Robust Adaptive Gain Higher Order Sliding Mode Observer Based Control-constrained Nonlinear Model Predictive Control for Spacecraft Formation Flying

This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.

Decentralized model reference adaptive sliding mode control based on fuzzy model

A new design scheme of decentralized model reference adaptive sliding mode controller for a class of MIMO nonlinear systems with the high-order interconnections is propcsed. The design is based on the universal approximation capability of the Takagi - Seguno （T-S） fuzzy systems. Motivated by the principle of certainty equivalenteontrol, a decentralized adaptive controller is designed to achieve the tracking objective without computafion of the T-S fuzz ymodel. The approach does not require the upper bound of the uncertainty term to be known through some adaptive estimation. By theoretical analysis, the closed-loop fuzzy control system is proven to be globally stable in the sense that all signalsinvolved are bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.

Modeling and Robust Backstepping Sliding Mode Control with Adaptive RBFNN for a Novel Coaxial Eight-rotor UAV

This paper focuses on the robust attitude control of a novel coaxial eight-rotor unmanned aerial vehicles (UAV) which has higher drive capability as well as greater robustness against disturbances than quad-rotor UAV. The dynamical and kinematical model for the coaxial eight-rotor UAV is developed, which has never been proposed before. A robust backstepping sliding mode controller (BSMC) with adaptive radial basis function neural network (RBFNN) is proposed to control the attitude of the eightrotor UAV in the presence of model uncertainties and external disturbances. The combinative method of backstepping control and sliding mode control has improved robustness and simplified design procedure benefiting from the advantages of both controllers. The adaptive RBFNN as the uncertainty observer can effectively estimate the lumped uncertainties without the knowledge of their bounds for the eight-rotor UAV. Additionally, the adaptive learning algorithm, which can learn the parameters of RBFNN online and compensate the approximation error, is derived using Lyapunov stability theorem. And then the uniformly ultimate stability of the eight-rotor system is proved. Finally, simulation results demonstrate the validity of the proposed robust control method adopted in the novel coaxial eight-rotor UAV in the case of model uncertainties and external disturbances. © 2014 Chinese Association of Automation.

Adaptive Robust Motion Trajectory Tracking Control of Pneumatic Cylinders with LuGre Model-based Friction Compensation

Friction compensation is particularly important for motion trajectory tracking control of pneumatic cylinders at low speed movement. However, most of the existing model-based friction compensation schemes use simple classical models, which are not enough to address applications with high-accuracy position requirements. Furthermore, the friction force in the cylinder is time-varying, and there exist rather severe unmodelled dynamics and unknown disturbances in the pneumatic system. To deal with these problems effectively, an adaptive robust controller with LuGre model-based dynamic friction compensation is constructed. The proposed controller employs on-line recursive least squares estimation（RLSE） to reduce the extent of parametric uncertainties, and utilizes the sliding mode control method to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. In addition, in order to realize LuGre model-based friction compensation, the modified dual-observer structure for estimating immeasurable friction internal state is developed. Therefore, a prescribed motion tracking transient performance and final tracking accuracy can be guaranteed. Since the system model uncertainties are unmatched, the recursive backstepping design technology is applied. In order to solve the conflicts between the sliding mode control design and the adaptive control design, the projection mapping is used to condition the RLSE algorithm so that the parameter estimates are kept within a known bounded convex set. Finally, the proposed controller is tested for tracking sinusoidal trajectories and smooth square trajectory under different loads and sudden disturbance. The testing results demonstrate that the achievable performance of the proposed controller is excellent and is much better than most other studies in literature. Especially when a 0.5 Hz sinusoidal trajectory is tracked, the maximum tracking error is 0.96 mm and the average tracking error is 0.45 mm. This paper constructs an adaptive robust controller which can compensate the friction force in the cylinder.

New adaptive quasi-sliding mode control for nonlinear discrete-time systems

A new adaptive quasi-sliding mode control algorithm is developed for a class of nonlinear discrete-time systems, which is especially useful for nonlinear systems with vaguely known dynamics. This design is model-free, and is based directly on pseudo-partial-derivatives derived on-line from the input and output information of the system using an improved recursive projection type of identification algorithm. The theoretical analysis and simulation results show that the adaptive quasi-sliding mode control system is stable and convergent.

Time delay control of hydraulic manipulators with continuous nonsingular terminal sliding mode

For the position tracking control of hydraulic manipulators,a novel method of time delay control(TDC) with continuous nonsingular terminal sliding mode(CNTSM) was proposed in this work.Complex dynamics of the hydraulic manipulator is approximately canceled by time delay estimation(TDE),which means the proposed method is model-free and no prior knowledge of the dynamics is required.Moreover,the CNTSM term with a fast-TSM-type reaching law ensures fast convergence and high-precision tracking control performance under heavy lumped uncertainties.Despite its considerable robustness against lumped uncertainties,the proposed control scheme is continuous and chattering-free and no pressure sensors are required in practical applications.Theoretical analysis and experimental results show that faster and higher-precision position tracking performance is achieved compared with the traditional CNTSM-based TDC method using boundary layers.

Fixed-time adaptive model reference sliding mode control for an air-to-ground missile

This paper addresses the fixed-time adaptive model reference sliding mode control for an air-to-ground missile associated with large speed ranges, mismatched disturbances and un-modeled dynamics. Firstly, a sliding mode surface is developed by the tracking error of the state equation and the model reference state equation with respect to the air-to-ground missile. More specifically,a novel fixed-time adaptive reaching law is presented. Subsequently, the mismatched disturbances and the un-modeled dynamics are treated as the model errors of the state equation. These model errors are estimated by means of a fixed-time disturbance observer, and they are also utilized to compensate the proposed controller. Therefore, the fixed-time controller is obtained by an adaptive reaching law and a fixed-time disturbance observer. Closed-loop stability of the proposed controller is established. Finally, simulation results including Monte Carlo simulations, nonlinear six-DegreeOf-Freedom(6-DOF) simulations and different ranges are presented to demonstrate the efficacy of the proposed control scheme.

Study of Model-free Adaptive Data-driven SMC Algorithm

A kind of adaptive sliding model control algorithm is developed to solve and improve the mathematical model dependency and un-modeled dynamics of a controlled system. The control strategy derived from a kind of data-driven control method in essence, thereby the input and output data are utilized by the controller with no information about the control system model. Theoretical analysis proves that this proposed control algorithm can improve the utilization of the estimated pseudo partial derivative information and accelerate the velocity of the convergence. The stability of the control system is further verified by rigorous mathematical analysis. This new discrete-time nonlinear systems model-free control algorithm obtained better control performance through the simulations for the linear motor position and the information tracking speed, which also achieved robust and accurate traceability.

Bio-inspired Backstepping Adaptive Sliding Mode Control for Parallel Mechanism with Actuation Redundancy

This paper presents a bio-inspired backstepping adaptive sliding mode control strategy for a novel 3 degree of freedom(3-DOF) parallel mechanism with actuation redundancy. Based on the kinematic model and the dynamic model, a sliding mode controller is designed to assure the tracking performance, and an adaptive law is introduced to approximate the system uncertainty including parameters variation, external disturbances and un-modeled part. Furthermore, a bio-inspired model is introduced to solve the inherent chattering problem of sliding mode control and provide a chattering free control. The simulation and experimental results testify that the proposed bio-inspired backstepping adaptive sliding mode control can achieve better performance(the tracking accuracy,robustness, response speed, etc.) than the conventional slide mode control.

A novel MPTC sensorless control strategy for ANFTSMC with ESO to control PMSM

Aiming at the problem that the traditional control strategy of permanent magnet synchronous motor(PMSM)for electric vehicles has low control performance,a novel adaptive non-singular fast terminal sliding mode control(ANFTSMC)model predictive torque control(MPTC)strategy is proposed.A new adaptive exponential approach rate is designed,and the traditional switching function sgn()is replaced by the hyperbolic tangent function tanh().A new ANFTSMC with extended state observer(ESO)is constructed as the speed regulator of the system,and ESO can observe disturbances.This improved method weakens chattering and improves the robustness of the system.To realize sensorless control of the speed control system,an ESO speed observer based on tanh(Fal)is constructed.Compared with the traditional ESO based on Fal function,the observation error is smaller,and the observation accuracy is higher.Finally,aiming at the model predictive torque control strategy used,a new objective function construction method is proposed,which avoids the design of weight coefficient,and the traditional voltage vector selection method is improved and optimized,which reduces the calculation amount of the algorithm.

考虑磁链变化率的永磁同步电机失磁故障复合容错控制

针对永磁同步电机(PMSM)失磁故障中磁链变化较快,近似认为磁链变化率为0会导致传统PMSM失磁容错控制方法性能受限的问题,本文提出一种基于智能比例积分微分的无模型超螺旋滑模复合容错控制(iPID-MFSTSMC)方法。首先,构建考虑永磁体磁链变化量的PMSM失磁故障数学模型,根据这一模型设计了磁链滑模观测器,实现了对于磁链及其变化率的观测。此外,针对快速变化的负载转矩设计了负载转矩导数滑模观测器。然后,基于磁链及其变化率、负载转矩导数的观测,设计了iPID无模型容错控制方法,该方法采用超螺旋滑模算法对观测误差及其他扰动进行抑制,改善了动态性能且降低了控制器参数的设计难度。利用Lyapunov稳定性定理证明了所设计容错控制方法的稳定性,并给出了参数的设计条件。最后,在磁链以及负载转矩快速变化工况下,通过仿真和实验分析表明,该方法可以有效减少系统抖振并降低超调量。

运行工况自适应的风储系统双层功率平滑策略

针对风电并网带来的功率波动问题,提出一种运行工况自适应的风电-混合储能系统双层功率平滑策略。在上层,考虑风储系统并网功率波动和储能运行状态,利用无模型自适应控制动态跟踪经滑动平均算法得到的并网参考功率,生成混合储能总功率任务;在下层,考虑储能介质的技术特性,利用模糊控制动态调节经变分模态分解确定的混合储能总功率任务的频率分界点,完成功率的自适应分配。算例分析表明:所提策略可以自适应平抑多工况下的风电功率波动,实现混合储能各介质间功率的合理分配。

PMSM无模型超螺旋快速积分终端滑模控制

针对永磁同步电机运行过程中因模型不确定、参数摄动和外部扰动等因素的影响,从而导致驱动系统性能下降的问题,提出一种新型控制策略。首先,为减少对系统数学模型的依赖,构建了一个新的超局部模型,用于描述永磁同步电机的转速环。其次,基于转速环的新型超局部模型,结合一种新型积分终端滑模面和改进超螺旋控制律来设计新型无模型超螺旋快速积分终端滑模控制器,实现了对转速的精确控制。再次,采用非奇异快速终端滑模面和双幂次趋近律设计改进扩展非奇异终端滑模扰动观测器,通过精确观测和前馈补偿未知扰动,有效地抑制参数摄动和外部扰动,增强了系统鲁棒性,提高系统的动态性能和稳态性能。最后,通过与传统控制方法的仿真和实验对比,证实所提算法转速抗超调能力提升为0.412 5%,转矩快速响应能力提升0.013 s。结果表明当存在未知扰动时,所提方法具有较强的鲁棒性和良好的抗干扰性。

基于改进型ADRC的PMSM无位置传感器控制

针对永磁同步电机矢量控制中传统速度环PI调节器存在协调性与抗干扰能力差的问题,引入自抗扰控制(ADRC)替代速度环PI调节器,考虑到线性ADRC中PD控制存在性能较差的缺点,选择滑模控制代替PD控制,提出改进型ADRC控制方法;同时采用模型参考自适应系统(MRAS)取代传统机械式位置传感器对电机的转子位置进行检测,实现了永磁同步电机无位置传感器控制。通过采用改进型ADRC与MRAS相结合的控制方法,电机控制系统具有了更好的动态响应速度和抗干扰能力。最后通过永磁同步电机对拖实验平台对电机在转速恒定负载突变和带载启动转速突变两种工况下进行实验,验证了改进型ADRC与MRAS相结合的控制策略的有效性。

无模型自适应滑模控制的微波加热过程温度控制

微波加热模型具有无限维、非线性和时变等特点,导致控制器难于设计和实现。针对此问题,提出了一种适用于微波加热过程的无模型自适应滑模控制方法。首先,对微波加热过程传热数学模型进行分析,建立了微波加热过程输入功率与温度之间的全格式动态线性化数据模型。然后,根据该数据模型设计了无模型自适应滑模控制器,并给出了数据模型中相关未知时变参数和未知干扰的估计算法。最后,利用COMSOL和MATLAB进行仿真,仿真结果验证了所提控制方法的有效性。

基于ESO的PMSM无模型快速超螺旋滑模预测控制

为提高表贴式永磁同步电机(Surface permanent magnet synchronous motor,SPMSM)在参数变化和外部扰动下的鲁棒性,提出一种基于扩张状态观测器的无模型快速超螺旋滑模预测控制方法。首先,建立SPMSM参数摄动时的新型超局部模型。其次,采用改进的超螺旋算法作为辅助控制率设计转速环无模型超螺旋滑模反馈控制器,同时利用复合的扩张扰动观测器估计超局部模型中的未知部分,并通过Lyapunov稳定性理论证明了控制器和观测器的稳定性。电流环应用无差拍电流预测控制策略,结合扩张状态观测器对扰动量进一步估计并进行前馈补偿,使电流环具有更好的动态响应和更小的谐波分量。仿真试验结果表明,所提方法可有效提高系统响应速度,改善SPMSM在发生参数漂移和外部扰动下的暂稳态性能,降低电流总谐波畸变率,提升系统鲁棒性和抗干扰性能。

基于ESMDO的级联双模型永磁同步电机鲁棒控制

考虑永磁同步电机调速控制系统中传统电流环数学模型的耦合非线性,结合无模型控制的优势,提出了一种基于扩展滑模观测器(extended sliding mode disturbance observer,ESMDO)的级联双模型永磁同步电机鲁棒控制方法,有效解决了传统PI控制器的鲁棒性差、动态响应慢的问题。首先,在转速环利用传统永磁同步电机数学模型设计了引入自校正开关增益的离散滑模转速控制器,通过离散的ESMDO观测综合扰动项并进行补偿。然后,在考虑电机参数的不确定性和外部扰动的情况下,建立了电流环超局部模型,设计了基于离散的ESMDO的无模型无差拍电流预测控制器。最后,以PI控制为对比方法进行仿真分析,仿真结果表明了所提方法的可行性与有效性。

基于ESO的永磁同步电机自耦合无模型滑模控制

为了解决基于模型的永磁同步电机调速系统易受外部负载扰动影响的问题,实现转速的高性能控制,提出自耦合无模型滑模级联式统一化控制策略。考虑参数不确定性以及内外扰动,建立了永磁同步电机双环超局部矢量模型。在传统无模型滑模控制器的基础上,通过选取比例双重积分滑模面设计了级联式无模型滑模速度、电流控制器,有效减小了转速的稳态误差。通过设计速度因子解决了控制器比例积分增益整定不合理的问题,同时采用扩张状态观测器对超局部模型中的未知部分进行估计并进行前馈补偿,设计了基于扩张状态观测器的永磁同步电机自耦合无模型滑模控制调速系统。通过与PI控制及传统无模型滑模控制的对比仿真与实验分析,验证了所提控制策略的可行性与有效性。

永磁同步电机无模型自适应滑模补偿预测控制

针对在永磁同步电机矢量控制系统中应用模型预测控制方法设计控制器时依赖电机数学模型参数,当电机运行过程中参数变化时,引起控制器参数与电机参数失配,导致系统控制性能降低。提出一种无模型自适应预测控制方法,利用系统输入输出数据和时变的伪偏导数建立预测模型;又由于无模型自适应预测控制方法没有反馈校正环节,易受外部扰动的影响,设计一种新型高阶滑模补偿器作为校正部分,以提高控制系统的鲁棒性且抑制滑模自身的抖振,最后MATLAB仿真验证了无模型自适应高阶滑模补偿预测控制方法的优越性。