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1.
基于神经网络的不确定机器人自适应滑模控制   总被引:13,自引:0,他引:13  
提出一种机器人轨迹跟踪的自适应神经滑模控制。该控制方案将神经网络的非线性映射能力与变结构控制理论相结合,利用RBF网络自适应学习系统不确定性的未知上界,神经网络的输出用于自适应修正控制律的切换增益。这种新型控制器能保证机械手位置和速度跟踪误差渐近收敛于零。仿真结果表明了该方案的有效性。  相似文献   

2.
一类非线性系统的积分变结构模糊自适应跟踪控制   总被引:1,自引:0,他引:1  
针对一类具有未知常数控制增益的不确定非线性系统,基于变结构控制原理,并利用具有非线性可调参数的模糊系统逼近等价控制,提出一种具有监督控制器的积分变结构模糊自适应跟踪控制策略.该策略通过监督控制器保证闭环系统所有信号有界.进一步,通过引入最优逼近误差的自适应补偿项来消除建模误差的影响.理论分析证明了跟踪误差能够收敛到零.仿真结果表明了该方法的有效性.  相似文献   

3.
非线性大系统的分散自适应模糊控制*   总被引:4,自引:1,他引:3  
本文针对非线性大系统,利用模糊系统的逼近能力,提出了一种分散自适应模糊控制器设计的系统方法。控制结构中采用分散模糊系统去自适应补偿过程不确定性,同时用模糊控制器的输出代替常规变结构控制律中的符号函数。利用李亚普诺夫理论,证明了控制算法是全局稳定的,跟踪误差可收敛到零的一个领域内。  相似文献   

4.
研究了具有不确定项的非线性Willis环上脑动脉瘤系统的混沌控制和同步问题,提出了一种自适应模糊滑模变结构控制方法,设计了模糊滑模变结构控制器及自适应控制律,并从理论上证明了控制系统的稳定性。在该控制器的作用下,受控Willis脑动脉瘤系统能够达到任意目标轨道,且不受不确定性的影响,具有很强的鲁棒性。定值跟踪和同步控制的仿真结果表明了控制器的有效性。  相似文献   

5.
针对一类不确定非线性系统, 基于变结构控制原理, 并利用具有非线性可调参数的模糊系统去逼近过程未知函数, 提出一种具有模糊监督控制器的积分变结构间接自适应控制方案. 该方案通过监督控制器保证闭环系统所有信号有界. 进一步, 通过引入最优逼近误差的自适应补偿项来消除建模误差的影响. 理论分析证明了跟踪误差收敛到零. 仿真结果表明了该方法的有效性.  相似文献   

6.
针对一类具有未知不确定性范数上界的线性时滞系统,设计自适应近似变结构控制器 ,对系统的不确定性范数上界进行在线估计,近似变结构控制器使系统进入滑模运动区域, 保证系统的一致终结有界性,进而用李雅谱诺夫函数方法分析了所得控制系统的性能.所提 出的近似自适应变结构控制器可以避免控制器中的不连续继电项,同时不必已知系统不确定 性范数界.用数字仿真例子验证了所提出控制器设计方法的有效性.  相似文献   

7.
提出一种针对机器人跟踪控制的神经网络自适应滑模控制策略。该控制方案将神经网络的非线性映射能力与滑模变结构和自适应控制相结合。对于机器人中不确定项,通过RBF网络分别进行自适应补偿,并通过滑模变结构控制器和自适应控制器消除逼近误差。同时基于Lyapunov理论保证机器手轨迹跟踪误差渐进收敛于零。仿真结果表明了该方法的优越性和有效性。  相似文献   

8.
不确定非线性系统的多模反演滑模控制   总被引:2,自引:0,他引:2  
对一般形式的仿射非匹配不确定非线性系统,研究了一种具有任意小跟踪误差的稳定控制器的新方法,结合反演(backstepping)设计和变结构控制,提出了反演变结构控制策略,对存在非匹配的不确定性和未知干扰的系统,设计的反演结构控制器实现了鲁棒输出跟踪,闭环系统在有限时间进入滑动模态,仿真算例证实了理论结果。  相似文献   

9.
不匹配不确定线性时滞系统的鲁棒自适应控制   总被引:5,自引:1,他引:4  
对一类同时具有匹配不确定性及结构确定不匹配不确定性的不确定时滞系统进行鲁棒自适应控制。首先,采用李雅谱诺夫函数方法,结合基于线性矩阵不等式的鲁棒控制器设计方法和变结构控制方法,设计鲁棒控制器,保证闭环系统的二次渐近稳定。利用自适应参数估计方法,设计具有匹配不确定性范数界估计能力的鲁棒自适应控制器,保证闭环系统的一致终结有界。结合算例,进行控制器的设计和仿真研究,验证所提出的设计方法的有效性。  相似文献   

10.
丁国锋  王孙安 《机器人》1997,19(5):338-343
针对不确定性机器人提出一种具有H^∞跟踪特性的神经网络(NN)控制器,使H^∞控制理论与NN有机地结合起来。通过适当选择控制变量加权因子可以使由于NN近似误差以及外部干扰引起的误差动态衰减到期望的程度下。文基基于Lyapunov方法给出了NN学习自适应律,H^∞跟踪特性的证明。最后通过在两自由度机器人控制中的应用表明该方案的可行性。  相似文献   

11.
Fuzzy adaptive tracking controllers for a class of uncertain nonlinear dynamical systems are proposed and analyzed. The controllers consist of adaptive and robustifying components whose role is to ify the effects of uncertainties and to achieve a desired tracking performance. The interactions between the two components have been investigated. The closed-loop system driven by the proposed controllers is shown to be stable with all the adaptation parameters being bounded. In particular, the proposed controllers guarantee uniform ultimate boundedness of the tracking error and the time bound of the uniform ultimate boundedness is obtained. An upper bound on the steady-state tracking error is obtained as a function of the gain of the robustifying term and the parameters of the adaptive component. The controllers are tested on an inverted pendulum and simulation results are included. A comparison of the proposed controllers with the ones in the literature is conducted.  相似文献   

12.
A novel adaptive fuzzy-neural sliding-mode controller with H(infinity) tracking performance for uncertain nonlinear systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors. Because of the advantages of fuzzy-neural systems, which can uniformly approximate nonlinear continuous functions to arbitrary accuracy, adaptive fuzzy-neural control theory is then employed to derive the update laws for approximating the uncertain nonlinear functions of the dynamical system. Furthermore, the H(infinity) tracking design technique and the sliding-mode control method are incorporated into the adaptive fuzzy-neural control scheme so that the derived controller is robust with respect to unmodeled dynamics, disturbances and approximate errors. Compared with conventional methods, the proposed approach not only assures closed-loop stability, but also guarantees an H(infinity) tracking performance for the overall system based on a much relaxed assumption without prior knowledge on the upper bound of the lumped uncertainties. Simulation results have demonstrated that the effect of the lumped uncertainties on tracking error is efficiently attenuated, and chattering of the control input is significantly reduced by using the proposed approach.  相似文献   

13.
The problem of robust output tracking for a class of uncertain nonlinear systems which do not satisfy the conventional matching condition is considered. The main assumption on the uncertainty is that the triangularity condition is satisfied. Based on backstepping method and input/output linearization approach, we propose a class of non-adaptive state feedback controllers which can guarantee exponential stability of the tracking error for the uncertain nonlinear systems first. Next, adaptive control laws are developed so that no prior knowledge of the bounds on the uncertainties is required. By updating these upper bounds, we design a class of adaptive robust controllers. It is shown that under the proposed adaptive robust control the tracking error of the controlled system converges to zero as time approaches infinity.  相似文献   

14.
一类非最小相位非线性系统的自适应控制   总被引:1,自引:1,他引:0  
针对一类非最小相位的非线性系统,通过引入一个近似系统,提出了一种简单的间接自 适应控制方法,并分析了采用该方法后系统输出的跟踪性能,给出了输出跟踪误差的上限.该 方法可克服现有的非线性自适应控制方法只能控制最小相位的非线性系统并且容易产生过 度控制的缺点.  相似文献   

15.
In this paper, adaptive tracking control of switched nonlinear systems in the parametric strict-feedback form is investigated. After defining a reparametrisation lemma in the presence of a non-zero reference signal, we propose a new adaptive backstepping design of the virtual controllers that can handle the extra terms arising from the reparametrisation (and that the state-of-the-art backstepping designs cannot dominate). The proposed adaptive design guarantees, under arbitrarily fast switching, an a priori bound for the steady-state performance of the tracking error and a tunable bound for the transient error. Finally, the proposed method, by overcoming the need for subsystems with common sign of the input vector field, enlarges the class of uncertain switched nonlinear systems for which the adaptive tracking problem can be solved. A numerical example is provided to illustrate the proposed control scheme.  相似文献   

16.
In this study, a dynamical adaptive integral backstepping variable structure control (DAIBVSC) system based on the Lyapunov stability theorem is proposed for the trajectory tracking control of a nonlinear uncertain mechatronic system with disturbances. In this control scheme, no prior knowledge is required on the uncertain parameters and disturbances because it is estimated by two types of dynamical adaptive laws. These adaptive laws are integrated into the dynamical adaptive integral backstepping control and variable structure control (VSC) parts of the DAIBVSC. The dynamical adaptive law in the dynamical adaptive integral backstepping control part updates parametric uncertainties, while the other in the VSC part adapts upper bounds of non‐parametric uncertainties and disturbances. In order to achieve a more robust output tracking and better parameter adaptation, the control system is extended by one integrator and sliding surface is augmented by an integral action. Experimental evaluation of the DAIBVSC is conducted with respect to performance and robustness to parametric uncertainties. Experimental results of the DAIBVSC are compared with those of a traditional VSC. The proposed DAIBVSC exhibits satisfactory output tracking performance, good estimation of the uncertain parameters and can reject disturbances with a chattering free control law. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

17.
研究了一类采样数据非线性系统的动态神经网络稳定自适应控制方法.不同于静态 神经网络自适应控制,动态神经网络自适应控制中神经网络用于逼近整个采样数据非线性系 统,而不是动态系统中的非线性分量.系统的控制律由神经网络系统的动态逆、自适应补偿项 和神经变结构鲁棒控制项组成.神经变结构控制用于保证系统的全局稳定性,并加速动态神 经网络系统的适近速度.证明了动态神经网络自适应控制系统的稳定性,并得到了动态神经 网络系统的学习算法.仿真研究表明,基于动态神经网络的非线性系统稳定自适应控制方法 较基于静态神经网络的自适应方法具有更好的性能.  相似文献   

18.
In this paper, an adaptive neural tracking control approach is proposed for a class of nonlinear systems with dynamic uncertainties. The radial basis function neural networks (RBFNNs) are used to estimate the unknown nonlinear uncertainties, and then a novel adaptive neural scheme is developed, via backstepping technique. In the controller design, instead of using RBFNN to approximate each unknown function, we lump all unknown functions into a suitable unknown function that is approximated by only a RBFNN in each step of the backstepping. It is shown that the designed controller can guarantee that all signals in the closed-loop system are semi-globally bounded and the tracking error finally converges to a small domain around the origin. Two examples are given to demonstrate the effectiveness of the proposed control scheme.  相似文献   

19.
This note deals with the tracking control of multiple-input-multiple-output (MIMO) nonlinear parametric strict-feedback systems in the presence of additive disturbances and parametric uncertainties. For such systems, C/sup 0/ robust adaptive controllers usually cannot ensure asymptotic tracking or even regulation. In this work, under the assumption the disturbances are C/sup 2/ with bounded time derivatives, we present a C/sup 0/ robust adaptive control construction that guarantees the tracking error is asymptotically driven to zero.  相似文献   

20.
The attitude tracking of a rigid spacecraft is approached in the presence of uncertain inertias, unknown disturbances, and sudden actuator faults. First, a novel integral terminal sliding mode (ITSM) is designed such that the sliding motion realizes the action of a quaternion‐based nonlinear proportional‐derivative controller. More precisely, on the ITSM, the attitude dynamics behave equivalently to an uncertainty‐free system, and finite‐time convergence of the tracking error is achieved almost globally. A basic ITSM controller is then designed to ensure the ITSM from onset when an upper bound on the system uncertainties is known. Further, to remove this requirement, adaptive techniques are employed to compensate for the uncertainties, and the resultant adaptive ITSM controller stabilizes the system states to a small neighborhood around the sliding surface in finite time. The proposed schemes avoid the singularity intrinsic to terminal sliding mode‐based controllers and the unwinding phenomenon associated with some quaternion‐based controllers. Numerical examples demonstrate the advantageous features of the proposed algorithm. Copyright © 2017 John Wiley & Sons, Ltd.  相似文献   

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