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.     

具有不确定参数二次自治系统的自适应同步问题研究

研究了两个带有参数的n维二次自治系统的自适应同步问题.根据Lyapunov稳定性理论及自适应控制方法得到了两个带有不确定参数非线性系统状态的渐近同步自适应控制方法.同时,识别了不确定参数.通过对两个超混沌系统的理论研究,证明了给定的非线性动力系统同步策略和参数识别的可行性.     

连续非自治系统的有限时间稳定性及其充分条件（英文）

本文研究了连续非自治系统的有限时间稳定性问题.从一维连续非自治系统的有限时间稳定性分析入手,本文通过使用比较原理,获得了一些判定一般n维连续非自治系统的有限时间稳定性的充分条件,这些条件改善了已有的连续非自治系统有限时间稳定性的判定条件.     

参数不确定非自治混沌系统的自适应指数同步

针对参数不确定非自治混沌系统,研究了指数同步问题。给出了自适应控制器的构造方法,并运用Lyapunov稳定性定理证明了在该控制器下的误差系统是指数稳定的,且可以通过调整控制参数控制同步时间。最后,利用MATLAB软件对两个含有不确定参数的非自治混沌系统进行了数值仿真,验证了所提出方法的有效性和正确性.     

连续非自治系统的有限时间稳定性及其充分条件

本文研究了连续非自治系统的有限时间稳定性问题. 从一维连续非自治系统的有限时间稳定性分析入手, 本文通过使用比较原理, 获得了一些判定一般n维连续非自治系统的有限时间稳定性的充分条件,这些条件改善了已有的连续非自治系统有限时间稳定性的判定条件.     

电液位置伺服系统的鲁棒自适应控制

针对由于参数不确定性、非线性等因素导致的电液位置伺服系统跟踪控制问题,基于Lyapunov(李雅普诺夫)稳定性理论,提出了一种具有参数自适应能力的鲁棒自适应反步方法.通过设计的自适应律来抑制由于参数不确定性对系统跟踪控制性能的影响,设计的鲁棒控制律使得系统具有全局一致渐近稳定性能.此外,还对伺服阀换向引起的不连续性进行了近似处理.以伺服阀控对称缸系统为控制对象,仿真结果表明,和传统的PD控制方法相比,在参数不确定性的情况下,该控制方法使得电液伺服系统的位置跟踪误差波动较小,且能以较快速度渐近收敛到0,同时所需要的伺服阀输入电压信号值也更小,相关不确定参数在经过较短时间后均可以收敛到其稳定值,从而验证了所提出算法的有效性.     

一类非仿射非线性系统的神经网络自适应跟踪控制

考虑了一类具有零动态的非仿射非线性不确定系统的神经网络直接自适应跟踪控制问题.控制信号由神经网络系统直接产生,无需另外设计系统估计器及鲁棒控制项.采用梯度下降方法以最小化神经网络控制器与未知理想控制器的误差代价函数产生神经网络白适应参数更新律.应用Lyapunov方法证明了闭环系统的稳定性及跟踪误差和相应闭环系统的所有状态最终一致有界性.最后针对带有外部扰动的非仿射非线性系统的仿真结果验证了该文方法的有效性.     

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.     

无需精确初始误差的纯反馈系统实用预设时间保性能控制设计

暂态行为、稳态精度、调节时间和收敛速率是评价控制系统闭环性能的四个关键指标.文章针对非匹配的不确定纯反馈非线性系统,提出了一种同时满足以上四个指标的跟踪控制设计方案.该方案通过设定性能函数来保证系统输出信号始终保持在由该函数边界形成的包络范围内.同时,在一种新颖的误差转换机制控制下,闭环系统的稳态精度和调节时间可以被预先设定.文章使用神经网络来逼近完全未知的非线性函数,其中神经网络的权值可以通过自适应律在线更新.另外,文章在自适应律中加入σ-修正项以避免估计参数发生漂移现象.最后,仿真结果验证了所提控制方法的有效性和在控制性能上的优越性.     

模糊仿生间接自适应控制用于逼近误差的估计

针对一类不确定非线性系统,提出将生物个体对外界环境的适应对策引入到间接模糊自适应控制方法.方法的特点是将生物个体的主动自适应性与模糊控制相结合,将反应生物特性能力的结构单位生态位作为模糊规则后件.在仿生模糊系统的基础上,利用Lyapunov综合方法形成状态反馈仿生自适应控制算法,关键问题是重构误差有界,得到的系统具有良好逼近性.仿生控制律有两部分构成,一部分是等效控制,另一部分是边界控制,边界参数自适应律被用于这个边界控制,根据稳定性理论,证明闭环系统的全局稳定性.最后对倒立摆系统进行了仿真,结果证明了该方法的有效性和可行性.     

Synchronization of mechanical horizontal platform systems in finite time

The horizontal platform system (HPS) is a mechanical device that exhibits rich and chaotic dynamics. In this paper, the problem of finite-time synchronization of two non-autonomous chaotic HPSs is investigated. It is assumed that both drive and response systems are disturbed by model uncertainties, external disturbances and fully unknown parameters. Appropriate update laws are proposed to undertake the unknown parameters. Using the update laws and finite-time control theory, a robust adaptive controller is derived to synchronize the two uncertain HPSs in a given finite time. Subsequently, the effects of input nonlinearities are taken into account and a robust adaptive controller is introduced to synchronize the two uncertain HPSs within a finite time. The finite-time stability and convergence of the proposed schemes are analytically proved. Two illustrative examples are presented to show the robustness and applicability of the proposed adaptive finite-time control techniques.     

Finite-time synchronization of two different chaotic systems with unknown parameters via sliding mode technique

In this paper, the problem of finite-time chaos synchronization between two different chaotic systems with fully unknown parameters is investigated. First, a new nonsingular terminal sliding surface is introduced and its finite-time convergence to the zero equilibrium is proved. Then, appropriate adaptive laws are derived to tackle the unknown parameters of the systems. Afterwards, based on the adaptive laws and finite-time control idea, an adaptive sliding mode controller is proposed to ensure the occurrence of the sliding motion in a given finite time. It is mathematically proved that the introduced sliding mode technique has finite-time convergence and stability in both reaching and sliding mode phases. Finally, some numerical simulations are presented to demonstrate the applicability and effectiveness of the proposed technique.     

Finite-time structure identification and synchronization of drive-response systems with uncertain parameter

This paper proposes an approach of finite-time synchronization to identify the topological structure and unknown parameters simultaneously for under general complex dynamical networks. Based on the finite-time stability theory, an effective control input and a feedback control with an updated law are designed to realize finite-time synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously. Since finite-time topology identification means the suboptimum in identified time, the results of this paper are important. Several useful criteria for finite-time synchronization are given. Finally, two examples simulations for supporting the theoretical results are also provided.     

Control and adaptive modified function projective synchronization of Liu chaotic dynamical system

In this work, the feedback control method is proposed to control the behaviour of Liu chaotic dynamical system. The controlled system is stable under some conditions on the parameters of the system determined by Routh-Hurwitz criterion. This paper also presents the adaptive modified function projective synchronization (AMFPS) between two identical Liu chaotic dynamical systems. Based on the Lyapunov stability theorem, adaptive control laws are designed to achieving the AMFPS. Finally, some numerical simulations are obtained to validate the proposed methods.     

Global finite-time synchronization of different dimensional chaotic systems

This paper addresses the problem of global finite-time synchronization of two different dimensional chaotic systems. Firstly, the definition of global finite-time synchronization of different dimensional chaotic systems are introduced. Based on the finite-time stability methods, the controller is designed such that the chaotic systems are globally synchronized in a finite time. Then, some uncertain parameters are adopted in the chaotic systems, new control law and dynamical parameter estimation are proposed to guarantee that the global finite-time synchronization can be obtained. By considering a dynamical parameter designed in the controller, the adaptive updated controller is also designed to achieve the desired results. At last, the results of two different dimensional chaotic systems are also extended to two different dimensional networked chaotic systems. Finally, three numerical examples are given to verify the validity of the proposed methods.     

Adaptive fuzzy sliding-mode control for multi-input multi-output chaotic systems

This paper describes an adaptive fuzzy sliding-mode control algorithm for controlling unknown or uncertain, multi-input multi-output (MIMO), possibly chaotic, dynamical systems. The control approach encompasses a fuzzy system and a robust controller. The fuzzy system is designed to mimic an ideal sliding-mode controller, and the robust controller compensates the difference between the fuzzy controller and the ideal one. The parameters of the fuzzy system, as well as the uncertainty bound of the robust controller, are tuned adaptively. The adaptive laws are derived in the Lyapunov sense to guarantee the asymptotic stability and tracking of the controlled system. The effectiveness of the proposed method is shown by applying it to some well-known chaotic systems.     

Adaptive lag synchronization for uncertain complex dynamical network with delayed coupling

This paper proposes an adaptive control method to achieve the lag synchronization between uncertain complex dynamical network having delayed coupling and a non-identical reference node. Unknown parameters of both the network and reference node are estimated by adaptive laws obtained by Lyapunov stability theory. With the estimated parameters, the proposed method guarantees the globally asymptotical synchronization of the network in spite of unknown bounded disturbances. The effectiveness of our work is verified through a numerical example and simulation.     

Robust finite-time convergence of chaotic systems via adaptive terminal sliding mode scheme

This paper investigates robust finite-time stabilization of a class of uncertain chaotic systems. A new terminal sliding mode (TSM) algorithm is proposed to steer the plant fast to zero within finite time. In particular, a new form of TSM is developed for multi-input and multi-output systems, and some criteria are presented to facilitate its control design. With adaption laws to identify uncertain parameters and unknown bounds on disturbances, the proposed terminal sliding mode controllers get rid of uncertainties and nonlinearities successfully. The closed-loop systems are provided with fast finite-time stability and strong robustness against uncertainties. Finally, numerical simulation of Lorenz system illustrates the effectiveness of this proposed control scheme.     

Adaptive synchronization of a hyperchaotic system with uncertain parameter

This paper addresses the synchronization problem of two Lü hyperchaotic dynamical systems in the presence of unknown system parameters. Based on Lyapunov stability theory an adaptive control law is derived to make the states of two identical Lü hyperchaotic systems with unknown system parameters asymptotically synchronized. Numerical simulations are presented to show the effectiveness of the proposed chaos synchronization schemes.