永磁同步电机有限时间预设性能控制

为实现扰动作用下对永磁同步电机角位置伺服系统的高瞬态和稳态跟踪性能控制,本文提出一种具有预设性能约束的有限时间控制方法.首先,设计扰动观测器实现对负载力矩扰动的估计与补偿.其次,引入有限时间预设性能函数以保证角跟踪误差的动态性能,并通过可逆变换将受不等式约束的角位置跟踪误差转换为等效的无约束误差形式.然后,将有限时间指...     

一类机械臂系统自适应有限时间有界H∞跟踪控制

考虑一种电机驱动的单连杆机械臂系统在受到输出约束时的自适应有限时间H∞跟踪控制问题.一个有限时间有界H∞性能的新概念被提出,并结合障碍Lyapunov函数(BLF)、神经网络自适应技术、有限时间控制理论和H∞控制理论,提出了一种该系统在输出受限条件下的自适应神经有限时间有界H∞跟踪控制器设计方法,避免了许多有限时间控制...     

A novel robust adaptive second-order sliding mode tracking control technique for uncertain dynamical systems with matched and unmatched disturbances

This paper investigates a robust adaptive second-order sliding mode control method for tracking problem of a class of uncertain linear systems with matched and unmatched disturbances. The fundamental idea of the suggested control method is that the discontinuous sign function is used for the time-derivative of the control signal and hence the smooth control input achieved after an integration process is continuous and removes the chattering problem. Using a PID sliding surface, the finite-time convergence of output tracking errors is obtained. The adaptive gain-tuning control law removes the necessity of gaining information about the upper bounds of the external disturbances. The control system is in the sliding mode and then, tracking errors converge to the origin in a finite time under the presence of the external disturbances. Simulation results on an uncertain numerical system and a turntable servo-system are presented to indicate the effectiveness and feasibility of the proposed scheme.     

Barrier function based finite-time tracking control for a class of uncertain nonlinear systems with input saturation

In this article, a novel robust finite-time tracking control scheme is proposed for a class of uncertain nonlinear systems subject to the model uncertainty, external disturbance, and input saturation. A barrier function based disturbance observer (BFDO) with finite-time convergence performance is developed to estimate the non-smooth nonlinear compound disturbance, which includes the uncertainty, disturbance of system and input saturation. In addition, an adaptive continuous nonsingular terminal sliding mode controller, based on the barrier function and the estimate of the BFDO is developed. The Lyapunov stability and finite-time convergence of the proposed control scheme are proved. The effectiveness and performance advantage of the proposed control scheme is demonstrated by numerical simulations and comparison with existing works.     

Nonlinear adaptive speed control of a permanent magnet synchronous motor: A perturbation estimation approach

This paper presents a nonlinear adaptive control (NAC) scheme for the speed regulation of a permanent magnet synchronous motor (PMSM) based on perturbation estimation and feedback linearizing control. All PMSM system’s unknown nonlinearities, parameter uncertainties, and external disturbances including unknown time-varying load torque disturbance, are defined as lumped perturbation terms, which are estimated by designing perturbation observers. The estimates are used to adaptively compensate the real perturbations and achieve adaptive feedback linearizing control of the original nonlinear system. The proposed control scheme does not require accurate system model and full state feedback. Stability of the close-loop system with proposed NAC is investigated via Lyapunov theory, and the effectiveness of proposed NAC scheme is verified through both simulation and experimental studies. Both simulation and experimental results show that the proposed NAC scheme can provide less regulation error in speed tracking, better dynamic performance and robustness against parameter uncertainties and load torque disturbance, compared with conventional vector control and load torque estimated based control.     

具有外部扰动的PMSM系统的无模型自适应预测控制

针对于一类具有强耦合、负载不确定性和外界干扰的永磁同步电机(PMSM)系统,本文研究了基于无模型自适应预测控制(MFAPC)问题,并提出了一种新颖的MFAPC方案来实现有外界扰动的PMSM系统的速度追踪任务.所提出控制方案的主要优势在于仅使用了被控系统的输入/输出数据,并且对外界干扰具有较强的鲁棒性.此外,还讨论了闭环系统跟踪误差的收敛性以及有界输入有界输出的稳定性.最后,通过与传统的PI控制方案、原型无模型自适应控制(MFAC)方案的仿真结果相比较,验证了所提出MFAPC方案的有效性和优越性.     

非线性系统有限时间自适应动态面容错控制

针对具有传感器故障的一类严格反馈非线性系统, 提出一种有限时间自适应动态面容错控制策略. 考虑的 传感器故障包括: 固定偏差故障、漂移故障、精度下降及失效故障. 以反步法为主要设计依据, 利用模糊逻辑系统处 理模型中的未知函数. 该控制策略的显著优势在于结合有限时间理论、容错控制、模糊逻辑控制及动态面控制, 使 得系统无论发生故障与否, 均使得系统在原点处是半全局实际有限时间稳定, 同时保证系统的实际输出信号在有限 时间内跟踪期望信号, 且跟踪误差收敛于坐标原点的小邻域内. 另外, 通过采用动态面控制技术克服了传统反步法 中的计算复杂问题. 最后, 仿真算例证明了该设计方案的有效性.     

Adaptive dynamic surface control using disturbance observer for nonlinear systems with input saturation and output constraints

An adaptive dynamic surface control (DSC) approach using fuzzy approximation and nonlinear disturbance observer (NDO) for uncertain nonlinear systems in the presence of input saturation, output constraint and unknown external disturbances is proposed in this paper. The issue of input saturation is addressed by introducing a lower bound assumption on the approximation function of saturation. The output constraint is handled by introducing an appropriate barried Lyapunov function. The nonlinear disturbance observer (NDO) is employed to estimate the unknown unmatched disturbances. It is manifested that the ultimately bounded convergence of all the variables in the closed-loop system is guaranteed and the tracking error can be made farely small by tuning the design parameters. Finally, two simulation examples illustrate the effectiveness and feasibility of the proposed approach.     

高超声速飞行器有限时间饱和跟踪控制

针对高超声速飞行器纵向模型存在外界干扰和模型参数不确定性情形下的有限时间跟踪问题进行了研究分析.针对外界干扰上界已知,基于快速积分滑模理论,设计了有限时间快速积分滑模控制器.当外界干扰上界未知时,结合具有低通滤波器性能的自适应算法,通过引入辅助系统设计了实际有限时间自适应快速积分滑模控制器,能够处理输入饱和问题.对所设计的两个控制器利用李雅普诺夫理论给出了严格理论证明,得到整个闭环系统分别为有限时间稳定的、实际有限时间稳定的,并能够保证系统其它状态变量在较短的时间内趋于稳态值.对不同类型参考信号进行了数字仿真,进一步验证了所设计两个控制器的有效性和鲁棒性.     

基于干扰观测器的一类不确定仿射非线性系统有限时间收敛backstepping控制

针对一类不确定仿射非线性系统的跟踪控制问题,提出一种基于干扰观测器的有限时间收敛backstepping控制方法.为增强小脑模型(CMAC)泛化和学习能力,将非对称高斯函数和模糊理论相结合,给出非对称模糊CMAC结构,设计干扰观测器实现系统未知复合干扰在线准确逼近;基于非对称模糊CMAC干扰观测器,给出有限时间收敛backstepping控制器设计步骤,利用Lyapunov稳定理论证明闭环系统稳定性,其中采用非线性微分器获取虚拟控制量滤波和微分信息以避免backstepping设计中的微分“膨胀问题”,设计辅助系统修正因微分器带来的误差对系统跟踪性能影响,引入基于障碍型函数的自适应滑模鲁棒项抑制复合干扰估计偏差对跟踪误差的影响;将所提方法应用于无人机飞行控制仿真实验,结果表明所提方法的有效性.     

Approximation-based disturbance observer approach for adaptive tracking of uncertain pure-feedback nonlinear systems with unmatched disturbances

This paper presents an approximation-based nonlinear disturbance observer (NDO) methodology for adaptive tracking of uncertain pure-feedback nonlinear systems with unmatched external disturbances. Compared with existing control results using NDO for nonlinear systems in lower-triangular form, the major contribution of this study is to develop an NDO-based control framework in the presence of non-affine nonlinearities and disturbances unmatched in the control input. An approximation-based NDO scheme is designed to attenuate the effect of compounded disturbance terms consisting of external disturbances, approximation errors and control coefficient nonlinearities. The function approximation technique using neural networks is employed to estimate the unknown nonlinearities derived from the recursive design procedure. Based on the designed NDO scheme, an adaptive dynamic surface control system is constructed to ensure that all signals of the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a neighbourhood of the origin. Simulation examples including a mechanical system are provided to show the effectiveness of the proposed theoretical result.     

Robust adaptive integrated translation and rotation finite-time control of a rigid spacecraft with actuator misalignment and unknown mass property

This paper tackles the problem of integrated translation and rotation finite-time control of a rigid spacecraft with actuator misalignment and unknown mass property. Due to the system natural couplings, the coupled translational and rotational dynamics of the spacecraft is developed, where a thruster configuration with installation misalignment and unknown mass property are taken into account. By solving an equivalent designated trajectory tracking problem via backstepping philosophy, a robust adaptive integrated finite-time control scheme is proposed to enable the spacecraft track command position and attitude in a pre-determined time, despite of external disturbance, unknown mass property and thruster misalignment. The finite-time closed-loop stability is guaranteed within the Lyapunov framework. Two scenario numerical simulations demonstrate the effect of the designed controller.     

交会对接模拟系统姿态跟踪有限时间抗干扰控制

针对交会对接模拟系统的姿态同步问题,在存在扰动和系统不确定性的情况下,利用改进的快速非奇异终端滑模面和改进的自适应律设计两个有限时间抗干扰控制器.改进的自适应律保证了两个控制器的连续性和对干扰的鲁棒性,且第2个控制器能解决边界层理论存在的边界层内有限时间稳定性丢失的问题.李雅普诺夫理论推导和仿真结果表明,提出的两个控制器能保证系统的有限时间稳定性,系统能快速收敛到平衡点.     

Command filter-based finite-time adaptive tracking control for MIMO dynamic systems with external disturbances and prescribed performance constraints

This paper investigates command filter-based finite-time stability of multi-input multi-output (MIMO) dynamic systems with prescribed performance constraints and external disturbances. A novel finite-time differentiator is introduced into command filter-based control scheme, which improves transient performance of each subsystem. Meanwhile, disturbance observers are utilized to eliminate negative effects on control system caused by external disturbances. Furthermore, featured with a selected performance function, it can be guaranteed that tracking errors remain in prescribed performance region. Stability analysis of the proposed controller is presented by using a Lyapunov function including transformed filter errors, parameter errors of neural networks, and observed errors of lumped disturbances. Effectiveness of proposed control method is verified by a numerical example and a practical system of inverted pendulums, respectively.     

Distributed finite-time trajectory tracking control for multiple nonholonomic mobile robots with uncertainties and external disturbances

This paper investigates the distributed finite-time trajectory tracking control for a group of nonholonomic mobile robots with time-varying unknown parameters and external disturbances. At first, the tracking error system is derived for each mobile robot with the aid of a global invertible transformation, which consists of two subsystems, one is a first-order subsystem and another is a second-order subsystem. Then, the two subsystems are studied respectively, and finite-time disturbance observers are proposed for each robot to estimate the external disturbances. Meanwhile, distributed finite-time tracking controllers are developed for each mobile robot such that all states of each robot can reach the desired value in finite time, where the desired reference value is assumed to be the trajectory of a virtual leader whose information is available to only a subset of the followers, and the followers are assumed to have only local interaction. The effectiveness of the theoretical results is finally illustrated by numerical simulations.     

Robust tracking enhancement of robot systems including motordynamics: a fuzzy-based dynamic game approach

A robust tracking control design of robot systems including motor dynamics with parameter perturbation and external disturbance is proposed in this study via adaptive fuzzy cancellation technique. A minimax controller equipped with a fuzzy-based scheme is used to enhance the tracking performance in spite of system uncertainties and external disturbance. The design procedure is divided into three steps. At first, a linear nominal robotic control design is obtained via model reference tracking with desired eigenvalue assignment. Next, a fuzzy logic system is constructed and then tuned to eliminate the nonlinear uncertainties as possibly as it can to enhance the tracking robustness. Finally, a minimax control scheme is specified to optimally attenuate the worst-case effect of both the residue due to fuzzy cancellation and external disturbance to achieve a minimax tracking performance. In addition, an adaptive fuzzy-based dynamic game theory is introduced to solve the minimax tracking problem. The proposed method is appropriate for the robust tracking design of robotic systems with large parameter perturbation and external disturbance. A simulation example of a two-link robotic manipulator driven by DC motors is also given to demonstrate the effectiveness of proposed design method's tracking performance     

Adaptive fuzzy neural network finite-time command filtered control of n-link robotic systems with actuator saturation

The finite time tracking control of n-link robotic system is studied for model uncertainties and actuator saturation. Firstly, a smooth function and adaptive fuzzy neural network online learning algorithm are designed to address the actuator saturation and dynamic model uncertainties. Secondly, a new finite-time command filtered technique is proposed to filter the virtual control signal. The improved error compensation signal can reduce the impact of filtering errors, and the tracking errors of system quickly converge to a smaller compact set within finite time. Finally, adaptive fuzzy neural network finite-time command filtered control achieves finite-time stability through Lyapunov stability criterion. Simulation results verify the effectiveness of the proposed control.     

SGCMGs驱动的挠性航天器有限时间自适应鲁棒控制

针对挠性航天器系统中同时存在单框架控制力矩陀螺群(Single gimbaled control moment gyroscopes,SGCMGs)摩擦非线性、电磁干扰力矩、惯量摄动以及外部干扰等问题,提出了一种有限时间自适应鲁棒控制(Finite-time adaptive robust control,FTARC)...     

Finite-time command filter-based adaptive tracking control for nonstrict feedback nonlinear systems with full-state restrictions and unmodeled dynamics

The finite-time command filter tracking control for a class of nonstrictly feedback nonlinear systems with unmodeled dynamics and full-state constraints is investigated in this paper. The hyperbolic tangent function is used as a nonlinear mapping technique to solve the obstacle of the full-state constraints. A new adaptive finite time control method is proposed through command filtering reverse engineering, and the shortcomings of the dynamic surface control (DSC) method are overcome by the error compensation mechanism. Dynamic signal is designed to handle dynamical uncertain terms. Normalization signal is designed to handle input unmodeled dynamics. Unknown nonlinear functions are approximated by radial basis function neural networks. Based on the Lyapunov stability theory, it is proved that all signals in the closed-loop system are semi-globally consistent and finally bounded and the output tracking error converges in finite time. Two numerical examples are utilized to verify the effectiveness of the proposed control approach.     

An adaptive disturbance rejection control scheme for multivariable nonlinear systems

An adaptive disturbance rejection control scheme is developed for uncertain multi-input multi-output nonlinear systems in the presence of unmatched input disturbances. The nominal output rejection scheme is first developed, for which the relative degree characterisation of the control and disturbance system models from multivariable nonlinear systems is specified as a key design condition for this disturbance output rejection design. The adaptive disturbance rejection control design is then completed by deriving an error model in terms of parameter errors and tracking error, and constructing adaptive parameter-updated laws and adaptive parameter projection algorithms. All closed-loop signals are guaranteed to be bounded and the plant output tracks a given reference output asymptotically despite the uncertainties of system and disturbance parameters. The developed adaptive disturbance rejection scheme is applied to turbulence compensation for aircraft fight control. Simulation results from a benchmark aircraft model verify the desired system performance.