共查询到10条相似文献,搜索用时 74 毫秒
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Min Wang Bing Chen Peng Shi 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2008,38(3):721-730
This paper proposes a novel adaptive neural control scheme for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients. Based on the radial basis function neural network online approximation capability, an adaptive neural controller is presented by combining the backstepping approach and Lyapunov-Krasovskii functionals. The proposed controller guarantees the semiglobal boundedness of all the signals in the closed-loop system and contains minimal learning parameters. Finally, three simulation examples are given to demonstrate the effectiveness and applicability of the proposed scheme. 相似文献
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一类非线性参数化系统自适应重复学习控制 总被引:1,自引:1,他引:0
针对一类高阶非线性参数化系统, 利用分段积分机制, 提出了一种新的自适应重复学习控制方法. 该方法结合反馈线性化, 可以处理参数在一个未知紧集内周期性快时变的非线性系统, 通过引进微分-差分混合型参数自适应律, 设计了一种自适应控制策略, 使广义跟踪误差在误差平方范数意义下渐近收敛于零, 通过构造Lyapunov泛函, 给出闭环系统收敛的一个充分条件. 实例仿真结果说明了该方法的可行性. 相似文献
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Adaptive neural control for strict-feedback stochastic nonlinear systems with time-delay 总被引:2,自引:0,他引:2
Huanqing WangAuthor Vitae Bing ChenAuthor Vitae Chong LinAuthor Vitae 《Neurocomputing》2012,77(1):267-274
The problem of robust stabilization is investigated for strict-feedback stochastic nonlinear time-delay systems via adaptive neural network approach. Neural networks are used to model the unknown packaged functions, then the adaptive neural control law is constructed by a novel Lyapunov-Krasovskii functional and backstepping. It is shown that all the variables in the closed-loop system are semi-globally stochastic bounded, and the state variables converge into a small neighborhood in the sense of probability. 相似文献
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Considering interconnections among subsystems, we propose an adaptive neural tracking control scheme for a class of multiple-input-multiple-output (MIMO) non-affine pure-feedback time-delay nonlinear systems with input saturation. Neural networks (NNs) are employed to approximate unknown functions in the design procedure, and the separation technology is introduced here to tackle the problem induced from unknown time-delay items. The adaptive neural tracking control scheme is constructed by combining Lyapunov–Krasovskii functionals, NNs, the auxiliary system, the implicit function theory and the mean value theorem along with the dynamic surface control technique. Also, it is proven that the strategy guarantees tracking errors converge to a small neighbourhood around the origin by appropriate choice of design parameters and all signals in the closed-loop system uniformly ultimately bounded. Numerical simulation results are presented to demonstrate the effectiveness of the proposed control strategy. 相似文献
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一类非线性系统的自适应神经网络控制 总被引:4,自引:0,他引:4
针对一类具有非仿射函数和下三角结构的、受干扰未知的非线性系统,提出一种新的自适应神经网络控制方法.它是严格反馈不确定系统和纯反馈系统的更一般化表达.在Backstepping设计思想基础上,证明了闭环信号的半全局最终一致有界性,并很好地处理了控制方向和控制奇异问题.通过仿真验证了该方法的有效性. 相似文献
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The problem of adaptive control is studied for a class of nonlinearly parameterised systems with quantised input signal and unknown control directions. The homogeneous domination approach and the Nussbaum-type gain method are applied to design an adaptive state-feedback controller. A hysteretic type of quantiser is incorporated to reduce actuator chattering. The proposed controller can ensure that all signals of the nonlinear system are globally bounded, and that the system state asymptotically converges to zero. Two numerical examples are presented to demonstrate the effectiveness and potential of the proposed techniques. 相似文献