非线性时滞系统自适应模糊动态面控制

针对未知非线性系统控制器设计过程中引入逼近器过多的问题,提出一种简化的自适应模糊动态面控制器设计方案.在控制器设计过程中,仅采用一个模糊逻辑系统作为逼近器,使得所有的未知项得到补偿,同时采用自适应技术在线辨识未知参数和逼近误差上界.文中的控制方案克服了传统backstepping控制器中"复杂性膨胀"的问题.通过构造合适的Lyapunov函数,证明闭环系统的所有信号为半全局最终一致有界.仿真实例验证所提出的控制方案的有效性.     

基于性能的直流电机系统未知推力波动的自适应补偿控制

针对一类直流电机系统,设计基于性能的未知推力波动的自适应补偿控制器.由于推力波动中含有非线性化的未知参数,因此无法利用常规的自适应方法,通过直接估计这些参数对其影响进行补偿.根据未知推力波动的结构特性,基于Lipshitz条件引入推力波动项的放大技术,设计其内部非线性化未知参数的自适应估计律,精确补偿其影响,从而避免了简单的把波动看作未知扰动所造成的系统性能的损失.有别于现有模型,在模型变换中并未忽略微小等效电感的影响,使得系统模型更具一般性.仿真结果表明该自适应控制器可有效补偿推力波动的影响,实现对指令信号的高精度快速跟踪且具有较强的抗干扰性和鲁棒性.     

一类死区非线性输入系统的自适应模糊控制

针对一类具有死区非线性输入的非线性系统,基于滑模控制的基本原理,利用II型模糊逻辑系统对未知函数进行在线逼近,提出了一种具有监督器的自适应模糊滑模控制方法。该方法通过监督控制器保证闭环系统所有信号有界,并通过引入最优逼近误差的自适应补偿项来消除建模误差的影响。通过理论分析,证明了跟踪误差收敛到零。     

基于RBF神经网络的一类非线性时滞系统自适应控制器设计

针对一类带有未知非线性函数的严格反馈非线性时滞系统,设计了一种自适应神经网络控制器.选择径向基函数神经网络逼近未知的非线性函数.所提出的控制方案能保证闭环系统的所有信号是全局一致最终有界的.证明了跟踪误差信号将收敛于一个小紧集内.仿真实例验证了所提出方法的有效性.     

基于神经网络的一类非线性时滞系统自适应控制器设计

针对一类带有扰动和未知时滞的非线性系统,通过反步方法设计一种鲁棒自适应控制器.提出了一种新的Lyapunov-Krasovskii泛函,补偿了未知时滞项的不确定性.引入一种合适的偶函数,避免了控制器的奇异性问题.通过Lyapunov直接方法,证明了所设计的控制器能保证闭环系统所有信号全局一致最终有界.     

具有类反斜线回滞执行器的非线性系统的自适应控制

针对类反斜线回滞非线性系统,设计了自适应控制器,保持系统稳定并实现对参考信号的任意精度跟踪.在控制器设计中,通过构造足够光滑的非线性函数作为符号函数的逼近,从而解决了传统自适应控制器设计中由于符号函数的引入而导致控制器不连续的问题,避免了因此而产生的抖震现象.在系统模型中充分考虑未建模动态,使模型更具一般性.最后应用MATLAB软件进行仿真实验,结果进一步验证了该控制器的有效性.     

基于动态面技术的随机非线性关联系统的输出反馈控制

针对一类参数不确定且含有未知关联项的随机非线性关联系统,提出了一种自适应输出反馈控制方案.该方案利用K滤波器估计不可量测的系统状态,将动态面技术与输出反馈控制相结合,避免了传统后推设计过程中对虚拟控制律反复求导出现的"复杂性膨胀"问题,设计的自适应动态面控制器可以确保闭环系统中的所有信号在概率意义下半全局一致终结有界,且跟踪误差收敛到一个小的残差集内.     

具有未建模动态耦合大系统的分散自适应动态面控制

对一类具有未建模动态的非线性耦合大系统,利用神经网络逼近未知非线性连续函数,提出一种分散自适应神经动态面控制方案,该方案通过引入一个动态信号克服了未建模动态,利用分离技术放宽了对系统扰动及耦合项的限制条件,将动态面控制与后推设计相结合,有效地解决了后推设计中需要对虚拟控制反复求导所导致的设计复杂性问题,最终实现了耦合大系统的分散自适应控制。通过理论分析,证明了闭环系统所有信号是半全局一致终结有界的,通过适当选取设计参数,跟踪误差能够收敛到零的一个小邻域内,仿真结果表明了所提控制方案的有效性。     

一族具有未知扰动的非线性参数化系统的模糊控制

本文研究一类具有未知扰动非线性参数化系统的模糊自适应跟踪控制问题,且其中所有的参数都是未知的。本文的主要特点是将非线性参数化函数作为一个整体并入其它的未知连续函数中,采用模糊逻辑系统对其进行逼近,而没有使用现有文献采用的分离变量技术,之后再结合递推技术设计出模糊自适应跟踪控制器,使得闭环系统的所有信号都是有界的且跟踪误差在均方意义下收敛到原点的某个小的剩余集内。最后给出仿真例子验证控制方法的有效性。     

南极大型望远镜跟踪系统的鲁棒自适应控制研究

提出一种鲁棒自适应控制器的设计方案,尤其适用于南极大型望远镜这样含有未知有界扰动,未建模动态的非线性系统.文章基于Lyapunov函数法,通过引入动态信号抑制未建模参量的影响,并采用自适应阻尼抑制各种不确定性.理论证明,所提出的鲁棒自适应控制器可保证跟踪系统的稳定性,通过选择合适的参数能达到控制精度的要求.仿真结果表明,本鲁棒自适应控制器的控制效果有很大改善.     

Design,modelling and simulation of a new nonlinear and full adaptive backstepping speed tracking controller for uncertain PMSM

In this study, a new nonlinear and full adaptive backstepping speed tracking control scheme is developed for an uncertain permanent magnet synchronous motor (PMSM). Except for the number of pole pairs, all the other parameters in both PMSM and load dynamics are assumed unknown. Three phase currents and rotor speed are supposed to be measurable and available for feedback in the controller design. By designing virtual control inputs and choosing appropriate Lyapunov functions, the final control and parameter estimation laws are derived. The overall control system possesses global asymptotic stability; all the signals in the closed loop system remain bounded, according to stability analysis results based on Lyapunov stability theory. Further, the proposed controller does not require computation of regression matrices, with the result that take the nonlinearities in quite general. Simulation results clearly exhibit that the controller guarantees tracking of a time varying desired reference speed trajectory under all the uncertainties in both PMSM and load dynamics without singularity and overparameterization. The results also show that all the parameter estimates converge to their true values on account of the fact that reference speed signal chosen to be sufficiently rich ensures persistency of excitation condition. Consequently, the proposed controller ensures strong robustness against all the parameter uncertainties and unknown bounded load torque disturbance in the PMSM drive system. Numerical simulations demonstrate the performance and feasibility of the proposed controller.     

Quantized-states-based adaptive control against unknown slippage effects of uncertain mobile robots with input and state quantization

An adaptive tracking design strategy based on quantized state feedback is developed for uncertain nonholonomic mobile robots with unknown wheel slippage effects. All state variables and control torques are assumed to be quantized by the state and input quantizers, respectively, in a network control environment. Thus, the quantized state feedback information is only available for the tracking control design. An approximation-based adaptive controller using quantized states is recursively designed to ensure the robust adaptive tracking against unknown wheel slippage effects where the quantized-states-based adaptive mechanism is derived to compensate for unknown wheel slippage effects, system nonlinearities, and quantization errors. The boundedness of the quantization errors and estimated parameters in the closed-loop system is analyzed by presenting some theoretical lemmas. Based on these lemmas, we prove the uniform ultimate boundedness of closed-loop signals and the convergence of the trajectory tracking error in the presence of wheel slippage effects. Simulations verify the effectiveness of the resulting tracking scheme.     

不确定非线性系统的鲁棒自适应控制器

在ｂａｃｋｓｔｅｐｐｉｎｇ程序中，把非线性自适应控制和鲁棒控制连接起来，为参数化的严格反馈系统在不确定性存在的情况下，建立了一种鲁棒自适应控制方案．非线性自适应控制被用来处理系统的线性参数化部分，而鲁棒控制通过引进非线性阻尼项被用来处理不确定性部分．与现有的方案不同，作者给出了非线性阻尼项的无限种选择，而不是仅仅一种选择．通过使用一种合适的选择，能够设计一个鲁棒自适应控制器．它不仅能够保证对不确定性的鲁棒性，而且能够使输出误差任意小，以及用较小的控制努力取得较好的性能．     

基于模糊与神经网络技术的复杂非线性跟踪控制

针对一类具有不确定性、多重时延和状态未知的复杂非线性系统,把模糊T-S模型和RBF神经网络结合起来,提出了一种基于观测器的跟踪控制方案.首先,应用模糊T-S模型对非线性系统建模,设计观测器用来观测系统状态,并由线性矩阵不等式得到模糊模型的控制律;其次,构建了自适应RBF神经网络,应用自适应RBF神经网络作为补偿器来补偿建模误差和不确定非线性部分.证明了闭环系统满足期望的跟踪性能.示例仿真结果表明了该方案的有效性.     

非线性时滞系统的直接自适应模糊控制

针对一类具有摄动的严格反馈非线性时滞系统,基于后推设计方法,利用第一类模糊系统的逼近能力,提出了一种新的直接自适应控制方案。该方案避免了虚拟控制增益符号已知的假设。设计中引入连续鲁棒项对系统的摄动部分进行抑制。通过理论分析,证明了闭环系统是半全局一致终结有界的,跟踪误差收敛到一个小的残差集内。     

多输入多输出非线性最小相位系统的自适应模糊控制

针对多输入多输出非线性最小相位系统,把自适应模糊控制和自适应模糊辨识结合起来,提出了一种自适应模糊控制方案.设计辨识器用来辨识系统的未知部分;然后由跟踪误差和辨识误差给出了参数调节规律,两种误差同时调节参数改善了系统性能.模糊逻辑系统用来估计未知函数.控制方案保证了系统的稳定性,实现了有界跟踪.仿真结果表明了该方案的可行性.     

Tracking control and generalized projective synchronization of a class of hyperchaotic system with unknown parameter and disturbance

In this paper, the tracking control and generalized projective synchronization of a class of hyperchaotic system with unknown parameter and disturbance are investigated. Based on the LaSalle’s invariant set theorem, a robust adaptive controller is contrived to acquire tracking control and generalized projective synchronization and parameter identification simultaneously. It is proved theoretically that the proposed scheme can allow us to drive the hyperchaotic system to any desired reference signals, including hyperchaotic signals, chaotic signals, periodic orbits or fixed value by the given scaling factor. The presented simulation results further demonstrate that the proposed method is effective and robust.     

自适应模糊变结构控制的研究

本文主要研究一类具有未知常数控制增益的非线性系统的自适应模糊控制问题,提出了一种能够利用专家的语言信息和数字信息的自适应模糊变结构控制器的设计方案。通过理论分析,证明了模糊变结构控制系统是全局稳定的,跟踪误差可收敛到零的一个邻域内     

Robust intelligent sliding model control using recurrent cerebellar model articulation controller for uncertain nonlinear chaotic systems

In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This RISMC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control (SMC) due to unknown system dynamics, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The all adaptation laws of the RISMC system are derived based on the Lyapunov stability analysis and projection algorithm, so that the stability of the system can be guaranteed. Finally, the proposed RISMC system is applied to control a Van der Pol oscillator, a Genesio chaotic system and a Chua’s chaotic circuit. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. In addition, the advantages of the proposed RISMC are indicated in comparison with a SMC system.