含执行机构未知动态的液压伺服系统输出反馈控制

针对含有未知动态(如:执行机构、负载等)液压伺服系统,提出一种基于未知系统动态估计器的输出反馈控制方法.该方法不依赖于函数逼近器和传统反步控制设计,且无需难以测量的系统内部状态.首先,为避免反步控制和系统全部状态,引入等价变换,将含液压执行机构的伺服系统高阶严格反馈模型转化为Brunovsky标准型,进而运用高阶滑模微分器观测转化后的系统未知状态.控制器设计中引入描述收敛速率、最大超调量和稳态误差的性能函数,保证预设控制系统稳态和瞬态控制性能.为补偿系统集总未知动态影响,设计一种仅含一个调节参数并保证指数收敛的未知系统动态估计器.该输出反馈控制器可以实现对系统输出的精确跟踪控制.最后,通过数值仿真结果表明了所提出算法的有效性.     

控制方向未知的不确定系统预设性能自适应神经网络反演控制

对一类控制方向未知的不确定严格反馈非线性系统的预设性能自适应神经网络反演控制问题进行了研究.系统中含有时变非匹配不确定项且控制方向未知.首先,提出了一种新的误差转化方法,放宽了对初始误差已知的限制;随后,利用径向基函数(radial basis function,RBF)神经网络及跟踪微分器分别实现了对未知函数和虚拟控制量导数的逼近,并综合运用Nussbaum函数和反演控制技术设计了控制器.所设计的控制器能保证系统内所有信号有界且输出误差满足预设的瞬态和稳态性能要求.最后的仿真研究验证了控制器设计方法的有效性.     

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...     

基于自调节有限时间预设性能函数的多智能体系统动态面状态约束量化控制

针对一类非线性多智能体系统,构建一种基于自调节有限时间预设性能函数的动态面状态约束量化控制策略.所提出控制方法的主要特点为:1)将自调节有限时间预设性能函数与屏障Lyapunov函数相结合对多智能体系统的状态进行约束,使得构建出的约束函数能够根据系统当前跟踪误差自行调节自身参数而无需人为干预; 2)通过使用动态面控制方法,避免传统反步控制方法的“微分爆炸”现象,并设计滤波补偿函数消除因引入动态面方法而产生的滤波误差和信号振荡的问题; 3)使用RBF神经网络逼近系统中未知非线性的同时,引入量化器以减轻系统的通讯负担,且所构建量化控制方法仅需量化器具有扇形有界性质即可.稳定性分析表明,闭环系统内所有信号均为半全局一致有界的.仿真环节验证了所提出控制策略的有效性.     

输入饱和的一类切换系统神经网络跟踪控制

针对单输入单输出系统研究一种在任意切换下的跟踪控制问题,系统包含未知扰动和输入饱和特性.首先,利用高斯误差函数描述一个连续可导的非对称饱和模型.其次,利用径向基神经网络（Radial basis function neural network,RBF NN）逼近未知的系统动态.最后,基于公共的Lyapunov函数构造状态反馈控制器.设计的控制器避免过多参数调节从而减轻计算负荷.结果展示本文给出的状态反馈控制器可以保证闭环系统的所有信号是半全局一致有界的,并且跟踪误差可收敛到零值小的领域内.最后的仿真结果进一步验证提出方法的有效性.     

具有预设暂态性能的一类不确定非线性系统渐近状态跟踪控制

研究一类不确定非线性时变系统的预设暂态性能渐近状态跟踪控制问题.在无需系统函数先验知识的条件下,本文采用漏斗控制技术和障碍李雅普诺夫函数方法,提出了一种新颖的鲁棒自适应状态反馈控制策略.所设计的控制器不仅能够确保状态跟踪误差渐近收敛到零点,而且满足其预先设定的性能要求.仿真实例验证了所提控制策略的有效性.     

基于有限时间预设性能的高超声速飞行器反演控制

针对存在参数不确定以及外界干扰的高超声速飞行器跟踪性能问题,提出一种基于有限时间预设性能的反演控制方案.首先,为便于控制器设计,将高超声速飞行器模型划分为速度和高度子系统,针对子系统分别设计预设性能控制器以提高系统的瞬态和稳态性能;然后,通过设计一种有限时间性能函数,使得跟踪误差能够在预设时间内收敛至稳态值;接着,考虑到反演设计中虚拟指令导数难以获取以及干扰项对系统的影响,基于干扰观测器提出一种扰动估计方法,目的是在取得良好的观测扰动效果的同时,使得控制器设计流程简化、复杂度降低;最后,基于Lyapunov稳定理论证明系统的跟踪误差最终一致有界,并通过仿真验证该方法的有效性.     

随机激励下板球系统建模与有限时间全状态预设性能跟踪控制

研究板球系统受到随机激励时的数学建模与轨迹跟踪控制问题. 首次建立了板球系统的随机数学模型, 并 结合backstepping方法、有限时间预设性能函数、全状态约束及新的预设性能推导方法设计了具有未知输入饱和的 随机板球系统实际有限时间全状态预设性能跟踪控制器, 实现了随机激励下板球系统的有限时间预设性能轨迹跟 踪控制. 所设计的控制器保证了系统跟踪误差能够被预先给定的有限时间性能函数约束, 并且能在任意给定的停息 时间内收敛到预先给定的邻域内. 最后通过仿真实验验证了所设计控制器具有更好的控制效果.     

具有输入输出约束的无人直升机预设性能安全跟踪控制

针对无人直升机姿态与高度系统存在未知外部干扰、输入饱和、姿态与高度约束等问题, 本文提出一种具 有输入输出约束的预设性能安全跟踪控制方法. 首先, 针对无人直升机的姿态与高度约束, 通过设计一类边界保护 算法, 构建了新的安全期望跟踪信号. 为了保证系统对于安全期望跟踪信号的跟踪性能, 将预设性能函数与边界保 护算法进行结合, 并对跟踪误差进行转换. 针对系统的输入饱和现象, 使用Sigmoid函数进行逼近; 同时, 针对饱和函 数的逼近误差与未知外部干扰构成的复合干扰, 采用参数自适应方法对其上界进行逼近. 然后, 结合反步控制方法 设计了安全跟踪控制器, 并通过Lyapunov稳定性理论证明了闭环系统所有信号的收敛性, 保证了无人直升机的安全 跟踪性能. 最终, 通过数值仿真验证了所提控制方法的有效性.     

含齿隙非线性的双电机驱动伺服系统控制研究——基于反演积分自适应方法

针对存在齿隙非线性的双电机驱动伺服系统的控制问题,给出了双电机驱动伺服系统的模型,应用反演积分自适应控制方法,引入虚拟控制量和位置跟踪误差的积分,确保系统跟踪误差能够渐近稳定地趋于零。通过逐步递推选择Lyapunov函数,设计了基于状态反馈的自适应控制器,并进行了稳定性分析。通过与常规PID控制的仿真结果相比较,表明所提出的控制策略能较好地补偿齿隙非线性的影响,提高了系统的位置跟踪性能和鲁棒性。     

Robust approximation-free prescribed performance control for nonlinear systems and its application

This paper presents a robust prescribed performance control approach and its application to nonlinear tail-controlled missile systems with unknown dynamics and uncertainties. The idea of prescribed performance function (PPF) is incorporated into the control design, such that both the steady-state and transient control performance can be strictly guaranteed. Unlike conventional PPF-based control methods, we further tailor a recently proposed systematic control design procedure (i.e. approximation-free control) using the transformed tracking error dynamics, which provides a proportional-like control action. Hence, the function approximators (e.g. neural networks, fuzzy systems) that are widely used to address the unknown nonlinearities in the nonlinear control designs are not needed. The proposed control design leads to a robust yet simplified function approximation-free control for nonlinear systems. The closed-loop system stability and the control error convergence are all rigorously proved. Finally, comparative simulations are conducted based on nonlinear missile systems to validate the improved response and the robustness of the proposed control method.     

Optimal prescribed performance tracking control of nonlinear motor driven systems via adaptive dynamic programming

Although optimal regulation problem has been well studied, resolving optimal tracking control via adaptive dynamic programming (ADP) has not been completely resolved, particularly for nonlinear uncertain systems. In this paper, an online adaptive learning method is developed to realize the optimal tracking control design for nonlinear motor driven systems (NMDSs), which adopts the concept of ADP, unknown system dynamic estimator (USDE), and prescribed performance function (PPF). To this end, the USDE in a simple form is first proposed to address the NMDSs with bounded disturbances. Then, based on the estimated unknown dynamics, we define an optimal cost function and derive the optimal tracking control. The derived optimal tracking control is divided into two parts, that is, steady-state control and optimal feedback control. The steady-state control can be obtained with the tracking commands directly. The optimal feedback control can be obtained via the concept of ADP based on the PPF; this contributes to improving the convergence of critic neural network (CNN) weights and tracking accuracy of NMDSs. Simulations are provided to display the feasibility of the designed control method.     

含有非匹配干扰和未知动态的非仿射系统滑模控制算法

针对含有非匹配干扰和未知动态的非仿射系统控制问题,提出了一种基于扩张状态观测器(ESO)的改进滑模控制(SMC)方案.本文首先利用扩张状态观测器,将原系统转变为一个包含干扰的二阶积分级联系统,使含有未知动态的非仿射系统控制器设计问题转化为二阶积分级联系统的控制器设计问题,从而使得控制器在设计过程中不需要对对象模型完全已...     

Disturbance observer-based tracking control with prescribed performance specifications for a class of nonlinear systems subject to mismatched disturbances

This work investigates simultaneous prescribed performance tracking control and mismatched disturbance rejection problems for a class of strict-feedback nonlinear systems. A novel control scheme combining prescribed performance control, disturbance observer technique, and backstepping method is proposed. The disturbance estimations are introduced into the design of virtual control law design in each step to compensate the mismatched disturbances. To further improve the control performance, a prescribed performance function characterizing the error convergence rate, maximum overshoot, and steady-state error is used to construct the composite controller. The proposed controller guarantees transient and steady-state performance specifications of tracking error and provides much better disturbance attenuation ability simultaneously. Rigorous stability analysis for the closed-loop system is established by direct Lyapunov function method. It is shown that all the states in the resulting closed-loop system are stable, and the tracking error evolves within the prescribed performance boundaries and asymptotically converges to zero even in the presence of mismatched external disturbances. Finally, theoretical results are illustrated and demonstrated by two simulation examples.     

带有输出约束的柔性关节机械臂预设性能自适应控制

针对带有输出约束和模型不确定的柔性关节机械臂系统,提出一种基于时变障碍李雅普诺夫函数的预设性能自适应控制方法.通过构造指数衰减的时变约束边界,提出时变正切型障碍李雅普诺夫函数,能够同时适用于约束与非约束情况,进而拓宽传统对数型障碍李雅普诺夫函数的适用范围.此外,通过预先设置时变边界函数的相关参数,使得系统输出在初始阶段...     

Adaptive neural prescribed performance control for a class of strict-feedback stochastic nonlinear systems under arbitrary switchings

This paper presents an adaptive neural tracking control scheme for strict-feedback stochastic nonlinear systems with guaranteed transient and steady-state performance under arbitrary switchings. First, by utilising the prescribed performance control, the prescribed tracking control performance can be ensured, while the requirement for the initial error is removed. Second, radial basis function neural networks approximation are used to handle unknown nonlinear functions and stochastic disturbances. At last, by using the common Lyapunov function method and the backstepping technique, a common adaptive neural controller is constructed. The designed controller overcomes the problem of the over-parameterisation, and further alleviates the computational burden. Under the proposed common adaptive controller, all the signals in the closed-loop system are 4-Moment (or 2 Moment) semi-globally uniformly ultimately bounded, and the prescribed tracking control performance are guaranteed under arbitrary switchings. Three examples are presented to further illustrate the effectiveness of the proposed approach.     

基于未知系统动态估计的机器人预设性能控制

针对含有未知系统动态和外部干扰的机器人系统,提出一种不依赖于函数逼近器且能保证瞬态和稳态性能的控制算法.设计未知系统动态估计器可重构机器人系统的未知动态(向心力、重力)和外部干扰,与其他方法相比,该估计器结构简单,只需调节一个参数,且引入滤波操作可避免使用加速度信号,有利于在实际机器人控制中的运用.控制器设计中引入描述...     

无人艇轨迹跟踪的预设性能抗扰控制研究

针对海洋环境干扰下的无人艇轨迹跟踪问题,提出一种预设性能轨迹跟踪抗扰控制方法。首先,该方法通过引入具有约束作用的性能函数设计预设性能反演控制器。同时采用干扰观测器精确补偿外界未知扰动,并引入带σ修正漏项自适应律对海洋环境干扰的界进行估计,实现了无人艇轨迹跟踪抗扰控制,且同时保证其暂态性能和稳态性能。然后根据李雅普诺夫稳...     

Modeling and inverse adaptive control of asymmetric hysteresis systems with applications to magnetostrictive actuator

When uncertain systems are actuated by smart material based actuators, the systems exhibit hysteresis nonlinearities and corresponding control is becoming a challenging task, especially with magnetostrictive actuators which are dominated by asymmetric hystereses. The common approach for overcoming the hysteresis effect is inverse compensation combining with robust adaptive control. Focusing on the asymmetric hysteresis phenomenon, an asymmetric shifted Prandtl–Ishlinskii (ASPI) model and its inverse are developed and a corresponding analytical expression for the inverse compensation error is derived. Then, a prescribed adaptive control method is applied to mitigate the compensation error and simultaneously guaranteeing global stability of the closed loop system with a prescribed transient and steady-state performance of the tracking error without knowledge of system parameters. The effectiveness of the proposed control scheme is validated on a magnetostrictive actuated platform.