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本文针对一类具有未知非线性函数和未知虚拟系数非线性函数的二阶非线性系统 ,提出了一种基于神经网络的稳定自适应输出跟踪控制方法 .用李雅普诺夫稳定性分析方法证明了本文的神经网络自适应控制器能够使受控系统稳定 ,并使输出跟踪误差随时间趋于无穷而收敛到零 .仿真算例证明了该算法的有效性 相似文献
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采用最小时间控制方法为Rossler的同步误差系统设计了一个非线性状态反馈控制器,基于Lyapunov稳定性理论,证明了所设计的控制器能够使受控误差系统全局渐近稳定到同步误差系统的零点,并且使所提出的目标泛函取得极小值.数值仿真表明,所设计的控制器实用有效并且易于实现. 相似文献
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一类非线性离散系统的直接自适应模糊控制 总被引:1,自引:0,他引:1
针对一类含延迟非线性离散系统,提出了一种直接自适应模糊控制器设计的新方案.将系统用T-S模糊模型来表示,并基于并行分布补偿(PDC)基本思想设计了一种具有未知参数的模糊控制器,同时采用梯度下降算法对该控制器的参数进行在线辨识.通过输入到状态稳定(ISS)方法,证明了系统输出和参考输出的误差有界且满足一定的平均性能.仿真表明本方法的有效性. 相似文献
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本文研究一类非线性不确定动态系统的基于状态反馈的鲁棒稳定控制器设计问题,提出了一种基于状态反馈的非线性控制律,该控制器使得闭环系统鲁棒稳定.对于Benchmark问题验证了所提控制律的正确性和有效性. 相似文献
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离散型模糊系统的稳定线性监督控制设计 总被引:3,自引:0,他引:3
在对现有的T-S型模糊系统的稳定性结果进行
分析的基础上,研究了状态空间形式下离散型模糊系统在子空间上的线性分解,基于该线性
分解设计一线性监督控制器使模糊闭环系统稳定,从而用简单的线性系统理论完成了对复杂
非线性系统的控制.仿真结果证明了该线性监督控制器的有效性. 相似文献
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针对一类非线性多变量离散时间动态系统,提出了基于神经网络与多模型的非线性自适应广义预测解耦控制方法.该控制方法由线性鲁棒广义预测解耦控制器和神经网络非线性广义预测解耦控制器以及切换机构组成.线性鲁棒广义预测解耦控制器用于保证闭环系统输入输出信号有界,神经网络非线性广义预测解耦控制器能够改善系统性能.切换策略通过对上述两种控制器的切换,保证系统稳定的同时,改善系统性能.同时本文给出了所提自适应解耦控制方法的稳定性和收敛性分析.最后,通过仿真实例验证了该方法的有效性. 相似文献
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This paper introduces a new decentralized adaptive neural network controller for a class of large-scale nonlinear systems with unknown non-affine subsystems and unknown interconnections represented by nonlinear functions. A radial basis function neural network is used to represent the controller’s structure. The stability of the closed loop system is guaranteed through Lyapunov stability analysis. The effectiveness of the proposed decentralized adaptive controller is illustrated by considering two nonlinear systems: a two-inverted pendulum and a turbo generator. The simulation results verify the merits of the proposed controller. 相似文献
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针对一类未知的非线性系统,利用输入/输出线性化将其变换为部分线性可控系统,通过RBF神经网络对未知非线性函数进行逼近,提出了一种基于RBF神经网络的自适应滑模控制,并设计了自适应滑模控制器;提出了一种连续函数,很好地减少了抖振现象,使得闭环系统状态一致稳定最终有界。实验结果验证了方法的有效性。 相似文献
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Yue Fu Author Vitae Author Vitae 《Automatica》2007,43(6):1101-1110
In this paper, a multivariable adaptive control approach is proposed for a class of unknown nonlinear multivariable discrete-time dynamical systems. By introducing a k-difference operator, the nonlinear terms of the system are not required to be globally bounded. The proposed adaptive control scheme is composed of a linear adaptive controller, a neural-network-based nonlinear adaptive controller and a switching mechanism. The linear controller can assure boundedness of the input and output signals, and the neural network nonlinear controller can improve performance of the system. By using the switching scheme between the linear and nonlinear controllers, it is demonstrated that improved performance and stability can be achieved simultaneously. Theory analysis and simulation results are presented to show the effectiveness of the proposed method. 相似文献
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Houda Salhi Samira Kamoun Najib Essounbouli Abdelaziz Hamzaoui 《International journal of control》2016,89(3):611-622
In this paper, we propose an adaptive control scheme that can be applied to nonlinear systems with unknown parameters. The considered class of nonlinear systems is described by the block-oriented models, specifically, the Wiener models. These models consist of dynamic linear blocks in series with static nonlinear blocks. The proposed adaptive control method is based on the inverse of the nonlinear function block and on the discrete-time sliding-mode controller. The parameters adaptation are performed using a new recursive parametric estimation algorithm. This algorithm is developed using the adjustable model method and the least squares technique. A recursive least squares (RLS) algorithm is used to estimate the inverse nonlinear function. A time-varying gain is proposed, in the discrete-time sliding mode controller, to reduce the chattering problem. The stability of the closed-loop nonlinear system, with the proposed adaptive control scheme, has been proved. An application to a pH neutralisation process has been carried out and the simulation results clearly show the effectiveness of the proposed adaptive control scheme. 相似文献
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In this paper, a stable adaptive fuzzy sliding mode based tracking control is developed for a class of nonlinear MIMO systems that are represented by input output models involving system uncertainties and external disturbances. The main contribution of the proposed method is that the structure of the controller system is partially unknown and does not require the bounds of uncertainties and disturbance to be known. First, a fuzzy logic system is designed to estimate the unknown function. Secondly, in order to eliminate the chattering phenomenon brought by the conventional variable structure control, the signum function is replaced by an adaptive Proportional Derivative (PD) term in the proposed approach. All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis, so that convergence to zero of tracking errors and boudedness of all signals in the closed-loop system can be guaranteed. Finally, a mass-spring-damper system is simulated to demonstrate the validity and the effectiveness of the proposed controller. 相似文献
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非线性系统的间接自适应模糊输出反馈监督控制 总被引:1,自引:0,他引:1
In this paper, an indirect adaptive fuzzy output feedback controller with supervisory mode for a class of unknown nonlinear systems is developed. The proposed approach does not need the availability of the state variables, moreover, a supervisory controller is appended to the adaptive fuzzy controller to force the state to be within the constraint set. Therefore, if the adaptive fuzzy controller cannot maintain the stability, the supervisory controller starts to work to guarantee stability. On the other hand, if the adaptive fuzzy controller works well, the supervisory controller will be deactivated. The overall adaptive fuzzy control scheme guarantees the stability of the whole closed-loop systems. The simulation results confirm the effectiveness of the proposed method. 相似文献
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TONG Shao-Cheng CHAI Tian-You 《自动化学报》2005,(2)
In this paper, an indirect adaptive fuzzy output feedback controller with supervisory mode for a class of unknown nonlinear systems is developed. The proposed approach does not need the availability of the state variables, moreover, a supervisory controller is appended to the adaptive fuzzy controller to force the state to be within the constraint set. Therefore, if the adaptive fuzzy controller cannot maintain the stability, the supervisory controller starts to work to guarantee stability. On the other hand, if the adaptive fuzzy controller works well, the supervisory controller will be de-activated. The overall adaptive fuzzy control scheme guarantees the stability of the whole closed-loop systems. The simulation results confirm the effectiveness of the proposed method. 相似文献
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针对一类非线性离散时间动态系统, 提出了一种新的非线性自适应切换控制方法. 该方法首先把非线性项分解为前一拍可测部分与未知增量和的形式, 并充分利用被控对象的大数据信息和知识, 把非线性项前一拍可测数据与未知增量都用于控制器设计, 分别设计了线性自适应控制器, 带有非线性项前一拍可测数据补偿的非线性自适应控制器以及带有非线性项未知增量估计与补偿的非线性自适应控制器. 三个自适应控制器通过切换函数和切换规则来协调控制被控对象. 既保证了闭环系统的稳定性, 同时又提高了闭环系统的性能. 分析了闭环切换系统的稳定性和收敛性. 最后, 通过水箱液位系统的物理实验, 实验结果验证了所提算法的有效性. 相似文献