非线性扩展结构大系统自适应神经网络跟踪控制

针对一类非线性关联大系统在结构扩展时的跟踪控制问题, 提出一种采用自适应神经网络的控制方法. 该方法要求在不改变原结构系统控制律的前提下设计新加入子系统的控制律和自适应律, 使扩展后所有子系统都具有很好的跟踪性能. 这里主要利用神经网络的逼近功能以及Backstepping 技术来设计自适应律和控制律, 通过Lyapunov 理论证明在该控制器的作用下闭环系统的所有信号均是有界的, 并可使系统准确跟踪. 仿真结果验证了所提出方法的有效性.

     

一类不确定非线性系统的自适应鲁棒控制

针对一类由非线性微分方程描述的不确定单输入单输出(SISO)系统,提出了一种自适应鲁棒控制算法.设计了一动态滤波器并将其与原系统组成扩展系统,由滤波器求得控制律稳定扩展系统.算法绕开辨识模型参数而是直接估计函数值,加快了控制律的求解.设计了状态误差观测器,用观测器的值构造控制律逼近状态反馈时的控制效果.基于Lyapunov 稳定理论分析了扩展系统的渐近稳定性并给出了闭环稳定的充分条件.最后仿真结果验证了算法的有效性和鲁棒性.     

飞行器自适应神经网络时滞控制

在飞行器稳定性控制问题的研究中,针对含有外部扰动、参数不确定性、状态和控制时滞的非线性飞行器系统,提出了一种时滞状态反馈控制与神经网络自适应估计相结合的方法.对非线性系统线性化处理得到飞行器线性模型,并由线性矩阵不等式(LMI)设计反馈控制律;采用径向基函数(RBF)神经网络自适应在线估计策略,对反馈控制律进行补偿以消除未知非线性影响;采用Lyapunov稳定性理论证明了在所设计控制律作用下,闭环系统渐近稳定同时满足H∞性能指标.仿真结果验证了上述方法的可行性及有效性.     

一类不确定互联系统的鲁棒分散自适应控制

利用反演法的系统性和结构特点,研究了一类含有非线性参数的不确定非线性互联系统的鲁棒分散自适应控制问题.首先,在较直观、较一般的假定下,根据系统的结构特点利用反演法设计出其控制器和自适应律,并且每个子系统控制器和自适应律的构成只利用了本身系统的状态信息,即所谓的分散控制;其次,利用Lyapunov理论证明了所设计的控制器和自适应律使得被控系统的状态及参数估计误差一致终极有界.最后,算例仿真验证了所设计的控制算法的有效性.     

一类非线性不确定系统的自适应积分滑模控制

针对一类具有不确定参数的复杂非线性系统,提出了一种自适应积分滑模控制方法。控制器的设计分两步进行：首先,基于被控对象模型构造一个简化子系统,设计出该子系统的一个全局渐近稳定控制律;然后构造一个积分滑模面,设计自适应积分滑模补偿器以处理系统中含有不确定参数的部分,保证了滑模面的可达性和原系统的闭环稳定性。补偿后,系统的完整自适应控制律由简化子系统的控制律加补偿控制器两部分组成。所提设计方法简单,便于工程实现。最后,通过仿真结果验证了设计方案的有效性。     

浸入与不变方法原理及其在非线性自适应控制中的应用

非线性系统理论的实际工程需求和复杂性使其成为控制学科中最具吸引力和挑战性的研究领域,为此介绍了一种新的非线性控制律设计方法——浸入与不变（I&I）理论.该方法首先选择一个比被控系统维数低的（局部）渐近稳定的目标系统,然后设计浸入映射和控制律,使得原系统在控制律作用下的动态轨迹都是目标系统在浸入映射下的像,并且该控制律能够保持目标系统的像为不变吸引流形,且使闭环轨迹有界.针对未知点质量模型,设计了一种新的非线性浸入与不变自适应控制律,实现了对参考指令的精确跟踪.将其与基于确定等价原则的自适应控制律相比较,仿真结果表明,所设计的浸入与不变控制律能够更好地处理带有未知参数的系统.     

约束自适应反步法及其在飞行控制中的应用

为解决系统含有参数不确定性和(状态)执行器受限条件下的鲁棒自适应控制问题,将SISO系统指令滤波器推广到MIMO系统,提出一种基于指令滤波的自适应块控反步方法。在设计(虚拟)控制律时引入指令滤波器,在克服标准反步法虚拟控制律导数计算膨胀问题的同时,能够施加系统状态和执行器的限制条件,并通过引入扩展跟踪误差,有效解决了约束条件下参数估计过程的稳定性和跟踪误差收敛问题。给出了Lyapunov闭环稳定性证明,并将该方法应用于含有未知气动参数和输入饱和约束的飞行器非线性姿态控制器设计。6自由度飞行仿真表明,该控制器具有良好的指令跟踪能力和较强的鲁棒性。     

基于改进扩展状态观测器的液压锚杆钻机滑模摆角控制

液压锚杆钻机摆角系统固有的死区、干扰和时变参数严重影响其动态和稳态性能. 为解决该问题, 通过融合动态面方法、滑模方法和扩展状态观测器, 提出一种基于改进非线性扩展状态观测器的液压锚杆钻机自适应滑模摆角控制方法. 首先, 引入一种死区补偿方法, 建立摆角系统的死区补偿模型. 其次, 为提高系统的抗扰动能力和抑制噪声, 设计一种改进的非线性扩展状态观测器. 此外, 构造一种自适应滑模控制律, 这其中, 基于性能函数和动态面方法设计一种新型的滑模面, 以提高控制精度; 随后, 设计一种新的滑模趋近律, 以提高系统滑模响应速度和消除滑模抖振. 进一步, 分别设计估计误差自适应律和参数自适应律以补偿扰动估计误差和抑制时变参数的影响. 最后, 通过将所提出的控制方法与8种控制方法进行比较, 验证其有效性.     

带有未知参数的惯性轮摆系统的自适应控制

针对带有未知参数的惯性轮摆系统,提出了一种自适应控制律设计方法。首先利用坐标变换将惯性轮摆系统的动力学模型转化为级联系统的形式。然后,针对系统参数未知的问题,在已有的惯性轮摆系统反馈控制律的基础上,利用控制器迭代设计思想,设计了惯性轮摆系统的自适应控制律,并利用李雅普诺夫稳定性理论证明了所得自适应控制律可以使得带有未知参数的惯性轮摆系统保持在摆杆垂直向上的平衡状态。最后以一个实际的惯性轮摆系统为例,采用该系统的物理参数进行仿真,分析了不同自适应参数下惯性轮摆系统各状态的收敛速度及摆起和稳定时间。仿真结果验证了所设计自适应控制器能够使惯性轮摆系统从垂直向下的平衡位置摆起并稳定在垂直向上的平衡位置。     

基于虚拟模型的自适应解耦抗扰控制

针对一类多变量非线性耦合系统,提出了一种基于虚拟模型的非线性自适应控制器.首先将非线性系统线性化处理并将其作为虚拟模型,对该模型设计线性自适应控制律.然后将线性控制律分别应用在虚拟系统和受控的实际非线性系统上,根据两者的输出误差设计补偿控制律,以达到对实际被控对象进行自适应解耦抗扰的目的.利用李雅普诺夫稳定理论给出了控制系统稳定性条件.实验仿真验证了控制算法的有效性.     

Control Lyapunov functions for adaptive nonlinear stabilization

For the problem of stabilization of nonlinear systems linear in unknown constant parameters, we introduce the concept of an adaptive control Lyapunov function (aclf) and use Sontag's constructive proof of Artstein's theorem to design an adaptive controller. In this framework the problem of adaptive stabilization of a nonlinear system is reduced to the problem of nonadaptive stabilization of a modified system. To illustrate the construction of aclf's we give an adaptive backstepping lemma which recovers our earlier design.     

Neural networks stabilization and disturbance attenuation for nonlinear switched impulsive systems

In this paper, we address the problem of neural networks (NNs) stabilization and disturbance rejection for a class of nonlinear switched impulsive systems. An adaptive NN feedback control scheme and an impulsive controller for output tracking error disturbance attenuation of nonlinear switched impulsive systems are given under all admissible switched strategy based on NN. The NN is used to compensate for the nonlinear uncertainties of switched impulsive systems, and the approximation error of NN is introduced to the adaptive law in order to improve the tracking attenuation quality of the switched impulsive systems. Impulsive controller is designed to attenuate effect of switching impulse. Under all admissible switching law, impulsive controller and adaptive NN feedback controller can guarantee asymptotic stability of tracking error and improve disturbance attenuation level of tracking error for the overall nonlinear switched impulsive system. Finally, a numerical example is given to demonstrate the effectiveness of the proposed control and stabilization methods.     

Adaptive robust simultaneous stabilization of multiple n-degree-of-freedom robot systems

In this paper, the adaptive robust simultaneous stabilization problem of uncertain multiple n-degree-of-freedom (n-DOF) robot systems is studied using the Hamiltonian function method, and the corresponding adaptive L2 controller is designed. First, we investigate the adaptive simultaneous stabilization problem of uncertain multiple n-DOF robot systems without external disturbance. Namely, the single uncertain n-DOF robot system is transformed into an equivalent Hamiltonian form using the unified partial derivative operator (UP-DO) and potential energy shaping method, and then a high dimensional Hamiltonian system for multiple uncertain robot systems is obtained by applying augmented dimension technology, and a single output feedback controller is designed to ensure the simultaneous stabilization for the higher dimensional Hamiltonian system. On this basis, we further study the adaptive robust simultaneous stabilization control problem for the uncertain multiple n-DOF robot systems with external disturbances, and design an adaptive robust simultaneous stabilization controller. Finally, the simulation results show that the adaptive robust simultaneous stabilization controller designed in this paper is very effective in stabilizing multi-robot systems at the same time.     

Adaptive control for a class of nonlinear systems with time-varying delays in state and input

This paper is concerned with the adaptive stabilization problem of uncertain input delayed systems.A solution to this problem is given for a class of uncertain nonlinear systems with time-varying delays in both state and input.An adaptive asymptotically stabilizing controller,which can guarantee the stability of the closed-loop system and the convergence of the original system state,is designed by means of the Lyapunov-Krasovskii functional stability theory combined with linear matrix inequalities (LMIs) an...     

Global adaptive finite‐time stabilization for a class of p‐normal nonlinear systems via an event‐triggered strategy

This article addresses the problem of global adaptive finite‐time control for a class of p‐normal nonlinear systems via an event‐triggered strategy. A state feedback controller is first designed for the nominal system by adding a power integrator method. Then, by the skillful design of adaptive dynamic gain mechanism, a novel event‐triggered controller is constructed for uncertain nonlinear system without homogeneous growth condition. It is proved that the global finite‐time stabilization of p‐normal nonlinear systems is guaranteed and the Zeno phenomenon is excluded. Finally, two examples are presented to indicate the effectiveness of the proposed control scheme.     

On Finite‐Time Stabilization of Active Disturbance Rejection Control for Uncertain Nonlinear Systems

This paper designs the active disturbance rejection control (ADRC) to achieve finite‐time stabilization for a class of uncertain nonlinear systems. The proposed control incorporates both an extended state observer (ESO) as well as an adaptive sliding mode controller. The ESO is utilized to estimate the full system states and the total uncertainties, and the adaptive strategy is incorporated to deal with the estimation errors. It is proved that, with the application of the proposed control law, semi‐global finite‐time stabilization can be achieved. Effectiveness of the proposed method is illustrated with a numerical example.     

Adaptive passification and stabilization for switched nonlinearly parameterized systems

This paper studies the issues of adaptive passification and global stabilization for a class of switched nonlinearly parameterized systems. Each subsystem is allowed to be non‐feedback passive. Firstly, a passivity concept for switched nonlinear systems is proposed. In particular, the change of storage functions of an inactive subsystem is described. An adaptively feedback passive switched nonlinear system is shown to be stabilized under the partly asymptotic zero‐state detectability assumption. Secondly, the adaptive feedback controller for each subsystem and a state‐dependent switching law are designed to render the resulting closed‐loop system passive. Finally, a new switched adaptive control technique is developed to solve the adaptive stabilization problem by exploiting the recursive feedback passification design technique and parameter separation technique when all subsystems have any same relative degree. The simulation results on adaptive stabilization of continuously stirred tank reactor system show effectiveness of the proposed design method. Copyright © 2016 John Wiley & Sons, Ltd.     

不确定非线性系统自适应动态事件触发输出反馈镇定

本文研究了一类不确定非线性系统的动态事件触发输出反馈镇定问题. 显著不同的是系统具有依赖于不可测状态的增长且增长率为输出的未知多项式. 尽管已有一些连续自适应控制器, 但需要巧妙融合非线性状态观测器、系统未知性的动态补偿以及非线性的抵御, 因此这些控制器具有一定的脆弱性, 不能平凡地拓展到不连续情形 (采样误差导致). 为此, 首先通过引入动态高增益和基于高增益的观测器来分别抵御未知增长率和重构系统不可测状态. 进而, 意识到静态事件触发机制的无效性, 通过引入动态事件触发机制, 成功设计出了事件触发输出反馈控制器, 确保了系统状态的全局有界性和收敛性. 数值仿真验证了所设计控制器的有效性.     

Adaptive Output‐Feedback Control of Nonlinear Systems with Multiple Uncertainties

This paper addresses the global stabilization via adaptive output‐feedback for a class of uncertain nonlinear systems. Remarkably, the systems under investigation are with multiple uncertainties: unknown control directions, unknown growth rates and unknown input bias, and can be used to describe more physical plants. Multiple uncertainties, which usually cannot be compensated by a sole compensation technique, may give rise to big technical difficulty for controller design. To overcome such difficulty and to achieve the global stabilization, a new adaptive output‐feedback scheme is proposed in this paper, by flexibly combining Nussbaum‐type function, tuning function technique and extended state observer. It is shown that, under the designed controller, the system states globally converge to zero. A simulation example on non‐zero set‐point regulation is given to demonstrate the effectiveness of the theoretical results.