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1.
针对带非线性摩擦力矩和负载扰动的高精度猎雷声纳基阵姿态稳定系统,提出了一种基于神经网络的自适应反步法控制方法。其中神经网络用于估计未知非线性摩擦力矩,进而设计反步法控制器和参数自适应律来对神经网络估计误差和负载扰动进行补偿。最后应用Lyapunov方法证明了所提出的自适应控制器能保证闭环系统的稳定性,并且可以通过选择适当的控制器参数来调整收敛率。仿真结果表明,基于神经网络的自适应反步法控制方法与PID控制相比,系统的动、静态性能指标及鲁棒性得到了全面的改善,与双闭环PID控制相比,跟踪精度提高了3倍多。  相似文献   

2.
This paper proposes a new neural network ? synchronization (NNHS) scheme for unknown chaotic systems. In the proposed framework, a dynamic neural network is constructed as an alternative to approximate the chaotic system. Based on this neural network and linear matrix inequality (LMI) formulation, the NNHS controller and the learning law are presented to reduce the effect of disturbance to an ? norm constraint. It is shown that finding the NNHS controller and the learning law can be transformed into the LMI problem and solved using the convex optimization method. A numerical example is presented to demonstrate the validity of the proposed NNHS scheme.  相似文献   

3.
This paper proposes a new neural network ℋ synchronization (NNHS) scheme for unknown chaotic systems. In the proposed framework, a dynamic neural network is constructed as an alternative to approximate the chaotic system. Based on this neural network and linear matrix inequality (LMI) formulation, the NNHS controller and the learning law are presented to reduce the effect of disturbance to an ℋ norm constraint. It is shown that finding the NNHS controller and the learning law can be transformed into the LMI problem and solved using the convex optimization method. A numerical example is presented to demonstrate the validity of the proposed NNHS scheme.  相似文献   

4.
This paper presents a new technique using a recurrent non-singleton type-2 sequential fuzzy neural network (RNT2SFNN) for synchronization of the fractional-order chaotic systems with time-varying delay and uncertain dynamics. The consequent parameters of the proposed RNT2SFNN are learned based on the Lyapunov–Krasovskii stability analysis. The proposed control method is used to synchronize two non-identical and identical fractional-order chaotic systems, with time-varying delay. Also, to demonstrate the performance of the proposed control method, in the other practical applications, the proposed controller is applied to synchronize the master–slave bilateral teleoperation problem with time-varying delay. Simulation results show that the proposed control scenario results in good performance in the presence of external disturbance, unknown functions in the dynamics of the system and also time-varying delay in the control signal and the dynamics of system. Finally, the effectiveness of proposed RNT2SFNN is verified by a nonlinear identification problem and its performance is compared with other well-known neural networks.  相似文献   

5.
Adaptive sliding mode control of dynamic system using RBF neural network   总被引:1,自引:0,他引:1  
This paper presents a robust adaptive sliding mode control strategy using radial basis function (RBF) neural network (NN) for a class of time varying system in the presence of model uncertainties and external disturbance. Adaptive RBF neural network controller that can learn the unknown upper bound of model uncertainties and external disturbances is incorporated into the adaptive sliding mode control system in the same Lyapunov framework. The proposed adaptive sliding mode controller can on line update the estimates of system dynamics. The asymptotical stability of the closed-loop system, the convergence of the neural network weight-updating process, and the boundedness of the neural network weight estimation errors can be strictly guaranteed. Numerical simulation for a MEMS triaxial angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive RBF sliding mode control scheme.  相似文献   

6.
In this paper, we discuss a robust disturbance rejection method for dealing with disturbances of unknown frequencies. Unlike many other approaches, the method proposed here does not require the disturbance frequencies of the separate harmonics to be estimated. The current approach is based on disturbance reduction and disturbance suppression. This novel disturbance reduction controller consists of an inverse of the nominal model with an input deduction and a high gain integral term. The proposed controller can reduce both periodic and nonperiodic unknown disturbances with uncertainties in both stable and unstable systems. In addition, undesired responses caused by residual disturbances and residual modeling uncertainties are suppressed by combining the novel disturbance reduction controller with a sliding mode controller. The simulation results demonstrate that the proposed disturbance rejection method performs well under different disturbance inputs including random signals.  相似文献   

7.
This paper proposes a robust adaptive backstepping synchronization method for a class of uncertain chaotic systems. Unknown factors including system uncertainties and external disturbances are estimated by a fuzzy disturbance observer. By use of the fuzzy disturbance observer, any prior information about the unknown factors is not need. The proposed method using the estimated values guarantees the global synchronization for chaotic systems with mismatched uncertainties in the sense of uniform ultimate boundedness. Finally, numerical examples are presented to show the effectiveness of the method.  相似文献   

8.
探讨了载体位置和姿态都不受控时,漂浮基空间机械臂在带有关节力矩输出死区及外部干扰情况下轨迹跟踪的控制算法设计问题。死区与外部干扰影响系统的跟踪精度与稳定性。为此引入积分型切换函数,减少外部干扰引起的稳态误差,并利用径向基函数神经网络逼近动力学方程的未知部分,设计了一种积分滑模神经网络控制方案。控制算法的优点是,在死区斜率与边界参数不确定及最优逼近误差上确界未知的条件下,可以利用最优逼近误差、死区及干扰的补偿项来消除影响。李亚普诺夫稳定性分析证明了闭环系统的稳定性,且轨迹跟踪误差将收敛到0的某个小邻域内。仿真算例证实了该控制算法的有效性,实现了空间机械臂的轨迹跟踪控制。  相似文献   

9.
Yang  Yikun  Yang  Bintang  Niu  Muqing 《Nonlinear dynamics》2018,93(3):1109-1120
An adaptive dynamic surface control (DSC) scheme is proposed for the multi-input multi-output attitude control of near-space hypersonic vehicles (NHV). The proposed control strategy can improve the control performance of NHV despite uncertainties and external disturbances. The proposed controller combines dynamic surface control and radial basis function neural network (RBFNN) and is designed to control the longitudinal dynamics of NHV. The DSC technique is used to handle the problem of “explosion of complexity” inherent to the conventional backstepping method. RBFNN is used to approximate the unknown nonlinear function, and a robustness component is introduced in the controller to cancel the influence of compound disturbance and improve robustness and adaptation of the system. Simulation results show that the proposed strategy possesses good robustness and fast response.  相似文献   

10.
Wei Wang  Yuling Song 《Meccanica》2012,47(8):2027-2039
Traffic accidents are often caused by vibration of automotive steering because the vibration can make a vehicle run like a snake. A?novel semi-active vibration control strategy of automotive steering with magneto-rheological (MR) damper is proposed in this paper. An adaptive RBF neural sliding mode controller is designed for the vibration system. It is showed that an equivalent dynamic model for the vibration system is established by using Lagrange method, and then treats it as actual system partially. A?feedback control law is designed to make this nominal model stable. Uncertain part of system and outside disturbance are estimated using RBF neural network, and their upper boundary is obtained automatically. By constructing reasonable switch function, state variables can arrive at origin asymptotically along the sliding mode. Strong robust character of control system is proved by stability analysis and a numerical simulation example is performed to support this control scheme.  相似文献   

11.
经典的卡尔曼滤波器要求假设系统的动态模型和观测模型的噪声统计特性已知,而组合导航系统的噪声具有非先验性。为了解决这一问题,提出了一种新型复合神经网络(CNN)辅助卡尔曼滤波器(Kalman)。仿真试验结果表明:该辅助算法的精度与一般卡尔曼算法相比提高了2倍,收敛时间缩短近200s,并有效地克服了传统神经网络学习速度慢、泛化能力弱的缺点,使系统具有自适应能力以应付动态环境的扰动。  相似文献   

12.
Zhang  Mingyue  Guan  Yongliang  Li  Chao  Luo  Sha  Li  Qingdang 《Nonlinear dynamics》2023,111(9):8347-8368

A composite controller based on a backstepping controller with an adaptive fuzzy logic system and a nonlinear disturbance observer is proposed in this paper to address the disturbance and uncertainty issues in the control of the optoelectronic stabilized platform. The matched and unmatched disturbances and system uncertainty are included in the stabilized platform model. The system's uncertainty and disturbance are approximated and estimated using an adaptive fuzzy logic system and a nonlinear disturbance observer. Moreover, the backstepping control algorithm is utilized to control the system. The simulations are performed in four states to confirm the viability of the proposed control technique. The proportional integral controller, proportional integral-disturbance observer controller, and fuzzy backstepping controller are contrasted with the proposed controller. It has been noted that the proposed controller's instantaneous disturbance's highest value is 5.1°/s. The maximal value of the coupling output for the two gimbals utilizing the proposed controller, however, is 0.0008°/s and 0.0018°/s, respectively. The findings presented here demonstrate that the backstepping controller, which is based on an adaptive fuzzy logic system and a nonlinear disturbance observer, is capable of precise tracking and dynamic tracking of a stabilized platform under disturbance and uncertainty.

  相似文献   

13.
为提高惯性稳定平台控制系统的稳定精度,在常规PID控制的基础上提出了一种扩张状态观测器与PID相结合的复合控制算法。利用扩张状态观测器将惯性稳定平台的各种内部扰动和外部扰动都视为总和扰动并观测出来,然后通过PID控制器进行误差反馈控制,从而提高控制系统的扰动抑制能力与稳定精度。以Lu Gre摩擦模型加入控制模型进行仿真分析,并通过北航自研的惯性稳定平台进行实验验证。结果表明:扩张状态观测器/PD复合控制方法具有高的扰动抑制能力,可显著提高稳定平台稳定精度。相比常规PID方法,扩张状态观测器/PD复合控制使横滚框和俯仰框的稳定精度分别提高了33.23%和55.01%。  相似文献   

14.
The nonlinear conjugate gradient method (CGM) is a very effective iterative method for solving large-scale optimal problems. In this paper, based on a variant of Polak–Ribière–Polyak method, two modified CGMs with disturbance factors are proposed. By the disturbance factors, the two proposed methods not only generate sufficient descent direction at each iteration but also converge globally for nonconvex minimization if the strong Wolfe line search is used. Finally, elementary numerical experiment results are reported, which show that the proposed methods are promising.  相似文献   

15.
In this work, we deal with autonomous tracking and disturbance rejection problem of quadrotor vehicle flying in uncertain environment. The vehicles kinematic and modeling error uncertainties are associated with external disturbance, inertia, mass, and nonlinear aerodynamic forces and moments. The proposed method integrate the techniques from adaptive control and robust control theory. Robust and adaptive control algorithms for translational and orientation tracking are derived using Lyapunov method. It is shown in our analysis that the altitude, position, and attitude tracking errors are bounded and their bounds asymptotically converge to zero in Lyapunov sense. Simulation results on a commercial quadrotor flying vehicle are given to demonstrate the effectiveness of theoretical arguments for real world application.  相似文献   

16.
Disturbance compensation is one of the major issues for underwater robots to hover as a mobile platform and to manipulate an object in an underwater environment. This paper presents a new strategy of disturbance compensation for a mobile dual-arm underwater robot using internal torques derived from redundant parallel mechanism theory. A model of the robot was analyzed by redundant serial and parallel mechanisms at the same time. The joint torque to operate the robot is obtained from a redundant serial mechanism model with null-space projection due to redundancy. The joint torque derived from the redundant parallel kinematic model is calculated to perfectly compensate for disturbances to the mobile platform and is included in the solution of the joint torque based on the serial redundant model. The resultant joint torque can generate force on the end-effector for required tasks and forces for disturbance compensation simultaneously . A simulation shows the performance of this disturbance compensation strategy. The joint torque based on the algorithm generates the desired task force and the disturbance compensation force together, and a little additional joint torque can generate a large internal force effectively due to the characteristics of a redundant parallel mechanism. The proposed method is more effective than compensation methods using thrusting force on the mobile platform.  相似文献   

17.
In this paper, a generalized control scheme for the class of nonlinear multiple-input multiple-output (MIMO) uncertain system with cross-coupling and nonlinearity in their input channels under the influence of external disturbances is presented. This is accomplished using full-order model following sliding mode control based on uncertainty and disturbance estimator (UDE) technique. The fourth-order uncertain nonlinear MIMO system is separated into multiple single-input single-output double integrator subsystems by considering the effect of input coupling and nonlinearity as a disturbance. The UDE is designed to estimate the plant uncertainties as well as external disturbances without the knowledge of the bounds on the uncertainties. The proposed method decouples the system and overcomes the problem of high initial control which ultimately eliminates the reaching phase and the chattering phenomenon which is generally occurred in sliding mode control. The effectiveness of the proposed control scheme is demonstrated through numerical simulation of two-link manipulator.  相似文献   

18.
重力扰动已经成为高精度长航时惯导系统的主要误差源之一。针对船用高精度惯导系统的重力扰动抑制问题,从舰船INS误差模型出发,推导了重力扰动在惯导系统中的传播特性。仿真结果表明垂线偏差将引起系统较大的舒拉振荡误差。为抑制重力扰动对系统的影响,引入常速度误差反馈阻尼网络和相位超前串联阻尼网络。分析了重力扰动在水平阻尼网络中的传递特性,实现了相应滤波器的设计。在此基础上完成了实验验证,海上试验结果表明,所引入的两种阻尼网络都能够阻尼掉重力扰动引起的舒拉振荡型导航误差,其中,相位超前串联阻尼网络效果更优,抑制率达到70%以上。  相似文献   

19.
Finite time integral sliding mode control of hypersonic vehicles   总被引:1,自引:0,他引:1  
This study investigates the tracking control problem for the longitudinal model of an airbreathing hypersonic vehicle (AHV) with external disturbances. By introducing finite time integral sliding mode manifolds, a novel finite time control method is designed for the longitudinal model of an AHV. This control method makes the velocity and altitude track the reference signals in finite time. Meanwhile, considering the large chattering phenomenon caused by high switching gains, an improved sliding mode control method based on nonlinear disturbance observer is proposed to reduce chattering. Through disturbance estimation for feedforward compensation, the improved sliding mode controller may take a smaller value for the switching gain without sacrificing disturbance rejection performance. Simulation results are provided to confirm the effectiveness of the proposed approach.  相似文献   

20.
针对空间连续型机器人系统三臂节执行器并发故障的问题,提出一种自适应鲁棒容错控制算法.采用非奇异快速终端滑模控制器,并通过自适应RBF(Radial Basis Function)神经网络在线调整控制器的切换项增益,使控制器在模型参数摄动和外部干扰下依旧具有较高的跟踪精度和较强的鲁棒性.基于Lyapunov稳定性理论,证...  相似文献   

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