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1.
提出一种不确定T-S模型的模糊滑模自适应控制方法。通过变换将该模型转换成3个组成部分:线性标称系统,已知非线性部分和未知不确定部分。针对它们设计3个控制器,其作用分别为:强迫系统沿着滑模面运动,消除已知扰动对线性标称系统的影响,克服不确定扰动(采用模糊滑模自适应控制,无需知道不确定的界限)。该方法无需求正定矩阵就能保证系统全局稳定。  相似文献   

2.
基于模糊控制理论和滑模控制理论以及自适应控制理论,研究了一类含有外部扰动的不确定分数阶混沌系统的混合投影同步问题.提出了一种自适应模糊滑模控制的分数阶混沌系统投影同步方法.模糊逻辑系统用来逼近未知的非线性函数和外部扰动,并且对逼近误差采用了自适应控制,同时构造了一种具有较强鲁棒性的分数阶积分滑模面.应用分数阶Barbalat引理设计了自适应模糊滑模控制器和参数自适应律.最后数值仿真结果验证了所提控制方法的有效性.  相似文献   

3.
针对带有内部不确定性及外部扰动的陀螺仪混沌系统的同步问题,提出了一种参数自适应滑模控制方法,并给出参数自适应律.该方法不依赖被控混沌系统的数学模型,可以快速跟踪主混沌系统.时域及复频域理论分析表明,由参数自适应滑模控制器组成的闭环控制系统是全局渐近稳定的,而且参数自适应滑模控制器具有良好的抗扰动鲁棒性.仿真结果表明该控制方法计算量小、响应速度快、控制精度高、抗扰动鲁棒性强,在非线性不确定系统控制领域具有广泛的应用价值.  相似文献   

4.
针对四旋翼无人机姿态控制中模型不完整、部分参数和扰动不确定的问题,提出了一种基于神经网络的自适应控制方法,采用RBF神经网络对无人机姿态动力学模型中不确定和扰动部分进行学习,设计了以类反步法为基础,包含反馈控制和神经网络控制的自适应控制器,实现了对未知动态的准确逼近,解决了传统控制方法中过于依赖精确模型的问题。同时设计了神经网络的权值自适应律,实现了控制过程中的在线学习和调整,并且通过李雅普诺夫方法证明了闭环系统的稳定性。仿真结果表明,在存在较大扰动的情况下,上述控制器可得到很好的控制效果,可以实现误差的快速收敛,具有较好的鲁棒性和自适应性。  相似文献   

5.
王宁  王永 《自动化学报》2018,44(4):685-695
针对具有未知外界扰动和系统不确定性的四旋翼飞行器,提出了一种基于模糊不确定观测器(Fuzzy uncertainty observer,FUO)的自适应动态面轨迹跟踪控制方法.通过将四旋翼飞行器系统分解为位置、姿态角和角速率三个动态子系统,使得各子系统虚拟控制器能够充分考虑欠驱动约束;采用一阶低通滤波器重构虚拟控制信号及其一阶导数,实现四旋翼跟踪控制设计的迭代解耦;设计了一种模糊不确定观测器,用以估计和补偿未知外界扰动与系统不确定性,从而确保闭环系统的稳定性和跟踪误差与其他系统信号的一致有界性.仿真研究验证了所提出的控制方法的有效性和优越性.  相似文献   

6.
针对一类满足匹配条件的不确定性时滞关联大系统,提出了一种基于Lyapunov稳定性理论的分散变结构自适应控制方案.通过引入积分滑模和能在线估计不确定性扰动与时滞关联的界的自适应算法,保证了闭环系统的渐近稳定性,实现了系统的鲁棒自适应控制.所提出的方案具有较强的工程实用性.算例仿真的结果表明了该控制方案的可行性.  相似文献   

7.
针对一类存在模型不确定性和未知非线性扰动的机器人系统,考虑其不确定项和未知扰动项的上界是关于系统状态的普通高阶多项式,结合模糊系统的逼近能力,提出了一种基于滑模控制原理的自适应模糊分散控制方法.该方法不仅能够使得关节之间相互耦合的机器人各关节的控制器仅由本关节的信息就能完全确定,而且消除了现存文献在设计机器人分散控制器...  相似文献   

8.
针对一类具有周期扰动和输入时滞的不确定非线性系统,提出一种基于神经网络的自适应动态面控制方案.将径向基函数神经网络和傅里叶级数展开结合,构造一种混合函数逼近器来逼近系统中未知的周期扰动函数.通过引入一个积分项解决输入时滞问题,同时采用带有非线性滤波器的动态面控制方法,避免自适应反推控制方法中普遍存在的复杂性爆炸问题.所提出的神经网络控制方案能够确保闭环系统中所有信号是半全局有界的,并且系统输出能渐近地跟踪给定的参考信号.两个仿真结果验证了所提出的控制方案是有效的.  相似文献   

9.
针对无模型自适应控制方法在测量扰动作用下控制效果不佳的问题, 本文提出了一种新的扰动抑制无模 型自适应控制方案. 首先基于受控系统的动态线性化数据模型及测量扰动的统计特性, 在最小方差估计准则下推导 了基于系统输入输出数据的改进卡尔曼滤波器. 然后基于此滤波器给出了一种新的扰动抑制无模型自适应控制方 案. 该方案仅需用到受控系统的输入输出数据, 即可实现在强测量扰动作用下系统的无模型自适应控制. 仿真结果 显示, 相比现有的扰动抑制无模型自适应控制方案, 该方案在系统跟踪常值参考信号、时变参考信号时均能有效地 抑制测量扰动, 适用性更好的同时可以获得更小的跟踪误差及更大的数据信噪比.  相似文献   

10.
针对被控对象大惯性、不确定特点,提出一种变风量空调系统室温智能控制方案,建立了变风量空调系统的数学模型,采用了串级控制策略,主控制器采用一种新的可变论域自适应模糊PID控制.用串级控制反馈控制改善性能,抑制一、二次扰动,减小了各种扰动对室温的影响.采用可变论域自适应模糊PID控制.进行仿真.结果证明,变风量空调系统具有良好的动态性和稳定性.当空调房间模型结构参数发生变化时,控制系统鲁棒性好.  相似文献   

11.
一类非线性不确定系统的最小方差神经控制   总被引:3,自引:0,他引:3  
针对一类非线性不确定系统,提出一种新的基于神经网络动态补偿的最小方差控制方法(MVNNC)。这种控制系统将传统的最小方差控制技术与神经网络优良的非线性逼近能力相结合,从而能有效地消除不确定性引起的控制误差,仿真实验表明,这种最小方差神经控制系统具有较强的鲁棒性和良好的动态性能。  相似文献   

12.
In this paper, a direct fuzzy adaptive robust control approach is proposed for a class of SISO nonlinear systems with completely unknown virtual control directions, unknown nonlinearities, unmodeled dynamics and dynamic disturbances. In the backstepping recursive design, fuzzy logic systems are employed to approximate the combined nonlinear uncertainties, a dynamic signal and Nussbaum gain technique are introduced into the control scheme to dominate the dynamic uncertainties and solve the unknown signs of virtual control directions, respectively. It is proved that the proposed robust fuzzy adaptive scheme can guarantee the all signals in the closed-loop system are semi-globally uniformly ultimately bounded. The effectiveness of the proposed approach is illustrated via three examples.  相似文献   

13.
电液伺服系统的多滑模鲁棒自适应控制   总被引:7,自引:0,他引:7  
针对一类参数与外负载非匹配不确定的非线性高阶系统,提出了一种基于逐步递推方法的多滑模鲁棒自适应控制策略.应用逐步递推的多滑模控制方法简化了高阶系统的控制问题,同时在自适应控制中加入鲁棒控制的方法,以消除不确定性对控制性能的影响.首先利用逐步递推方法与状态反馈精确线性化理论,得出确定系统的多滑模控制器设计方法;然后基于Lyapunov稳定性分析方法,给出不确定系统的参数自适应律,及鲁棒自适应控制器的设计方法.本文把该控制策略应用到电液伺服系统的位置跟踪控制中,仿真结果显示,该控制方法具有较强的鲁棒性及良好的跟踪效果.  相似文献   

14.
This paper presents an approach to design robust fixed structure controllers for uncertain systems using a finite set of measurements in the frequency domain. In traditional control system design, usually, based on measurements, a model of the plant, which is only an approximation of the physical system, is first built, and then control approaches are used to design a controller based on the identified model. Errors associated with the identification process as well as the inevitable uncertainties associated with plant parameter variations, external disturbances, measurement noise, etc. are expected to all contribute to the degradation of the performance of such a scheme. In this paper, we propose a nonparametric method that uses frequency-domain data to directly design a robust controller, for a class of uncertainties, without the need for model identification. The proposed technique, which is based on interval analysis, allows us to take into account the plant uncertainties during the controller synthesis itself. The technique relies on computing the controller parameters for which the set of all possible frequency responses of the closed-loop system are included in the envelope of a desired frequency response. Such an inclusion problem can be solved using interval techniques. The main advantages of the proposed approach are: (1) the control design does not require any mathematical model, (2) the controller is robust with respect to plant uncertainties, and (3) the controller structure can be chosen a priori, which allows us to select low-order controllers. To illustrate the proposed method and demonstrate its efficacy, an application to an air flow heating system is presented.  相似文献   

15.
By considering the dynamic response of a robot manipulator as characterized by the sliding function, a technique is proposed to estimate the perturbation in the robot control system. Perturbation compensation is then incorporated in the design of a robust control law to cancel the effects of system parametric uncertainties and external disturbances. A normalized power rate component is introduced to replace the discontinuous control that is usually associated with variable structure system. The suggested robust control law ensures that the robot control system reaches an user specified neighbourhood of the sliding manifold in finite time and with prescribed transient behaviour. Explicit estimates of the bounds on modelling errors and external disturbances are not required while signal measurement uncertainties can be accommodated. Furthermore, using the equivalent control concept, a very simple expression is derived to estimate the system perturbation signal. Detailed computer simulation results are presented to demonstrate the effectiveness of the proposed control law.  相似文献   

16.
不确定非线性系统的自适应反推高阶终端滑模控制   总被引:1,自引:0,他引:1       下载免费PDF全文
针对一类非匹配不确定非线性系统,提出一种神经网络自适应反推高阶终端滑模控制方案.反推设计的前1步利用神经网络逼近未知非线性函数,结合动态面控制设计虚拟控制律,避免传统反推设计存在的计算复杂性问题,并抑制非匹配不确定性的影响;第步结合非奇异终端滑模设计高阶滑模控制律,去除控制抖振,使系统对于匹配和非匹配不确定性均具有鲁棒性.理论分析证明了闭环系统状态半全局一致终结有界,仿真结果表明了所提出方法的有效性.  相似文献   

17.
This paper deals with a signal‐based robust adaptive approximation technique for a proportional derivative (PD) regulator which is applied to an electromagnetic valve actuator control for camless internal combustion engines. PD regulators generate very high spikes in the presence of unavoidable noise. These spikes cause high power dissipation and poor dynamic performance with a lack of precision. The presented method allows the reduction of the noise and not robust nonlinear uncertainties effects by using minimum variance analysis. The technique with which the PD regulator is approximated does not depend on the model of the controlled system. Hence, the technique is quite general and can be applied to any type of system. In addition, this paper describes a feasible real‐time self‐tuning of an approximated discrete PD regulator using a backward Euler technique. The main contribution of the paper is the presentation of an approximated PD controller using a minimum variance control strategy together with a weighted least squares method to adapt the parameters of this approximated controller. This control law realises a robust control technique with respect to the noise and nonlinear uncertainties. Moreover, a comparison with the approximate PD controller proposed in MATLAB by Mathworks is provided. The presented technique ensures a good dynamic performance, including low dissipation as well as accurate positioning and soft landing control.  相似文献   

18.
马克茂 《控制与决策》2013,28(2):201-204
针对大型空间飞行器的大角度姿态控制问题,考虑航天器惯量矩阵中的不确定性和外部扰动力矩,应用高阶滑模控制方法设计了姿态跟踪控制律.采用的二阶滑模控制方法改善了系统针对不确定性及外部扰动的鲁棒性,并减弱了振颤现象.针对所设计的控制器进行了仿真验证,并与一阶滑模控制进行了对比,仿真结果表明了所提出方法的有效性.  相似文献   

19.
本文针对控制力矩陀螺框架伺服系统中存在的参数不确定性、摩擦非线性及外部干扰问题,提出了一种考虑LuGre摩擦的自适应鲁棒控制方法.针对陀螺框架伺服系统未知惯量和阻尼系数、LuGre摩擦参数不确定性及未知外部干扰上界,设计参数更新律对其进行估计.在此基础上,为提高系统对不确定参数及未知干扰的鲁棒性,设计带有期望补偿的自适应鲁棒控制器,可实现对LuGre摩擦非线性的精确补偿,同时减小测量信号噪声及外部干扰对系统的不利影响.应用Lyapunov稳定性理论分析了闭环系统的稳定性.对挠性航天器姿态机动控制的仿真结果,验证了所提方法的有效性.  相似文献   

20.
A robust sliding mode approach combined with a field oriented control (FOC) for induction motor (IM) speed control is presented. The proposed sliding mode control (SMC) design uses an adaptive switching gain and an integrator. This approach guarantees the same robustness and dynamic performance of traditional SMC algorithms. And at the same time, it attenuates the chattering phenomenon, which is the main drawback in actual implementation of this technique. This approach is insensitive to uncertainties and permits to decrease the requirement for the bound of these uncertainties. The stability and robustness of the closed- loop system are proven analytically using the Lyapunov synthesis approach. The proposed method attenuates the effect of both uncertainties and external disturbances. Experimental results are presented to validate the effectiveness and the good performance of the developed method.  相似文献   

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