不确定电液位置伺服系统的自适应终端滑模控制

为了解决非线性、不确定电液伺服系统的位置跟踪控制问题,提出了一种基于反步法的自适应终端滑模控制方法.该方法将自适应控制和终端滑模方法结合在一起,一方面,提出的自适应控制律可以对电液伺服系统中的不确定性参数进行有效在线估计和补偿;另一方面,通过引入误差吸引子到滑模趋近律中得到变系数趋近律,设计的终端滑模控制律不仅能够消除普通终端滑模控制律中的非奇异项,还大大降低了滑模面的抖震.最终,根据Lyapunov稳定性理论,位置跟踪误差的有限时间稳定性得以严格证明.将该方法与积分反步滑模控制和线性滑模控制方法进行了对比研究,仿真结果验证了该方法在电液伺服系统位置跟踪控制方面良好的鲁棒性和跟踪精度.     

采用RBF网络的喷雾机喷杆自适应动态面跟踪控制

为了实现喷雾机喷杆快速而准确地伺服跟踪农作物冠层高度，选用电液伺服系统作为其位置调节装置，系统建模以喷雾机喷杆为负载的电液伺服系统.首先，充分考虑系统的强非线性和参数不确定因素，建立完整的数学模型；然后，采用动态面方法设计控制器，通过RBF网络对不确定项和非线性函数进行逼近，在控制律中加入阻尼项补偿干扰对系统性能的影响；基于Lyapunov稳定性方法，证明闭环系统信号最终一致有界；最后，对某喷雾机喷杆系统进行仿真验证，结果表明设计控制器具有良好的仿形跟踪控制性能.     

卫星姿态跟踪的间接自适应模糊预测控制

对含模型不确定性和未知干扰的卫星姿态系统提出了具有间接自适应模糊补偿的广义预测跟踪控制方法. 首先基于卫星姿态动力学模型设计了非线性广义预测控制律, 再利用自适应模糊系统逼近预测控制律中的模型不确定项, 使得所得到的预测控制算法可实施.证明了当卫星姿态模型中不确定项满足一定条件时, 所设计的控制律可使卫星姿态跟踪误差收敛到原点的小邻域内,并仿真结果验证了所提出方法的有效性.     

PMSM伺服系统的神经网络动态面控制

针对永磁同步电动机(PMSM)伺服系统中存在负载扰动和参数不确定问题,提出一种新型的基于预估器的自适应神经网络动态面控制算法.采用神经网络在线辨识系统的不确定项.在控制设计中引入神经网络预估器,并利用预估偏差学习神经网络的权值向量.通过引入动态面控制技术克服传统反步递推控制设计中存在的"复杂性爆炸"问题.所提控制算法可以在实现快速自适应的同时,避免了控制输入中可能存在的高频信号和控制输入漂移问题,进而提高PMSM伺服系统的位置跟踪控制性能.仿真结果验证了所提控制算法的有效性,并且与现有自适应神经网络控制方案相比,基于文章提出的自适应神经网络动态面控制方案的PMSM伺服系统具有更好的位置跟踪性能.     

冷轧机压下伺服系统的输出反馈有限时间控制研究

针对冷轧机压下电液伺服系统存在非线性、参数不确定性和负载干扰等特点,提出了基于扩张状态观测器的输出反馈有限时间控制方法.利用扩张状态观测器对系统的状态变量进行观测,解决了电液伺服系统的速度和加速度难以实际测量的难题,并对未知函数及扰动具有鲁棒性.依据有限时间控制理论并结合反步构造法设计了有限时间控制器,并证明了系统的全局稳定性.仿真表明:扩张状态观测器能够快速准确的观测系统的状态;基于扩张状态观测器的有限时间控制方法能使系统快速、准确地跟踪指定位置目标,并具有很强的鲁棒性.     

一类不确定性非线性系统的状态反馈鲁棒自适应控制器的设计与分析

该文考虑一类具有一般不确定性和部分参数未知的非线性系统（1），设计出一种用于跟踪参考信号的状态反馈鲁棒自适应控制器，此控制器对系统参数和状态的不确定性具有鲁棒性，能保证闭环系 统的全局稳定性，并解决了ε 跟踪问题. 仿真结果表明，所设计的鲁棒自适应控制系统具有良好的跟踪性能， 而且控制量在容许控制的范围之内.     

不确定非线性系统的周期信号自适应跟踪

考虑不确定非线性系统的周期信号的自适应跟踪问题. 系统的不确定性不能参数化,周期信号由一非线性系统产生.提出了跟踪周期信号的自适应控制律. 此控制律保证了闭环系统所有的信号有界和跟踪误差趋于零. 已有的有关的周期信号跟踪控制律只能保证跟踪误差的平方在一周期上的积分趋于零.     

一类非线性不确定系统的鲁棒自适应模糊跟踪控制

针对一类单输入单输出非线性不确定系统，提出一种稳定的间接自适应模糊控制方法。该方法考虑了跟踪误差和逼近误差对参数自适应律的共同影响，并对模糊逼近误差和外扰采用H∞补偿控制。仿真结果表明本文所提出的方法具有良好的跟踪性能。     

基于性能的直流电机系统未知推力波动的自适应补偿控制

针对一类直流电机系统,设计基于性能的未知推力波动的自适应补偿控制器.由于推力波动中含有非线性化的未知参数,因此无法利用常规的自适应方法,通过直接估计这些参数对其影响进行补偿.根据未知推力波动的结构特性,基于Lipshitz条件引入推力波动项的放大技术,设计其内部非线性化未知参数的自适应估计律,精确补偿其影响,从而避免了简单的把波动看作未知扰动所造成的系统性能的损失.有别于现有模型,在模型变换中并未忽略微小等效电感的影响,使得系统模型更具一般性.仿真结果表明该自适应控制器可有效补偿推力波动的影响,实现对指令信号的高精度快速跟踪且具有较强的抗干扰性和鲁棒性.     

考虑执行器特性的机械臂全阶滑模控制

针对动力学模型中带有参数未知特性的机械臂位置和速度跟踪问题,提出一种新型的基于神经网络和全阶滑模的控制策略.该策略考虑了执行器的动力学特性,然后基于跟踪误差,建立了全阶滑模面,并利用径向基网络对模型未知特性进行逼近,进而设计鲁棒自适应控制律使得系统状态到达滑模面并沿滑模面收敛到平衡点.理论分析证明了所设计的控制策略可在克服抖振问题的同时保证闭环系统的渐近稳定性.二连杆机械臂系统的数值仿真结果验证了所提出方法的有效性.     

计及位置不确定的喷雾机喷杆系统仿形姿态渐近跟踪控制北大核心CSCD

针对喷雾机喷杆仿形系统中同时存在负载变化、未建模不确定项、物理参数摄动以及外部干扰等问题,提出了一种基于小波网络逼近的具有自适应性和鲁棒性的反步控制方法.首先,将含有不确定、未知和非线性项的喷杆仿形系统建立为完整的数学模型,将其等价转化为具有严格反馈的状态空间形式;其次,采用设计的小波基元去构造神经网络,在满足最优误差有界条件下逼近反步法中虚拟等效控制部分,选取自适应更新律估计系统中存在的未知参数,引入鲁棒补偿项减小复合干扰对系统的不利影响,降低了输入指令信号的阶次要求;最后,通过构造合适的Lyapunov函数,应用稳定性理论证明了闭环系统位置跟踪误差渐近收敛到原点.仿真结果表明,所提控制方法可实现喷雾机喷杆位置姿态快速升降机动调整,有效地增强了喷杆系统的鲁棒稳定性和控制精度.     

Adaptive control of uncertain nonlinear systems using mixed backstepping and Lyapunov redesign techniques

In this paper, a robust adaptive control law for a class of uncertain nonlinear systems is proposed. The proposed controller guarantees asymptotic output tracking of systems in the strict-feedback form with unknown static parameters, and matched and unmatched dynamic uncertainties. This controller takes advantages of a robust stability property of the Lyapunov redesign method and a systematic design procedure of the backstepping technique. In fact, the backstepping technique is employed to enrich the Lyapunov redesign method to compensate for not only matched - but also unmatched-uncertainties. On the other hand, using the Lyapunov redesign method in each step of the conventional backstepping technique makes backstepping robust. The suggested controller is designed through repeatedly utilizing the Lyapunov redesign method in each step of the backstepping technique. Simulation results reveal the efficiency of the Lyapunov redesign-based backstepping controller.     

An adaptive sliding mode backstepping control for the mobile manipulator with nonholonomic constraints

To solve disturbances, nonlinearity, nonholonomic constraints and dynamic coupling between the platform and its mounted robot manipulator, an adaptive sliding mode controller based on the backstepping method applied to the robust trajectory tracking of the wheeled mobile manipulator is described in this article. The control algorithm rests on adopting the backstepping method to improve the global ultimate asymptotic stability and applying the sliding mode control to obtain high response and invariability to uncertainties. According to the Lyapunov stability criterion, the wheeled mobile manipulator is divided into several stabilizing subsystems, and an adaptive law is designed to estimate the general nondeterminacy, which make the controller be capable to drive the trajectory tracking error of the mobile manipulator to converge to zero even in the presence of perturbations and mathematical model errors. We compare our controller with the robust neural network based algorithm in nonholonomic constraints and uncertainties, and simulation results prove the effectivity and feasibility of the proposed method in the trajectory tracking of the wheeled mobile manipulator.     

Adaptive fuzzy control for a class of chaotic systems with nonaffine inputs

A robust adaptive fuzzy control scheme is presented for a class of chaotic systems with nonaffine inputs, modeling uncertainties and external disturbances by using backstepping approach. Fuzzy logic systems (FLS) are employed to approximate the unknown parts of the virtual control and practical controls. The main characteristics of the scheme are that the number of the online adaptive parameters is no more than two times of the order of chaotic system and the tracking errors are guaranteed to be uniformly asymptotically stable with the aid of additional adaptive compensation terms. Lorenz system, Chen system, Lü system and Liu system are presented to illustrate the feasibility and effectiveness of the proposed control technique.     

Nonlinear adaptive output feedback robust control of hydraulic actuators with largely unknown modeling uncertainties

In this paper, a nonlinear adaptive output feedback robust controller is proposed for motion control of hydraulic servo systems in the presence of largely unknown matched and mismatched modeling uncertainties. Different from the existing control technologies, the presented hydraulic closed-loop controller which can deal with strong matched and mismatched parametric uncertainties is synthesized via the backstepping technique. Specially, a nonlinear disturbance observer which can estimate the largely mismatched disturbance is integrated into the design of the linear extended state observer to obtain estimation of unmeasurable system states, uncertain parameters and strong disturbances simultaneously. In addition, the projection-type adaptive law is synthesized into the design of the resulting controller. More importantly, the global stability of the whole closed-loop system is strictly guaranteed by the Lyapunov analysis. Furthermore, the effectiveness and practicability of the presented control strategy have been demonstrated by comparative experiments under different working conditions.     

Design of a coordinated adaptive backstepping tracking control for nonlinear uncertain active suspension system

This paper presents a novel adaptive backstepping tracking control for nonlinear uncertain active suspension system, which can achieve the coordinated control over the sprung-mass acceleration and suspension dynamic displacement for nonlinear uncertain active suspension system based on a developing model-reference system. First, according to adaptive backstepping control principle, this model-reference system is designed with purpose of providing the ideal reference trajectories for the sprung-mass displacement and vertical velocity, respectively. Then, the design of a coordinated adaptive backstepping tracking controller is conducted to make the control plant accurately track the prescribed performances of the model-reference system by virtue of the backstepping technique and Lyapunov stability theory, in which a virtual controller with online parameter regulation rules is designed and implemented to guarantee the stability of vehicle body. Finally, a numerical example is provided to verify the effectiveness of our designed adaptive backstepping tracking controller under various operating scenarios.     

Adaptive tracking control for a class of switched uncertain nonlinear systems under a new state-dependent switching law

This paper deals with the problem of adaptive fuzzy tracking control for a class of switched uncertain nonlinear systems. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and the adaptive backstepping and dynamic surface control techniques are adopted. First, a new state-dependent switching method is proposed. By introducing convex combination technique and designing a state-dependent switching law, only the solvability of the adaptive tracking control problem for a convex combination of the subsystems is necessary. Second, a new common Lyapunov function with switched adaptive parameters is constructed to reduce the conservatism. Third, to avoid Zeno behavior, a modified state-dependent switching law with dwell time is proposed. It is shown that under the proposed control and switching laws, all the signals of the closed-loop system are bounded and all the state tracking errors can converge to a priori accuracy, even if some subsystems are uncontrollable. Finally, the effectiveness of the proposed method is illustrated through two simulation examples.     

Adaptive type-2 fuzzy backstepping control of uncertain fractional-order nonlinear systems with unknown dead-zone

A new problem of adaptive type-2 fuzzy fractional control with pseudo-state observer for commensurate fractional order dynamic systems with dead-zone input nonlinearity is considered in presence of unmatched disturbances and model uncertainties; the control scheme is constructed by using the backstepping and adaptive technique. To avoid the complexity of backstepping design process, the dynamic surface control is used. Also, Interval type-2 Fuzzy logic systems (IT2FLS) are used to approximate the unknown nonlinear functions. By using the fractional adaptive backstepping, fractional control laws are constructed; this method is applied to a class of uncertain fractional-order nonlinear systems. In order to better control performance in reducing tracking error, the PSO algorithm is utilized for tuning the controller parameters. Stability of the system is proven by the Mittag–Leffler method. It is shown that the proposed controller guarantees the boundedness property for the system and also the tracking error can converge to a small neighborhood of the origin. The efficiency of the proposed method is illustrated with simulation examples.