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.

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.

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.

Adaptive RISE Control of Winding Tension with Active Disturbance Rejection

A winding system is a time-varying system that considers complex nonlinear characteristics,and how to control the stability of the winding tension during the winding process is the primary problem that has hindered development in this field in recent years.Many nonlinear factors affect the tension in the winding process,such as friction,structured uncertainties,unstructured uncertainties,and external interference.These terms severely restrict the tension tracking performance.Existing tension control strategies are mainly based on the composite control of the tension and speed loops,and previous studies involve complex decoupling operations.Owing to the large number of calculations required for this method,it is inconvenient for practical engineering applications.To simplify the tension generation mechanism and the influence of the nonlinear characteristics of the winding system,a simpler nonlinear dynamic model of the winding tension was established.An adaptive method was applied to update the feedback gain of the continuous robust integral of the sign of the error(RISE).Furthermore,an extended state observer was used to estimate modeling errors and external disturbances.The model disturbance term can be compensated for in the designed RISE controller.The asymptotic stability of the system was proven according to the Lyapunov stability theory.Finally,a comparative analysis of the proposed nonlinear controller and several other controllers was performed.The results indicated that the control of the winding tension was significantly enhanced.

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.

基于自适应终端滑模的高速列车迭代学习速度控制

针对高速列车的速度追踪控制问题,充分利用列车运行的重复性,考虑工程应用中迭代初始状态不同和复杂的外部环境,提出一种基于线性扩张状态观测器(LESO)的自适应非奇异终端滑模迭代学习控制算法,使系统在任意迭代初值时均能保证追踪精度。提出一种时变非奇异终端滑模面以抑制初态误差影响,采用LESO估计并补偿列车扰动,设计自适应迭代更新律估计LESO的观测误差,设计全饱和自适应迭代控制律计算输入并将其约束于允许范围内。建立类Lyapunov的复合能量函数,通过严格的数学分析证明其迭代域的差分负定性和有界性,证明所设计的时变滑模面可实现渐进收敛,并证明追踪误差在滑模面内可在有限时间内收敛至平衡点。将本文提出的算法与滑模控制、变增益迭代学习控制、自抗扰控制等算法进行比较。仿真结果表明:无论是否存在迭代初始误差,在相同的条件下,本文提出的算法较其他算法具有更强的抗干扰能力,速度追踪精度提高90%及以上,停车误差可迭代收敛至001 m。

基于自适应ST算法的机器人轨迹跟踪研究

为实现更精确地机器人轨迹跟踪控制,提高系统的抗干扰能力,研究提出基于自适应搜索和追踪算法的机器人轨迹跟踪方法,先建立机器人模型和跟踪轨迹,再采用支持实时动态参数调整的自适应ST算法。实验表明,三种不同的控制方法均能够使水下机器人达到所需的位置和姿态。其中,指令滤波控制方法表现出更快的平均收敛时间,仅为1.3秒。结果表明,研究所提方法能实现更短的调节时间,减小轨迹跟踪误差,同时保持稳定性和抗干扰性。

基于扩张状态观测器的永磁同步电机自适应鲁棒控制

永磁同步电机无传感器控制具有简化机械结构、降低成本和延长使用寿命等优点,然而其跟踪性能受不可测系统状态和干扰的观测精度影响。为了提高其跟踪精度,提出了一种结合转子位置、转速和干扰观测器的自适应鲁棒控制方法。首先,通过滑模观测器获得反电动势估计;然后,引入自适应律对参数化不确定性进行在线估计,形成以转子位置误差为输入的扩张状态观测器,提高了观测精度;最后,基于不确定性项估计和干扰观测值,设计转速跟踪误差的积分滑模面和相应的自适应滑模控制器,保证了电机系统的控制性能。仿真和实验结果验证了所提方法的有效性。

测量噪声下的高超声速飞行器组合观测鲁棒控制

针对高超声速飞行器大包络飞行时,风场等外部干扰和测量噪声导致控制系统性能变差甚至失稳的问题,提出了一种基于状态观测的高超声速飞行器鲁棒控制策略。考虑噪声和外部干扰影响下系统状态受扰的问题,设计了扩张状态观测器(ESO)和自适应Kalman滤波器(AKF)的特殊组合,在统计特性未知的噪声和外部干扰影响下准确估计系统状态。其中,自适应Kalman滤波器用于滤除噪声,为扩张状态观测器提供不受噪声影响的状态估计,扩张状态观测器连续为自适应Kalman滤波器提供外部干扰估计。基于系统状态估计设计线性高斯二次型控制器,实现高超声速飞行器精确轨迹跟踪。最后,通过仿真验证了该方法在测量噪声及风干扰影响下的鲁棒跟踪能力。

基于特征模型的5阶关节伺服系统扰动补偿策略

针对工业机器人关节伺服系统负载时变和模型不确定性问题,提出将线性扩张状态观测器和基于特征模型的全系数自适应控制相结合的控制策略。建立双惯量柔性关节动力学模型并得到关节伺服系统5阶扩张状态方程。基于该模型设计5阶线性扩张状态观测器,通过该观测器估计系统总扰动并进行扰动补偿,并证明观测器收敛性。基于特征建模的方法,通过实验数据和梯度下降法对特征参数进行辨识,并基于参数值设计全系数自适应控制律,将该控制律结合线性扩张状态观测器设计一种控制策略,对系统进行精确控制。实验结果表明,新的控制策略使系统在变负载扰动工况下的定位精度达到0.003°,正弦信号跟踪误差保持在0.92°以内,系统具有较强的鲁棒性和控制精度。

基于自适应线性扩张状态观测器的双有源桥变换器无模型预测电压控制

针对模型预测控制算法参数依赖性问题以及传统扰动观测器应用于双有源桥变换器中存在估计补偿滞后于外部扰动、固定增益无法适应外部宽范围干扰变化等缺点,提出一种基于自适应线性扩张状态观测器的无模型预测电压控制策略。首先,结合预测控制与无模型控制方法构建双有源桥变换器的电压预测超局部模型,代替传统物理模型,降低参数依赖;其次,设计线性扩张状态观测器对超局部模型中动态部分进行反馈补偿,提高控制精度。同时在线拟合电压误差趋势,自适应调整观测器带宽,实现超前补偿;最后,设计成本函数,求解最优移相比,实现无模型预测电压控制。实验结果验证了该方法在提升系统鲁棒性和动态性方面的有效性。

燃烧后CO_(2)捕集系统的复合无模型自适应控制

燃烧后CO_(2)捕集(PCC)系统作为一种有效的碳减排技术,其优化控制对提高CO_(2)捕集效率和降低能耗具有重要意义。针对PCC系统的控制问题,提出一种复合无模型自适应控制(MFAC)方法,旨在解决传统控制方法依赖精确模型、难以适应系统参数变化和不确定性的问题。该方法将扩张状态观测器引入MFAC中,利用扩张状态观测器估计系统总扰动,提高系统的跟踪和抗干扰能力。进行不同控制方案下的PCC系统对比仿真,其中,在跟踪CO_(2)捕集率设定值的仿真中,复合MFAC展现出了良好的跟踪性能,上升时间95.69 s,比传统的MFAC快4.65 s,较比例-积分-微分(PID)控制快78.02 s。在抗扰性能的对比仿真中,复合MFAC在受到扰动时所产生的偏差最小,绝对误差积分和平方误差积分的数值均小于MFAC和PID控制器,具有良好的抗干扰能力。仿真验证了所提出控制方案的有效性和适用性。

基于ESO的分拣并联机器人无标定视觉伺服自适应滑模控制

针对无标定分拣并联机器人需获取精确图像雅可比矩阵的问题,同时为克服图像检测误差、建模误差及外部干扰对无标定视觉伺服系统的影响,提出一种基于扩张状态观测器(extended state observer,ESO)的分拣并联机器人无标定视觉伺服自适应滑模控制方法。通过将表征机器人图像空间与任务空间映射关系的图像雅可比矩阵与系统不确定项集总到同一通道的状态方程,引入ESO对分拣并联机器人视觉伺服系统的集总不确定性进行在线估计,设计一种基于扩张状态观测器的自适应积分滑模控制器,并通过设计自适应律动态调整滑模控制切换增益,以提高视觉伺服系统精度,同时达到抑制滑模控制抖振的效果。采用Lyapunov稳定性理论证明该控制方法的稳定性,最后通过仿真实验验证了所提出视觉伺服自适应滑模控制方法的可行性和有效性。

Model-driven full system dynamics estimation of PMSM-driven chain shell magazine

Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is proposed to estimate the unmeasured states and disturbance, in which the model parameters are adjusted in real time. Theoretical analysis shows that the estimation errors of the disturbances and unmeasured states converge exponentially to zero, and the parameter estimation error can be obtained from the extended state. Then, based on the extended state of the AESO, a novel parameter estimation law is designed. Due to the convergence of AESO, the novel parameter estimation law is insensitive to controllers and excitation signal. Under persistent excitation(PE) condition, the estimated parameters will converge to a compact set around the actual parameter value. Without PE signal, the estimated parameters will converge to zero for the extended state. Simulation and experimental results show that the proposed method can accurately estimate the unmeasured states and disturbance of the chain shell magazine, and the estimated parameters will converge to the actual value without strictly continuous PE signals.

Command filtered integrated estimation guidance and control for strapdown missiles with circular field of view

In this paper,an integrated estimation guidance and control(IEGC)system is designed based on the command filtered backstepping approach for circular field-of-view(FOV)strapdown missiles.The threedimensional integrated estimation guidance and control nonlinear model with limited actuator deflection angle is established considering the seeker's FOV constraint.The boundary time-varying integral barrier Lyapunov function(IBLF)is employed in backstepping design to constrain the body line-of-sight(BLOS)in IEGC system to fit a circular FOV.Then,the nonlinear adaptive controller is designed to estimate the changing aerodynamic parameters.The generalized extended state observer(GESO)is designed to estimate the acceleration of the maneuvering targets and the unmatched time-varying disturbances for improving tracking accuracy.Furthermore,the command filters are used to solve the"differential expansion"problem during the backstepping design.The Lyapunov theory is used to prove the stability of the overall closed-loop IEGC system.Finally,the simulation results validate the integrated system's effectiveness,achieving high accuracy strikes against maneuvering targets.

异步电动机无速度传感器模型参考自适应控制

针对异步电机运行过程中参数易发生变化的问题,基于扩张状态观测器的思想,将可变的电机参数作为扰动项,设计一种带有反馈补偿的转子磁链观测器,并结合模型参考自适应系统实现异步电机无传感器矢量控制。将此转子磁链观测器作为模型参考自适应系统中的参考模型,克服电压型磁链观测器的纯积分漂移问题。仿真结果表明:在电机定转子互感发生20%偏置的情况下,所提算法转速辨识误差最大为0.3%、转速超调量仅为0.83%、转矩脉动减小了38%,具有良好的转速辨识精度和抗扰动能力。

基于级联扩展状态观测器和新型滑模的PMSM控制

为了缩短永磁同步电机的响应时间,提高系统的动态性能、稳态精度和系统鲁棒性,设计了一种级联扩展状态观测器和自适应非奇异快速终端滑模控制相结合的控制系统。首先,基于电机数学模型,建立了级联扩展状态观测器,能够准确地观测和补偿扰动,优化了系统的动态性能、稳态精度和鲁棒性;其次,在速度环设计了新型非奇异快速终端滑模面和趋近率,能够有效地抑制PI控制中的转速超调和抖振现象,实现快速收敛;在控制器设计中,考虑到观测器估计误差是未知的,因此设计了一种自适应律,用以调整未知的估计参数;最后,对所提出的控制策略进行了严格的稳定性分析。仿真结果表明,与传统控制方法相比,转速超调抑制能力提升为9.6%,同时转速快速响应能力提升0.045 s,具有优异的速度动态性能和抗干扰能力,提高了系统的性能。

基于改进扩展状态观测器的永磁同步电动机的自适应滑模控制

永磁同步电动机运行过程中存在负载扰动和参数摄动等问题,从而影响永磁同步电动机的转速。为提高永磁同步电动机的抗干扰性,提出了基于改进扩展状态观测器的自适应滑模控制策略。首先,设计改进的扩展状态观测器,根据扰动的大小动态调整扩展状态观测器增益,提高了系统的响应速度。其次,设计自适应滑模控制器,通过代价函数评定出最优滑模面系数,并进一步设计自适应滑模面,提高系统的收敛速度。最后,通过引入自适应律,在线估计扰动的观测误差。仿真结果表明:所提出的方法能够有效克服负载扰动和参数摄动对永磁同步电动机转速的影响,提高了系统的鲁棒性。

Integrated guidance and control of guided projectile with multiple constraints based on fuzzy adaptive and dynamic surface

Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic characteristics,and multiple constraints,such as impact angle,limited measurement of line of sight(LOS)angle rate and nonlinear saturation of canard deflection.Initially,a strict feedback cascade model of IGC in longitudinal plane was established,and extended state observer(ESO)was designed to estimate LOS angle rate and uncertain disturbances with unknown boundary inside and outside of system,including aerodynamic parameters perturbation,target maneuver and model errors.Secondly,aiming at zeroing LOS angle tracking error and LOS angle rate in finite time,a nonsingular terminal sliding mode(NTSM)was designed with adaptive exponential reaching law.Furthermore,combining with dynamic surface,which prevented the complex differential of virtual control laws,the fuzzy adaptive systems were designed to approximate observation errors of uncertain disturbances and to reduce chatter of control law.Finally,the adaptive Nussbaum gain function was introduced to compensate nonlinear saturation of canard deflection.The LOS angle tracking error and LOS angle rate were convergent in finite time and whole system states were uniform ultimately bounded,rigorously proven by Lyapunov stability theory.Hardware-in-the-loop simulation(HILS)and digital simulation experiments both showed FADS provided guided projectile with good guidance performance while striking targets with different maneuvering forms.

Adaptive backstepping control for levitation system with load uncertainties and external disturbances

To explore the precise dynamic response of the levitation system with active controller, a maglev guide way-electromagnet-air spring-cabin coupled model is derived firstly. Based on the mathematical model, it shows that the inherent nonlinearity, inner coupling, misalignments between the sensors and actuators, load uncertainties and external disturbances are the main issues that should be solved in engineering. Under the assumptions that the loads and external disturbance are measurable, the backstepping module controller developed in this work can tackle the above problems effectively. In reality, the load is uncertain due to the additions of luggage and passengers, which will degrade the dynamic performance. A load estimation algorithm is introduced to track the actual load asymptotically and eliminate its influence by tuning the parameters of controller online. Furthermore,considering the external disturbances generated by crosswind, pulling motor and air springs, the extended state observer is employed to estimate and suppress the external disturbance. Finally, results of numerical simulations illustrating closed-loop performance are provided.