disturbance rejection control to this day, aiming at estimating ＂total disturbance＂ from observable measured output. In this paper, we construct a nonlinear ESO for a class of uncertain lower triangular nonlinear systems with stochastic disturbance and show its convergence, where the total disturbance includes internal uncertain nonlinear part and external stochastic disturbance. The numerical experiments are carried out to illustrate effectiveness of the proposed approach.

Sampled-data extended state observer for uncertain nonlinear systems

In this paper, we present a sampled-data nonlinear extended state observer （NLESO） design method for a class of nonlinear systems with uncertainties and discrete time output measurement. To accommodate the inter-sample dynamics, an inter-sample output predictor is employed in the structure of the NLESO to estimate the system output in the sampling intervals, where the prediction is used in the proposed observer instead of the system output. The exponential convergence of the sampled-data NLESO is also discussed and a sufficient condition is given by the Lyapunov method. A numerical example is provided to illustrate the performance of the proposed observer.

Active Disturbance Rejection Control for Uncertain Nonlinear Systems With Sporadic Measurements

This paper deals with the problem of active disturbance rejection control(ADRC)design for a class of uncertain nonlinear systems with sporadic measurements.A novel extended state observer(ESO)is designed in a cascade form consisting of a continuous time estimator,a continuous observation error predictor,and a reset compensator.The proposed ESO estimates not only the system state but also the total uncertainty,which may include the effects of the external perturbation,the parametric uncertainty,and the unknown nonlinear dynamics.Such a reset compensator,whose state is reset to zero whenever a new measurement arrives,is used to calibrate the predictor.Due to the cascade structure,the resulting error dynamics system is presented in a non-hybrid form,and accordingly,analyzed in a general sampled-data system framework.Based on the output of the ESO,a continuous ADRC law is then developed.The convergence of the resulting closed-loop system is proved under given conditions.Two numerical simulations demonstrate the effectiveness of the proposed control method.

An Improved Nonlinear Dynamic Inversion Method for Altitude and Attitude Control of Nano Quad-Rotors under Persistent Uncertainties

Nonlinear dynamic inversion(NDI)has been applied to the control law design of quad-rotors mainly thanks to its good robustness and simplicity of parameter tuning.However,the weakness of relying on accurate model greatly restrains its application on quad-rotors,especially nano quad-rotors(NQRs).NQRs are easy to be influenced by uncertainties such as model uncertainties(mainly from complicated aerodynamic interferences,strong coupling in roll-pitch-yaw channels and inaccurate aerodynamic prediction of rotors)and external uncertainties(mainly from winds or gusts),particularly persistent ones.Therefore,developing accurate model for altitude and attitude control of NQRs is difficult.To solve this problem,in this paper,an improved nonlinear dynamic inversion(INDI)method is developed,which can reject the above-mentioned uncertainties by estimating them and then counteracting in real time using linear extended state observer(LESO).Comparison with the traditional NDI(TNDI)method was carried out numerically,and the results show that,in coping with persistent uncertainties,the INDI-based method presents significant superiority.

基于对数型障碍Lyapunov函数的俯仰驾驶仪设计

相控阵雷达制导拦截弹在拦截高速大机动目标时,弹体气动参数剧烈非线性变化影响控制系统对大攻角的响应效果,应设计考虑攻角指令跟踪误差约束的鲁棒自动驾驶仪控制律。基于双幂次趋近律和对数型障碍李雅普诺夫函数设计了鲁棒非线性自动驾驶仪控制律,可将攻角指令的跟踪误差快速收敛于约束范围内。通过降阶扩张状态观测器对系统中存在的气动参数不确定性和系统外部扰动进行在线估计和补偿。稳定性分析和数值仿真表明,攻角可在1 s内达到稳态且攻角响应的稳态误差<10-4°,所提出的自动驾驶仪控制律具有较强的鲁棒性,能够准确稳定地跟踪攻角指令,控制导弹产生所需过载进而精准拦截目标。

改进扩张状态观测器的PMSM自抗扰控制策略

为增强永磁同步电机伺服系统对负载扰动、电机参数摄动等工况的鲁棒性,提出一种改进自抗扰速度环控制策略。设计级联非线性扩张状态观测器估计系统总扰动,NESO1观测系统扰动,NESO2将NESO1观测扰动作为已知部分观测剩余扰动,减小传统非线性扩张状态观测器对扰动的观测误差。针对传统非线性fal函数存在拐点不光滑连续,易导致系统震颤的问题,设计一种newfal非线性函数并应用到级联NESO的改进结构中。基于MATLAB/Simulink平台搭建模型,仿真结果表明改进自抗扰控制对速度变化、负载扰动、参数摄动等具有较强的鲁棒性。newfal-CADRC相较于传统ADRC速度稳态误差、负载突变变化值以及恢复时间分别减少约36%、59%、66%。最后在1 kW的实际系统平台上进行验证。综合仿真和实物实验,充分证明了改进的控制策略对负载扰动、斜坡负载扰动具有较好的鲁棒性,对参数摄动、噪声影响具有较好的抵抗能力。

基于TNESO的PMSLM分数阶自抗扰控制

线性自抗扰控制(LADRC)以结构简单、易于实现且抗干扰能力强的特点在永磁同步直线电机(PMSLM)中得到广泛应用,但电机启动和负载突变会导致LADRC系统中的线性扩张状态观测器(LESO)扰动估计精度下降。为此,提出一种基于时变增益非线性扩张状态观测器(TNESO)的PMSLM分数阶自抗扰控制策略。结合LESO和非线性扰动观测器(NDOB),并根据误差与增益的关系构建动态增益函数,设计新型状态观测器TNESO;在此基础上,以分数阶PDμ控制律代替线性状态误差反馈控制律(LSEF),建立改进型自抗扰速度控制系统,以进一步提高电机控制的实时性和鲁棒性。仿真与实验结果表明:所设计的速度控制系统可以有效减少直线电机启动、负载突变时的观测响应时间,抑制观测初始时刻扰动峰值,从而满足高性能的PMSLM速度控制要求。

基于扩张状态观测器的伺服加载模糊滑模控制

针对电动伺服加载测试台存在的间隙、摩擦等非线性控制问题,以滑模变结构控制(SMC)为主体进行了加载控制器设计。分析伺服加载测试台整体结构,提出一种基于扩张状态扰动观测器(ESO)的模糊滑模控制(FSMC)策略。该策略在使用ESO针对伺服加载系统的外部干扰进行观测的基础上,设计了模糊控制对滑动模态面和滑模趋近律进行自适应调节,提高了系统的动态实时跟随能力和干扰补偿能力,并减小SMC控制器稳定时的抖振现象。仿真结果表明:所设计的基于扩张状态观测器的模糊滑模控制器(FSMC-ESO)对比传统SMC及PID控制具有更好的快速响应性和鲁棒性。

基于滑模自抗扰的储能变流器控制策略

为了提高储能变流器(PCS)的动态性能,设计基于降阶级联扩张状态观测器(ESO)和互补滑模控制(CSMC)的改进自抗扰控制(ADRC)策略,将改进ADRC策略应用于PCS的双向DC/AC变流器电压外环.改进ESO为降阶级联ESO以提高状态变量和系统总扰动的估计速度,增加扰动估计能力;更改PD控制为CSMC以设计状态误差反馈律,提升PCS的系统鲁棒性;设计改进指数趋近律以抑制抖振现象.为了证明改进ADRC策略相较于PI控制和传统ADRC的优越性,建立仿真模型并搭建相关实验平台.仿真与实验结果表明,改进ADRC策略减小了PCS暂态时直流母线电压波动,提高了PCS交流侧功率响应速度,改善了交流侧的输出电能质量.

基于增强型扩张状态观测器的永磁同步电机低抖振高抗扰二阶终端滑模电流控制

永磁同步电机电流滑模控制具有较好的参数鲁棒性,但控制精度受到滑模抖振的影响,且抖振抑制与抗扰性之间存在矛盾。为此,该文提出一种基于增强型扩张状态观测器的二阶终端滑模电流控制方案,可以有效提升电流控制性能。通过二阶终端滑模控制器的设计,将一阶积分快速终端滑模嵌套在二阶非奇异终端滑模面中,使得滑模抖振得到较好的抑制,同时实现电流无稳态误差的快速收敛。通过引入扩张状态观测器对扰动信号的集总估计与补偿,缓解了抖振与抗扰性之间的矛盾,进一步提升了电流精度。针对数字控制的延迟影响,设计了Smith预估器,提升了扰动补偿精度。最后,通过实验对该文所设计的电流控制方案进行验证,并通过对比展示了该方案的有效性。

基于级联线性-非线性自抗扰控制器的永磁直线同步电机速度控制策略研究

为了提升永磁直线同步电机(permanent magnet linear synchronous motor,PMLSM)在负载变化、参数摄动和其他不确定因素下的抗扰性能和速度跟踪性能,提出一种基于级联线性-非线性自抗扰控制器的PMLSM速度控制策略。首先,建立考虑负载扰动和参数失配的PMLSM数学模型;其次,设计级联线性-非线性扩张状态观测器来实时估计和补偿系统所受的不确定扰动,前级线性扩张状态观测器保证系统在大扰动下保持稳定,后级非线性扩张状态观测器利用非线性机制进一步提高系统对扰动的估计精度,从而将线性自抗扰控制和非线性自抗扰控制的优势相结合,以此提升系统的速度跟踪性能和抗扰动能力;并且,对所提控制器提出基于劳斯判据的稳定性分析方法,并对系统的抗扰性能和噪声抑制性能进行了频域分析;最后,对基于PI控制、级联线性自抗扰控制、非线性自抗扰控制和级联线性-非线性自抗扰控制的永磁直线同步电机系统进行仿真和实验对比,验证所提方法的优越性。

高空舱进气环境压力模拟新型自抗扰控制

高空舱进气环境压力模拟控制系统在发动机开展过渡态试验中存在强气流扰动及大量随机噪声干扰,为此,提出新型非线性状态误差反馈函数xal及在结构上引入总扰动状态变量反馈环节来设计扩张状态观测器算法(记作xal-ESO),并以此提出基于xal-ESO的高空舱进气环境压力模拟新型自抗扰控制方法。借助数值仿真对比所提出的xal-ESO与常见ESO在状态与总扰动方面的估计能力,结果表明xal-ESO能有效抑制系统输出噪声并取得较好的估计品质。基于系统核心设备模型搭建高空舱进气环境压力模拟仿真平台并进行工程试验,对比了基于xal-ESO的自抗扰控制与当前工程中使用的线性自抗扰控制的进气环境压力控制效果,试验结果显示线性自抗扰控制方法受噪声影响明显,而所提出的新型自抗扰控制方法在发动机过渡态试验中跟踪进气压力时超调量降低了58.70%,稳态误差降低了95.71%,表明该方法能够有效提升高空舱进气环境压力模拟效果,提升发动机过渡态性能评价的准确性。

基于NESO-LFDC的四旋翼无人机滑模姿态控制

针对四旋翼无人机姿态控制中存在空气动力学特性复杂,易受干扰的特性,提出一种基于非线性扩张状态观测器(nonlinear extended state observer,NESO)和低频干扰补偿器(low-frequency disturbance compensator,LFDC)的非奇异快速终端滑模控制方法。该方法内环设计了NESO和LFDC结合,以获得干扰补偿值并补偿总干扰的低频分量。在外环设计了跟踪微分器和可变切换增益的非奇异快速终端滑模控制器,用于补偿虚拟干扰估计值的误差和总干扰的高频分量。仿真结果表明,该控制方法可以更好地估计总干扰的低频和高频分量,减少虚拟干扰估计值的误差对四旋翼无人机姿态控制的影响,并提升响应速度。