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针对飞行器在大机动飞行过程中气动参数不确定、外部未知干扰因素较多及系统建模可能存在误差等问题,设计了一种基于RBF神经网络的非线性自适应反演控制器。飞行器大机动飞行过程中的广义不确定性由RBF神经网络在线逼近,神经网络权值矩阵通过自适应律在线更新。反演设计过程中对虚拟控制律的反复求导带来的"项数膨胀"问题,通过引入一阶滤波器来解决。通过构造Lyapunov函数,证明了闭环系统所有信号均有界,并且跟踪误差指数收敛到零的一个小邻域内。对某飞行器进行了大机动飞行仿真,结果表明该控制器具有良好的跟踪效果和鲁棒性。 相似文献
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研究了一类单输入单输出仿射非线性系统的自适应控制问题.采用反馈线性化方法设计控制器,用神经网络逼近系统中的未知非线性函数,并在神经网络权值的自适应律中引入权值误差的概念,以改善系统的动态性能.同时采用滑模控制方法设计补偿器,提高了系统的鲁棒性.理论分析及仿真结果表明,所设计的控制器,不仅能解决该系统的轨迹跟踪控制问题,... 相似文献
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阐述在未知扰动下含有未知量的非线性多智能体系统控制问题。提出了一种分布式设计,可实现在加权有向图拓扑下的多智能体系统一致性跟踪控制。每个智能体由有未知量的严格反馈非线性系统建模,并包含外部干扰。通过backstepping技术和神经网络的方法,在只需要自己和相邻智能体之间的相对状态信息的情况下,为每个从智能体构造自适应分布式控制器。设计的控制器和自适应控制率可保证领航者与所有跟随器之间的跟踪误差收敛到原点的一个小邻域。运用Radial Basis Function(RBF)神经网络用于逼近未知的非线性函数,并设计了一个非线性扰动观测器用于估计未知的外部扰动。采用Nussbaum函数来处理模型中未知符号的参数,仿真结果验证了所提方法的有效性。 相似文献
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为了克服未知的执行器故障对四旋翼无人机编队飞行的影响,提出了一种基于动态规划的最优协同容错控制律。首先,建立了四旋翼无人机模型,然后,基于动态规划设计了最优协同控制律,利用RBF神经网络逼近最优性能指标函数,设计了自适应律来估计未知的执行器故障,最终得到的最优协同容错控制律可实现对无人机编队飞行的高精度控制。通过对比仿真验证了设计的控制律具有更优的编队控制效果,编队飞行的最大轨迹跟踪误差仅为0.04 m,控制精度较高,设计的自适应律具有更优的故障估计效果,最大估计误差仅为0.05 N·m,实现了对四旋翼无人机编队的安全稳定控制。 相似文献
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本文针对一类执行器带未知死区的仿射非线性系统,提出了一种新型的神经网络自适应控制器的设计方法,该方法首先引入一个神经网络来估计对象的部分未知非线性动态行为,再基于隐函数定理构造另一个静态神经网络作为新型补偿器以补偿执行器的未知不对称的死区非线性.本文利用Lyapunov理论在给出光滑的控制律的同时严格证明了整个闭环系统的跟踪误差以及各个神经网络权参数的一致最终有界性,而且通过调节设计参数可以使系统的跟踪误差收敛到零附近的一个小邻域内.本文提出的控制方案可以保证对象在线稳定地跟踪任何光滑的目标轨迹,仿真研究表明了此控制方案的可行性和有效性. 相似文献
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针对可重复使用运载器(RLV)再入过程中存在的未知干扰、不确定性以及舵面部分失效(PELF)等问题,基于增量反演法(IBS)和跟踪微分干扰补偿器(TDDC)设计了鲁棒容错控制律.首先,对姿态角回路和角速率回路分别设计增量控制律,并引入误差积分项增强系统的鲁棒性.其次,对于传统增量反演法直接忽略掉的慢变项和泰勒展开高阶项,基于Sigmoid跟踪微分器设计了适用于IBS控制律的干扰补偿器对其进行估计和补偿.最后,仿真结果表明,相比于传统的增量反演法,所设计的控制律指令跟踪精度更高. 相似文献
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本文采用后推设计算法为一类严格反馈系统设计了基于方向基函数神经网络(DBFNN)的自适应控制器.在后推算法中的每步都引入一积分型的Lyapunov函数来设计一个虚拟控制器,并在最后一步为闭环系统综合设计了神经网络控制器.网络权值的调整基于所选择的Lyapunov函数,于是设计方案能保证整个闭环系统是最终一致有界的.把所设计控制方案用于带有未知参数和外部干扰的电力系统励磁控制中.仿真结果表明了所设计控制器的有效性. 相似文献
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Chih-Min Lin Chun-Fei Hsu 《Industrial Electronics, IEEE Transactions on》2002,49(1):115-123
A neural-network-based adaptive control (NNAC) design method is proposed to control an induction servomotor. In this NNAC design, a neural network (NN) controller is investigated to mimic a feedback linearization control law; and a compensation controller is designed to compensate for the approximation error between the feedback linearization control law and the NN controller. The interconnection weights of the NN can be online tuned in the sense of the Lyapunov stability theorem; thus, the stability of the control system can be guaranteed. Additionally, in this NNAC system design, an error estimation mechanism is investigated to estimate the bound of approximation error so that the chattering phenomenon of the control effort can be reduced. Simulation and experimental results show that the proposed NNAC servomotor control systems can achieve favorable tracking and robust performance with regard to parameter variations and external load disturbances 相似文献
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当飞机在大回环飞行中,由于受到空气动力学的扰动较大,需要进行飞行姿态稳定性控制,传统方法采用分段线性化控制方法,在大扰动条件下,飞行过程中各段的控制误差不断方法,导致飞行稳定性不好。提出一种基于自适应反步跟踪的飞行器反馈调整稳定性控制算法。构建大回环飞行中的飞行稳定性控制的参量模型系统,考虑外界干扰的情况下,进行飞行器反馈调整稳定性控制目标函数构建,采用自适应反步跟踪方法拟合控制过程的状态误差响应,实现控制器优化设计。仿真结果表明,采用该算法进行飞行器的稳定性控制,系统误差受到外界扰动的影响较小,控制器的自适应收敛性较高,展示了较好的应用性能。 相似文献
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《Industrial Electronics, IEEE Transactions on》2009,56(9):3296-3304
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This paper presents a controller structure for robust high speed and accuracy motion control systems. The overall control system consists of four elements: a friction compensator; a disturbance observer for the velocity loop; a position loop feedback controller; and a feedforward controller acting on the desired output. A parameter estimation technique coupled with friction compensation is used as the first step in the design process. The friction compensator is based on the experimental friction model and it compensates for unmodeled nonlinear friction. Stability of the closed-loop is provided by the feedback controller. The robust feedback controller based on the disturbance observer compensates for external disturbances and plant uncertainties. Precise tracking is achieved by the zero phase error tracking controller. Experimental results are presented to demonstrate performance improvement obtained by each element in the proposed robust control structure 相似文献
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《Mechatronics》2000,10(1-2):265-287
System performance of robot manipulators with nonadaptive controllers might degrade significantly in the presence of structured or unstructured uncertainties. In order to improve the system performance, a novel radial-basis-function (RBF) neural-network (NN) compensator is proposed. With the RBF NN compensator introduced, the system errors and the NN weights with large dispersion in the initial NN weights are guaranteed to be bounded in the Lyapunov sense. The NN weights of the RBF NN compensator are adaptively tuned. Several software-based controllers, including the computed-torque control (CTC) and a few RBF NN schemes, are implemented in an industrial manipulator in real time. Experimental results are obtained to demonstrate the relative effectiveness of the proposed controllers in improving the tracking performance of the robot manipulators associated with structured or unstructured uncertainties. 相似文献
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Faa-Jeng Lin Tzann-Shin Lee Chih-Hong Lin 《Industrial Electronics, IEEE Transactions on》2003,50(3):456-470
In this paper, a robust controller design with H/sub /spl infin// performance using a recurrent neural network (RNN) is proposed for the position tracking control of a permanent-magnet linear synchronous motor. The proposed robust H/sub /spl infin// controller, which comprises a RNN and a compensating control, is developed to reduce the influence of parameter variations and external disturbance on system performance. The RNN is adopted to estimate the dynamics of the lumped plant uncertainty, and the compensating controller is used to eliminate the effect of the higher order terms in Taylor series expansion of the minimum approximation error. The tracking performance is ensured in face of parameter variations, external disturbance and RNN estimation error once a prespecified H/sub /spl infin// performance requirement is achieved. The synthesis of the RNN training rules and compensating control are based on the solution of a nonlinear H/sub /spl infin// control problem corresponding to the desired H/sub /spl infin// performance requirement, which is solved via a choice of quadratic storage function. The proposed control method is able to track both the periodic step and sinusoidal commands with improved performance in face of large parameter perturbations and external disturbance. 相似文献
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Fault Tolerant Control for a Class of Nonlinear Systems with Application to Near Space Vehicle 总被引:1,自引:0,他引:1
Yufei Xu Bin Jiang Gang Tao Zhifeng Gao 《Circuits, Systems, and Signal Processing》2011,30(3):655-672
In this paper, a fault tolerant control (FTC) scheme, which is based on backstepping and neural network (NN) methodology,
is proposed for a general class of nonlinear systems with known structure and unknown faults. Firstly, the linearly parameterized
radial basis function (RBF) NNs are employed to approximate unknown system faults, and the network weights are adapted using
adaptive on-line parameter-learning algorithms. Then an adaptive backstepping based FTC is designed to compensate for the
effect of system faults. The asymptotical stability of the closed-loop system and uniform boundedness of the state tracking
errors are proved according to Lyapunov theory. Finally, the designed strategy is applied to near space vehicle (NSV) attitude
dynamics, and simulation results are presented to demonstrate the effectiveness of the proposed approach. 相似文献
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This paper studies the identification and the real-time control of an electrohydraulic servo system. The control strategy is based on the nonlinear backstepping approach. Emphasis is essentially on the tuning parameters effect and on how it influences the dynamic behavior of the errors. While the backstepping control ensures the global asymptotic stability of the system, the tuning parameters of the controller, nonetheless, do greatly affect the saturation and chattering in the control signal, and consequently, the dynamic errors. In fact, electrohydraulic systems are known to be highly nonlinear and non-differentiable due to many factors, such as leakage, friction, and especially, the fluid flow expression through the servo valve. These nonlinear terms appear in the closed loop dynamic errors. Their values are so large that in the presence of a poor design, they can easily overwhelm the effect of the controller parameters. Backstepping is used here because it is a powerful and robust nonlinear strategy. The experimental results are compared to those obtained with a real-time proportional-integral-derivative (PID) controller, to prove that classic linear controllers fail to achieve a good tracking of the desired output, especially, when the hydraulic actuator operates at the maximum load. Before going through the controller design, the system parameters are identified. Despite the nonlinearity of the system, identification is based on the recursive least squares method. This is done by rewriting the mathematical model of the system in a linear in parameters (LP) form. Finally, the experimental results will show the effectiveness of the proposed approach in terms of guaranteed stability and zero tracking error 相似文献