An extended state observer with adjustable bandwidth for measurement noise

In this paper,a bandwidth-adjustable extended state observer(ABESO)is proposed for the systems with measurement noise.It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise,which conflicts with observation accuracy.Therefore,we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system.The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error.When the tracking error decreases,the bandwidth decreases to suppress the noise,otherwise the bandwidth does not change.It is proven that the error dynamics are bounded and converge in finite time.The relationship between the upper bound of the estimation error and the scaling factor is given.When the scaling factor is less than 1,the ABESO has higher estimation accuracy than the linear extended state observer(LESO).Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments.The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.

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.

Differential geometric guidance command with finite time convergence using extended state observer

For improving the performance of differential geometric guidance command(DGGC), a new formation of this guidance law is proposed, which can guarantee the finite time convergence(FTC) of the line of sight(LOS) rate to zero or its neighborhood against maneuvering targets in three-dimensional(3D) space. The extended state observer(ESO) is employed to estimate the target acceleration, which makes the new DGGC more applicable to practical interception scenarios. Finally, the effectiveness of this newly proposed guidance command is demonstrated by the numerical simulation results.

Event-triggered model-free adaptive control for a class of surface vessels with time-delay and external disturbance via state observer

This paper provides an improved model-free adaptive control(IMFAC)strategy for solving the surface vessel trajectory tracking issue with time delay and restricted disturbance.Firstly,the original nonlinear time-delay system is transformed into a structure consisting of an unknown residual term and a parameter term with control inputs using a local compact form dynamic linearization(local-CFDL).To take advantage of the resulting structure,use a discrete-time extended state observer(DESO)to estimate the unknown residual factor.Then,according to the study,the inclusion of a time delay has no effect on the linearization structure,and an improved control approach is provided,in which DESO is used to adjust for uncertainties.Furthermore,a DESO-based event-triggered model-free adaptive control(ET-DESO-MFAC)is established by designing event-triggered conditions to assure Lyapunov stability.Only when the system’s indicator fulfills the provided event-triggered condition will the control input signal be updated;otherwise,the control input will stay the same as it is at the last trigger moment.A coordinate compensation approach is developed to reduce the steady-state inaccuracy of trajectory tracking.Finally,simulation experiments are used to assess the effectiveness of the proposed technique for trajectory tracking.

Extended state observer-based control with an adjustable parameter for a large ground-based telescope

The high-precision requirements will always be constrained due to the complicated operating conditions of the ground-based telescope. Owing to various internal and external disturbances, it is necessary to study a control method, which should have a good ability on disturbance rejection and a good adaptability on system parameter variation. The traditional proportional-integral(PI) controller has the advantage of simple and easy adjustment, but it cannot deal with the disturbances well in different situations. This paper proposes a simplified active disturbance rejection control law, whose debugging is as simple as the PI controller, and with better disturbance rejection ability and parameter adaptability. It adopts a simplified second-order extended state observer(ESO) with an adjustable parameter to accommodate the significant variation of the inertia during the different design stages of the telescope. The gain parameter of the ESO can be adjusted online with a recursive least square estimating method once the system parameter has changed significantly. Thus, the ESO can estimate the total disturbances timely and the controller will compensate them accordingly. With the adjustable parameter of the ESO, the controller can always achieve better performance in different applications of the telescope. The simulation and experimental verification of the control law was conducted on a 1.2-meter ground based telescope. The results verify the necessity of adjusting the parameter of the ESO, and demonstrate better disturbance rejection ability in a large range of speed variations during the design stages of the telescope.

Simulation on model predictive control for PMSM drive system based on double extended state observer

A novel double extended state observer(DESO)based on model predictive torque control(MPTC)strategy is developed for three-phase permanent magnet synchronous motor(PMSM)drive system without current sensor.In general,to achieve high-precision control,two-phase current sensors are necessary for successful implementation of MPTC.For this purpose,two ESOs are used to estimate q-axis current and stator resistance respectively,and then based on this,d-axis current is estimated.Moreover,to reduce torque and flux ripple and to improve the performance of the torque and speed,MPTC strategy is designed.The simulation results validate the feasibility and effectiveness of the proposed scheme.

PMSM speed control using adaptive sliding mode control based on an extended state observer

In this study,a composite strategy based on sliding-mode control( SMC) is employed in a permanent-magnet synchronous motor vector control system to improve the system robustness performance against parameter variations and load disturbances. To handle the intrinsic chattering of SMC,an adaptive law and an extended state observer( ESO) are utilized in the speed SMC controller design. The adaptive law is used to estimate the internal parameter variations and compensate for the disturbances caused by model uncertainty. In addition,the ESO is introduced to estimate the load disturbance in real time. The estimated value is used as a feed-forward compensator for the speed adaptive sliding-mode controller to further increase the system's ability to resist disturbances. The proposed composite method,which combines adaptive SMC( ASMC) and ESO,is compared with PI control and ASMC. Both the simulation and experimental results demonstrate that the proposed method alleviates the chattering of SMC systems and improves the dynamic response and robustness of the speed control system against disturbances.

Extended state observer based smooth switching control for tilt-rotor aircraft

A tilt-rotor aircraft has three flight modes: helicopter mode, airplane mode and conversion mode. Unlike the traditional aircraft, the tilt-rotor aircraft, which combines the characteristics of helicopters and fixed-wing aircraft, is a complex multi-body system with the violent variation of the aerodynamic parameters. For these characteristics, a new smooth switching control scheme is provided for the tilt-rotor aircraft. First, the reference commands for airspeed and nacelle angles are calculated by analyzing the conversion corridor and the conversion path. Subsequently, based on the finite-time switching theorem, an average dwell time condition is designed to guarantee the stability in the switching process. Besides, considering the state vibrations and bumps may appear in switching points, the fuzzy weighted logic is employed to improve the system transient performance. For disturbance rejection, three extended state observers are designed separately to estimate the disturbances in the switched systems. Compared with the traditional auto disturbance rejection control and proportion integration differentiation control, this method overcomes the conservatism of wasting the whole model information. The control performances of robustness and smoothness are verified with simulation, which shows that the new smooth switching control scheme is more targeted and superior than the traditional design method.

A non-contact spacecraft architecture with extended stochastic state observer based control for gravity mission

A novel non-contact spacecraft architecture with the extended stochastic state observer for disturbance rejection control of the gravity satellite is proposed.First,the precise linear driving non-contact voice-coil actuators are used to separate the whole spacecraft into the non-contact payload module and the service module,and to build an ideal loop with precise dynamics for disturbance rejection control of the payload module.Second,an extended stochastic state observer is enveloped to construct the overall nonlinear external terms and the internal coupled terms of the payload module,enabling the controller design of the payload module turned into the linear form with simple bandwidth-parameterization tuning in the frequency domain.As a result,the disturbance rejection control of the payload module can be explicitly achieved in a timely manner without complicated tuning in actual implementation.Finally,an extensive numerical simulation is conducted to validate the feasibility and effectiveness of the proposed approach.

Intelligent Process Fault Diagnosis for Nonlinear Systems with Uncertain Plant Model via Extended State Observer and Soft Computing

There have been many studies on observer-based fault detection and isolation (FDI), such as using unknown input observer and generalized observer. Most of them require a nominal mathematical model of the system. Unlike sensor faults, actuator faults and process faults greatly affect the system dynamics. This paper presents a new process fault diagnosis technique without exact knowledge of the plant model via Extended State Observer (ESO) and soft computing. The ESO’s augmented or extended state is used to compute the system dynamics in real time, thereby provides foundation for real-time process fault detection. Based on the input and output data, the ESO identifies the un-modeled or incorrectly modeled dynamics combined with unknown external disturbances in real time and provides vital information for detecting faults with only partial information of the plant, which cannot be easily accomplished with any existing methods. Another advantage of the ESO is its simplicity in tuning only a single parameter. Without the knowledge of the exact plant model, fuzzy inference was developed to isolate faults. A strongly coupled three-tank nonlinear dynamic system was chosen as a case study. In a typical dynamic system, a process fault such as pipe blockage is likely incipient, which requires degree of fault identification at all time. Neural networks were trained to identify faults and also instantly determine degree of fault. The simulation results indicate that the proposed FDI technique effectively detected and isolated faults and also accurately determine the degree of fault. Soft computing (i.e. fuzzy logic and neural networks) makes fault diagnosis intelligent and fast because it provides intuitive logic to the system and real-time input-output mapping.

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.

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.

Observer-Based Control for a Cable-Driven Aerial Manipulator under Lumped Disturbances

With the increasing demand for interactive aerial operations,the application of aerial manipulators is becoming more promising.However,there are a few critical problems on how to improve the energetic efficiency and pose control of the aerialmanipulator forpractical application.In this paper,a novel cable-drivenaerialmanipulatorused for remote water sampling is proposed and then its rigid-flexible coupling dynamics model is constructed which takes joint flexibility into account.To achieve high precision joint position tracking under lumped disturbances,a newly controller,which consists of three parts:linear extended state observer,adaptive super-twisting strategy,and fractional-order nonsingular terminal sliding mode control,is proposed.The linear extended state observer is adopted to approximate unmeasured states and unknown lumped disturbances and achieve model-free control structure.The adaptive super-twisting strategy and fractional-order nonsingular terminal sliding mode control are combined together to achieve good control performance and counteract chattering problem.The Lyapunovmethod is utilized to prove the overall stability and convergence of the system.Lastly,various visualization simulations and ground experiments are conducted,verifying the effectiveness of our strategy,and all outcomes demonstrate its superiorities over the existing control strategies.

An Improved Deadbeat Predictive Current Control Method for SPMSM Drives with a Novel Adaptive Disturbance Observer

To improve the dynamic performance of conventional deadbeat predictive current control(DPCC)under parameter mismatch,especially eliminate the current overshoot and oscillation during torque mutation,it is necessary to enhance the robustness of DPCC against various working conditions.However,the disturbance from parameter mismatch can deteriorate the dynamic performance.To deal with the above problem,firstly,traditional DPCC and the parameter sensitivity of DPCC are introduced and analyzed.Secondly,an extended state observer(ESO)combined with DPCC method is proposed,which can observe and suppress the disturbance due to various parameter mismatch.Thirdly,to improve the accuracy and stability of ESO,an adaptive extended state observer(AESO)using fuzzy controller based on ESO,is presented,and combined with DPCC method.The improved DPCC-AESO can switch the value of gain coefficients with fuzzy control,accelerating the current response speed and avoid the overshoot and oscillation,which improves the robustness and stability performance of SPMSM.Finally,the three methods,as well as conventional DPCC method,DPCC-ESO method,DPCC-AESO method,are comparatively analyzed in this paper.The effectiveness of the proposed two methods are verified by simulation and experimental results.

带有状态/输入量化的无人艇航向跟踪控制

[目的]针对水面无人艇(USV)的海上通信受限的问题,提出一种带有状态/输入量化的USV航向跟踪控制方法。[方法]基于反步法设计系统控制律,结合动态面技术降低虚拟控制律的计算量膨胀问题。对于控制系统中存在的不确定项及外界干扰,利用扩张状态观测器(ESO)进行估计。采用均匀量化器分别对控制系统中的状态变量和控制输入进行量化,且量化后的状态反馈信息仅用于跟踪控制。利用量化状态递归设计基于ESO的USV航向控制器,证明闭环控制系统中量化变量和非量化变量间误差的有界性。[结果]基于李雅普诺夫稳定性理论,提出了量化误差考量及闭环系统稳定性判定方法,严格证明了所设计的带有状态量化和输入量化的USV航向跟踪控制系统的稳定性,仿真实验验证了该控制策略的有效性。[结论]结果表明,所提方法可为USV航向跟踪控制提供借鉴。

基于比例谐振内模扩张状态观测器的PMLSM推力波动抑制策略

定位力是永磁同步直线电机(PMLSM)产生推力波动的主要原因,导致振动和噪声,恶化驱动系统运行性能。针对这一问题,该文提出一种基于比例谐振内模扩张状态观测器(PR-IMESO)的PMLSM推力波动抑制策略以提高系统控制精度和运行性能。首先,对PMLSM推力波动进行建模与分析,针对推力波动中占比较大的定位力分量,根据内模原理研究考虑定位力模型的内模扩张状态观测器(IMESO),并在观测器中引入谐振项以加强对二次脉动定位力的抑制。所提出抑制策略对PMLSM定位力具有良好的观测及补偿能力,还可对其余未建模的复杂动子推力波动进行抑制,具有较好的推力波动整体抑制效果。最后,在一台750 W的PMLSM实验平台上验证所提出抑制策略的有效性。

引入ESO的永磁超环面电机无模型预测电流控制

为改善无差拍预测电流控制(DPCC)对永磁超环面电机系统参数的依赖性,研究了引入扩张状态观测器(ESO)的永磁超环面电机无模型预测电流控制(MFPCC-ESO)策略。根据永磁超环面电机的复合转子结构,引入自转运动影响系数与磁势系数,在旋转坐标系下建立该电机的时变数学模型;利用永磁超环面电机系统的输入与输出,建立该电机具有时变比例因子的超局部模型,同时引入ESO对超局部模型的干扰部分进行实时估计,并利用朱利稳定判据证明了ESO的稳定性;结合延时补偿的DPCC预测得到参考电压矢量,从而实现永磁超环面电机的MFPCC-ESO策略。对参数匹配和失配下永磁超环面电机MFPCC-ESO策略与DPCC策略进行对比分析,仿真结果表明:MFPCC-ESO策略下的永磁超环面电机具有优越的动态和稳态性能及强鲁棒性,同时该控制策略还能有效降低永磁超环面电机的输出波动。

永磁同步电机改进积分型时变滑模控制

为了提高永磁同步电机的控制性能,改善对于电机的控制方法,针对永磁同步电机的积分滑模控制进行研究,首先,提出积分滑模控制在运行中遭遇未知干扰后易产生转速超调的问题。然后,通过定义自调节的积分初值来消除运行过程中因积分累积所产生的超调,改善转速超调问题。其次,为了提高滑模控制在电机整个运动的全局阶段的收敛性,提出基于预测在线寻优的时变滑模控制,通过预测控制变量来选出当前时刻的最优滑模面,使得状态变量可以更快收敛到滑模面,进一步降低转速误差,提高系统的控制精度与控制速度。最后,建立扩张状态观测器来观测系统的未知干扰,对控制器进行补偿,提高整个控制系统的鲁棒性,并且通过仿真和实验验证了所提出方法的有效性。

基于多阶反馈重构的微电网端口变换器自抗扰策略

直流微电网低压负载侧电能稳定供应是新型电力系统中新能源有效消纳的重要保障。针对微电网供能枢纽变换器受扰情况下输出不稳定的问题,提出了一种观测器状态变量重构补偿的改进型自抗扰策略。首先,通过剖析自抗扰框架下无法避免的结构问题,推导出观测误差精准范式,并对扰动观测变量进行重构补偿,实现对总扰动的快速跟踪和消除。然后,进一步对改进策略在稳定性能、跟踪性能、抗扰性能、鲁棒性能4个维度进行理论分析,验证了该策略的正确性与有效性。最后,利用数字仿真和物理实验模拟实际工况进行对比分析,验证了该策略在微电网系统多种内外不确定扰动下均具有较好的动态性能。

基于PFC电路直流纹波抑制的二阶自适应滑模控制器设计

文中提出一种背靠背型中性点钳位式(back-to-back neutral point clamped,BT-NPC)功率因数校正(power factor correction,PFC)电路,并设计二阶自适应滑模控制方法用于提高电路鲁棒性与降低电流谐波含量。首先,分析所提三电平PFC电路工作特性,推导该电路的等效模型及其模态扰动,并分析模态扰动量对其工作特性的影响;然后,结合高阶滑模理论与自适应控制两者的优点,设计二阶自适应滑模控制器,既使电路具有变结构控制的良好鲁棒性,又能最大限度的减小控制震颤。同时,基于电流带宽分析,设计比例谐振控制器补偿交流电流与工频相位,并设计基于扩张状态观测器的直流电压采样滤波方法,用于消除二倍频纹波造成的电流谐波影响。最后,基于BT-NPC电路,搭建220 V/50 Hz、1 kW/400 V的实验样机,实验结果验证所提变换器的可行性和控制方法的有效性。