Event-triggered adaptive fuzzy control for nonstrict-feedback nonlinear systems with output hysteresis

This paper concentrates upon the issue of adaptive fuzzy tracing control for a class of nonstrict-feedback nonlinear systems output with hysteresis via an event-triggered strategy. To handle the difficulty caused by the nonstrict nonlinear systems, the variable separation technique is introduced. The design difficulty of output hysteresis is addressed by employing a hysteresis inverse function and Nussbaum function to compensate unmeasurable state signal. Meanwhile, the fuzzy logic system (FLS) is used to estimate the unknown function at each step of recursion. Moreover, by devising the relative threshold event-triggered mechanism (ETM), the frequency of actuators and controllers can be largely decreased. Thus, the adaptive fuzzy event-triggered tracing control strategy is proposed by combining the barrier Lyapunov function and backstepping technique. With the proposed scheme, it is theoretically demonstrated that all signals in the closed-loop system are bounded, and the tracing errors are driven to a small neighborhood of the origin under the output constraint. Eventually, two examples demonstrate the efficacy of the proposed control strategy.     

模糊Smith智能温度控制器的设计与仿真

结合模糊PID控制与模糊自适应Smith预估控制的优点,提出了模糊Smith智能控制方法。用模糊控制方法设计了改进型Smith预估器的滤波时间常数,并制定了其整定规则和参数的模糊自适应调整机构。仿真研究表明,模糊Smith智能控制能改善参数时变的纯滞后系统的控制性能,提高系统控制时的鲁棒性与自适应性。     

Design of a fuzzy adaptive controller for MIMO nonlinear time-delay systems with unknown actuator nonlinearities and unknown control direction

This paper aims at investigating the fuzzy adaptive control design for uncertain multivariable systems with unknown actuator nonlinearities and unknown control direction that possibly exhibit time-delay. The actuator nonlinearities involve dead-zone or backlash-like hysteresis, while the control direction is closely related to the sign of the control gain matrix. Two fuzzy adaptive controllers are proposed to deal with such an issue. The design of the first controller is mainly carried out in the free time-delay case, while the second control design is performed assuming that the system exhibits time-varying delays. Of practical interest, the adaptive compensation of the effects of the actuator nonlinearities requires neither the knowledge of their parameters nor the construction of their inverse. Furthermore, the lack of knowledge of the control direction is handled by incorporating in the control law a Nussbaum-type function. The effectiveness of the proposed fuzzy adaptive controllers is illustrated through simulation results.     

基于模糊Smith方法的温控系统仿真研究

在过程控制中,经常会碰到纯滞后、时变、非线性的复杂系统,传统的模糊控制和PID控制方法解决上述问题效果不佳。为了解决控制系统中超调量大和调节时间长等问题,针对热疗温度控制对象的纯滞后特性,在Smith预估器和传统PID控制的基础上,结合模糊PID控制与模糊自适应Smith预估控制,提出模糊Smith智能控制方法。方法通过对模型的纯滞后进行补偿,来减小纯滞后系统的超调和增强系统的稳定性。通过建立热疗数学模型并进行仿真研究,结果表明无论在参数不变还是参数改变的情况下,方法在超调量和凋节时间等方面都有很大提高,极大地改善了控制性能,提高了温度控制系统的鲁棒性和抗干扰性。     

对迟滞三明治系统基于Duhem算子的自适应控制

对具有迟滞非线性的三明治系统,设计了基于Duhem算子的神经网络自适应控制器.首先对前端动态子系统进行近似补偿;然后用Duhem算子描述所提出的迟滞状态,用神经网络逼近迟滞状态与迟滞输出的关系,实现对迟滞非线性的建模.基于该迟滞模型并采用伪控制技术设计神经网络自适应控制器,通过Lyapunov方法证明了系统的稳定性,并推导出神经网络的权值自适应调整律和控制律.最后通过仿真验证了该方案的有效性.     

电弧炉的反步自适应模糊控制

电弧炉是具有三相强耦合、高度非线性和不确定性的复杂被控对象,并且目前对电弧炉的控制要求越来越严格,为此将反步控制与自适应模糊控制相结合,应用于电弧炉电极调节系统中.给出了反步自适应模糊控制系统的详细设计过程.用递推法设计反步控制量,用自适应模糊控制逼近反步控制量中的不确定项,设计出自适应模糊控制律.通过李亚普诺夫函数推导了模糊规则参数调整的自适应律.最后引入监督控制以减少模糊逼近误差.仿真结果表明:所提出的控制算法能有效地抑制弧长的扰动,具有较强的鲁棒性,从而使电弧炉电极调节系统拥有较好的动静态性能.     

连续回滞系统的模型参考自适应控制

采用Stop和Play算子表示的Prandtl-Ishlinskii回滞模型描述回滞特性,该模型便于实现控制器的设计．考虑带有未知回滞驱动且以状态空间形式表示的连续时间线性动态系统,给出了模型参考白适应控制设计方案．控制策略保证闭环系统的全局稳定性和期望的跟踪精度,有效地抑制回滞产生的不精确和振荡现象．数值仿真结果表明了控制算法的有效性．     

Adaptive Pseudo Inverse Control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic Systems

This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control(DSC)scheme.The"pseudo inverse"means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is included.The main contributions are summarized as:1)to our best knowledge,it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult;2)by designing the saturated-type hysteresis pseudo inverse compensator,the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis;3)by combining DSC technique with the tracking error transformed function,the"explosion of complexity"problem in backstepping method is overcome and the prespecified tracking performance is achieved.Analysis of stability and experimental results on the hardware-inloop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.     

肿瘤热疗中温控系统的建模与仿真

热疗是近几年出现的一种治疗肿瘤的新方法,针对热疗温度控制对象的纯滞后特性,在具有一阶惯性环节的Smith预估器的基础上,结合模糊PID控制与模糊自适应Smith预估控制,提出了一种模糊Smith智能控制方法。在生物热传递方程的基础上,建立了典型的热疗数学模型。通过对此模型的仿真研究表明：模糊Smith智能控制方法改善了控制性能,使温度控制系统的鲁棒性和抗干扰性得到了显著提高。     

自适应模糊多环控制在惯导平台稳定回路中的应用

稳定回路控制是决定平台导航系统精度的关键因素之一.传统的校正控制动态性能和抗干扰性能较差,而模糊控制具有稳态误差,因此单一的控制往往很难实现更高精度的导航.为了得到较好的导航精度,以某惯导平台为研究对象,在传统单闭环回路的基础上,引入电流环和速率环,并加入模糊控制,形成复合三环控制,同时针对复合控制切换抖动的问题,设计了基于模糊控制的自适应调节机构.仿真结果表明,采用自适应模糊多环控制,不仅消除了系统控制切换产生的抖动以及模糊控制带来的稳态误差,而且有效改善了控制系统的动态性能.     

基于迟滞算子的非平滑三明治系统自适应控制

针对一类具有非平滑的迟滞三明治系统, 提出一种基于神经网络的自适应控制方法. 首先利用神经网络做出了前端动态模块的逆系统实现前端动态模块的近似补偿, 这样将迟滞三明治系统转化成一般的迟滞非线性系统. 然后提出一个迟滞算子将迟滞的多映射转化成一一映射, 基于这个迟滞算子设计了神经网络自适应控制器, 通过Lyapunov方法证明了系统的稳定性并推导出神经网络的权值自适应调整律和控制律. 最后通过仿真验证了该方案的有效性.     

Adaptive fuzzy dynamic surface control for uncertain nonlinear systems in pure-feedback form with input and state constraints using noisy measurements

This paper is concerned with the design of an adaptive fuzzy dynamic surface control for uncertain nonlinear pure-feedback systems with input and state constraints using a set of noisy measurements. The design approach is described as follows. The nonlinear uncertainties are approximated by using the fuzzy logic systems at the first stage, secondly the adaptive fuzzy dynamic surface control is introduced to remove the problem of the explosion of complexity for the derivation of the adaptive fuzzy backstepping control, thirdly a new saturation function for state constraints is proposed to design the controllers based on the Lyapunov function, fourthly the number of the adjustable parameters is reduced by using the simplified extended single input rule modules, and finally the weighted least squares estimator to take the estimates for the un-measurable states and the adjustable parameters is in a simplified structure designed. The proposed approach provides effective system performance in the simulation experiment.     

动态不确定非线性系统直接自适应模糊backstepping控制

对一类单输入单输出动态不确定非线性系统,提出一种直接自适应模糊backstepping和小增益相结合的控制方法.设计中,首先用模糊逻辑系统逼近虚拟控制器:其次把自适应模糊控制和backstepping控制设计技术相结合.给出了直接自适应模糊控制设计方法.最后基于Lyapunov函数和小增益方法证明了整个闭环系统的稳定性.仿真实例进一步验证了所提方法的有效性.     

迟滞非线性动态系统神经网络自适应控制

为了减轻非线性动态系统中未知迟滞(Hysteresis)的不良影响，该文提出了一类Backlash型迟滞模型。将有限数量不同宽度的Backlash(Matlab／Simulink)算子进行叠加，来仿真执行器中的迟滞非线性动态。用此模型，提出了基于径向基函数神经网络的自适应控制方案，以控制伴有未知迟滞的非线性动态系统。该方案采用了动态逆的思想及伪控制的概念。利用Lyapunov稳定理论，设计了两个鲁棒控制项，保证动态系统的稳定性、系统中所有信号有界和误差收敛到起点的领域内。通过Matlab／Simulink仿真实验，证明了所提出方案的有效性。     

Fuzzy dynamic characteristic modeling and adaptive control of nonlinear systems and its application to hypersonic vehicles

In this paper, a fuzzy dynamic characteristic modeling and adaptive control method is proposed for a class of nonlinear systems. By employing fuzzy dynamic characteristic model, the controlled plant is described as a slowly time-varying fuzzy system, wherein the parameters are estimated online by using recursive Least-Squares algorithm. Under this framework, a fuzzy adaptive controller is constructed, and the stability condition of the closed-loop system is also derived. The main advantage of the proposed m...     

模糊自适应Smith预估器在温室控制中的应用研究

该文以蒸汽管道为对象,采用机理分析法对温室加温时的温度对象进行分析,得到室内温度模型和蒸汽管道模型。采用模糊控制技术,组成温室温度的模糊控制系统。针对温室系统大延时滞后的特点,采用自适应Sm ith预估器对温室模糊控制系统进行补偿,组成模糊自适应Sm ith预估控制系统。运用MATLAB软件的S imu link建立温室控制系统的仿真模型,并分别用常规模糊控制技术和模糊自适应Sm ith预估控制技术对温室加温进行仿真试验,仿真结果表明在温室加温的模糊控制系统中增加自适应Sm ith预估器后,系统具有更强的适应能力,系统的动态特性都有了较大的改善。     

Observer-based adaptive control of robot manipulators: Fuzzy systems approach

This paper presents a fuzzy adaptive control suitable for motion control of multi-link robot manipulators with structured and unstructured uncertainties. When joint velocities are available, full state fuzzy adaptive feedback control is designed to ensure the stability of the closed loop dynamic. If the joint velocities are not measurable, an observer is introduced and an adaptive output feedback control is designed based on the estimated velocities. In the proposed control scheme, we need not derive the linear formulation of robot dynamic equation and tune the parameters. To reduce the number of fuzzy rules of the fuzzy controller, we consider the properties of robot dynamics and the decomposition of the uncertainties terms. The proposed controller is robust against uncertainties and external disturbance. Further, it is shown that required stability conditions, in both cases, can be formulated as LMI problems and solved using dedicated software. The validity of the control scheme is demonstrated by computer simulations on a two-link robot manipulator.     

Adaptive fuzzy dynamic surface control for uncertain nonlinear systems

In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of ＂explosion of complexity＂ in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller （SMC）. Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.     

An approach to adaptive control of fuzzy dynamic systems

This paper discusses adaptive control for a class of fuzzy dynamic models. The adaptive control law is first designed in each local region and then constructed in the global domain. It is shown that the resulting fuzzy adaptive control system is globally stable. Robustness issues of the adaptive control system are also addressed. A simulation example is given for demonstration of the application of the approach     

基于AFSMC算法的四旋翼飞行器控制策略研究

针对四旋翼飞行器在飞行过程中,控制系统存在非线性、强耦合、不确定性和鲁棒性差的问题,建立了关于四旋翼飞行器的动力学数学模型,将自适应控制、模糊控制和滑模控制相结合,提出基于自适应模糊滑模控制(AFSMC)的快速平稳控制策略。采用模糊系统推理方法实现理想控制律的逼近。在满足李雅普诺夫稳定性条件的前提下进行控制器的设计和稳定性分析,并结合四旋翼的数学模型和给定参数进行了MATLAB仿真。仿真结果表明,AFSMC控制器相比常规PID控制器具有良好的动态性能和抗干扰能力。