Adaptive fuzzy nonlinear inversion-based control for uncertain chaotic systems

This paper presents a robust output feedback control method for uncertain chaotic systems, which comprises a nonlinear inversion-based controller with a fuzzy robust compensator. The proposed controller eliminates the unknown nonlinear function by using a fuzzy system, whose inputs are not the state variables but feedback error signals. The underlying stability analysis as well as parameter update law design are carried out by using the Lyapunov-based technique. The proposed method indicates that the nonlinear inversion-based control approach can also be applied to uncertain chaotic systems. Theoretical results are illustrated through two simulation examples.

Fault tolerant control of electric pitch control system based on single current detection

In view of the current sensors failure in electric pitch system,a variable universe fuzzy fault tolerant control method of electric pitch control system based on single current detection is proposed.When there is single or two-current sensor fault occurs,based on the proposed method the missing current information can be reconstructed by using direct current（DC）bus current sensor and the three-phase current can be updated in time within any two adjacent sampling periods,so as to ensure stability of the closed-loop system.And then the switchover and fault tolerant control of fault current sensor would be accomplished by fault diagnosis method based on adaptive threshold judgment.For the reconstructed signal error caused by the modulation method and the main control target of electric pitch system,a variable universe fuzzy control method is used in the speed loop,which can improve the anti-disturbance ability to load variation,and the robustness of fault tolerance system.The results show that the fault tolerant control method makes the variable pitch control system still has ideal control characteristics in case of sensor failure although part of the system performance is lost,thus the correctness of the proposed method is verified.

Parkinsonian oscillations and their suppression by closed-loop deep brain stimulation based on fuzzy concept

This paper provides an adaptive closed-loop strategy for suppressing the pathological oscillations of the basal ganglia based on a variable universe fuzzy algorithm.The pathological basal ganglia oscillations in the theta(4-9 Hz)and beta(12-35 Hz)frequency bands have been demonstrated to be associated with the tremor and rigidity/bradykinesia symptoms in Parkinson’s disease(PD).Although the clinical application of open-loop deep brain stimulation(DBS)is effective,the stimulation waveform with the fixed parameters cannot be self-adjusted as the disease progresses,and thus the stimulation effects go poor.To deal with this difficult problem,a variable universe fuzzy closed-loop strategy is proposed to modulate different PD states.We establish a cortico-basal ganglia-thalamocortical network model to simulate pathological oscillations and test the control effect.The results suggest that the proposed closed-loop control strategy can accommodate the variation of brain states and symptoms,which may become an alternative method to administrate the symptoms in PD.

Adaptive fuzzy controllers based on variable universe

Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation functions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contraction-expansion factor is discussed. At last, three models of adaptive fuzzy control based on variable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.

Design of longitudinal predictive re-entry guidance law based on variable universe fuzzy-PI composite control

This paper studies the longitudinal predictive re-entry guidance law based on the variable universe fuzzy- PI composite control to overcome the inaccuracy of the reference trajectory re-entry guidance for reentry vehicles. The variable universe fuzzy controller is used to obtain a satisfactory dynamic response when the downrange error is large, and the PI controller is utilized to eliminate the steady state error when the downrange error is small. Simulation results show that the proposed guidance law is very robust to the initial errors and can achieve better accuracy, and is also able to handle the effect of the stochastic errors in re-entry processes.

Variable universe fuzzy control of walking stability for flying‐walking power line inspection robot based on multi‐work conditions

To address complex work conditions incredibly challenging to the stability of power line inspection robots,we design a walking mechanism and propose a variable universe fuzzy control(VUFC)method based on multi‐work conditions for flying‐walking power line inspection robots(FPLIRs).The contributions of this paper are as follows:(1)A flexible pressing component is designed to improve the adaptability of the FPLIR to the ground line slope.(2)The influence of multi‐work conditions on the FPLIR's walking stability is quantified using three condition parameters(i.e.,slope,slipping degree and swing angle),and their measurement methods are proposed.(3)The VUFC method based on the condition parameters is proposed to improve the walking stability of the FPLIR.Finally,the effect of the VUFC method on walking stability of the FPLIR is teste.The experimental results show that the maximum climbing angle of the FPLIR reaches 29.1°.Compared with the constant pressing force of 30 N,the average value of slipping degree is 0.93°,increasing by 35%.The maximum and average values of robot's swing angle are reduced by 46%and 54%,respectively.By comparing with fuzzy control,the VUFC can provide a more reasonable pressing force while maintaining the walking stability of the FPLIR.The proposed walking mechanism and the VUFC method significantly improve the stability of the FPLIR,providing a reference for structural designs and stability controls of inspection robots.

Variable universe stable adaptive fuzzy control of nonlinear system

A kind of stable adaptive fuzzy control of nonlinear system is implemented using variable universe method. First of all, the basic structure of variable universe adaptive fuzzy controllers is briefly introduced. Then the contraction-expansion factor that is a key tool of variable universe method is defined by means of integral regulation idea, and a kind of adaptive fuzzy controllers is designed by using such a contraction-expansion factor. The simulation on first order nonlinear system is done. Secondly, it is proved that the variable universe adaptive fuzzy control is asymptotically stable by use of Lyapunov theory. The simulation on the second order nonlinear system shows that its simulation effect is also quite good. Finally a useful tool, called symbolic factor, is proposed, which may be of universal significance. It can greatly reduce the settling time and enhance the robustness of the system.

Variable universe adaptive fuzzy control on the quadruple inverted pendulum

This paper focuses on the control problem of the quadruple inverted pendulum by variable universe adaptive fuzzy control.First,the mathematical model on the quadruple inverted pendulum is described and its controllability is versified.Then,an efficient controller on the quadruple inverted pendulum is designed by using variable universe adaptive fuzzy control theory.Finally the simulation of the quadruple inverted pendulum is shown in detail.Besides,the experimental results on the hardware systems,i.e.real object systems,on a single inverted pendulum,a double inverted pendulum and a triple inverted pendulum are briefly introduced.

Variable Universe Fuzzy Control for Battery Equalization

In order to avoid the overcharge and overdischarge damages, and to improve the lifetime of the lithium-ion batteries, it is essential to keep the cell voltages in a battery pack at the same level,i.e., battery equalization. Based on the bi-directional modified Cuk converter, variable universe fuzzy controllers are proposed to adaptively maintain equalizing currents between cells of a serially connected battery pack in varying conditions. The inputs to the fuzzy controller are the voltage differences and the average voltages of adjacent cell pairs. A large voltage difference requires large equalizing current while adjacent cells both with low/high voltages can only stand small discharge/charge currents. Compared with the conventional fuzzy control method, the proposed method differs in that the universe can shrink or expand as the effects of the input changes. This is important as the input may change in a small range. Simulation results demonstrate that the proposed variable universe fuzzy control method has fast equalization speed and good adaptiveness for varying conditions.

Fuzzy控制的本质与一类高精度Fuzzy控制器的设计

本文揭示，Fuzzy控制器在本质上就是某种插值器．首先阐明Fuzzy控制的插值机理，然后讨论常用的双输入单输出分片插值器，最后介绍基于论域收缩的一类高精度Fuzzy控制器的设计思想．

可变论域自适应Fuzzy-PID控制器的设计与研究

针对常规模糊PID控制器由于论域固定带来的不足,提出了一种基于可变论域控制思想、具有自适应能力的Fuzzy-PID控制方法。通过变论域调整因子环节,根据系统响应各阶段的误差和误差变化,在线实时调整伸缩因子,从而改善量化因子、比例因子和模糊PID控制器的参数。该控制方法较好地解决了控制规则数量与控制精度间的矛盾,实现了论域随系统控制要求进行自适应伸缩。仿真研究表明,该控制方法具有自适应能力强,实时控制性能好的特点。应用结果表明,系统的鲁棒性、动态特性和稳态精度等明显优于常规模糊PID控制器。

Fuzzy-PID控制器的分析与改进

分析了常规Fuzzy PID控制器的缺陷 ,并在可变论域思想的基础上提出了一种新型的变论域Fuzzy PID控制器 ,该控制器响应速度快、无超调、几乎无震荡以及控制精度高 。

可变论域Fuzzy-PID控制器的设计与仿真

针对常规模糊控制器的缺陷 ,在可变论域思想的基础上提出了一种新型的Fuzzy -PID控制器 ,该控制器响应速度快、无超调、几乎无震荡以及控制精度高 ,具有较强的应用前景。

一种随机变论域Fuzzy控制器在医疗头盔中的实现

目前的自适应模糊控制方法在实际问题中难以达到良好的效果。针对这一问题,提出一种随机变论域Fuzzy控制器。首先,基于原有的伸缩因子设计一种简单、精准的随机伸缩因子,并通过仿真对比验证其性能;接着,以实际前后圈梁伸缩的长度与理想状态下前后圈梁伸缩的长度期望值的误差和误差的变化作为输入变量,引起旋钮转速变化的多少作为输出变量,设计随机变论域Fuzzy控制器;最后,使用仿真实验对比响应曲线图分析得到,设计的模糊控制器性能明显提升,并且整个控制过程中超调小、稳定性高、响应时间有明显的缩短,实现了医疗头盔的治疗效果。

基于遗传算法的汽车主动悬架变论域模糊PID控制

针对1/4车主动悬架系统,提出一种基于遗传算法(genetic algorithm,GA)的变论域模糊比例-积分-微分(proportional-integral-differential,PID)控制方法.在建立主动悬架系统模型的基础上,引入变论域思想设计模糊PID控制器.为进一步改善控制器减振效果,采用GA来优化变论域中伸缩因子描述函数的参数.结果表明:相比PID、模糊PID与未优化的变论域模糊PID等控制方法,基于GA的变论域模糊PID控制方法在降低车身垂向加速度、改善乘坐舒适性方面具有优越性;所提控制方法对簧载质量和车辆行驶速度不确定性具备较强的鲁棒性.

基于可变终端Tube-Based MPC的机场除雪车横向稳定性控制方法

为了提高机场路面自动驾驶除雪车作业过程中的侧倾稳定性,提出了一种基于可变终端tubebased MPC的机场除雪车横向稳定性控制方法。建立了除雪车作业的三自由度侧倾动力学解耦模型,采用tube-based MPC控制算法,基于除雪车横向稳定性、误差跟踪特性等约束条件设计了LQR函数,使MPC具有更好的鲁棒性,并在此基础上针对除雪车高速情况下可能出现的跟踪偏差发散设计了可变终端集。设计了多重模糊控制策略,确保除雪车在安全可行域内的灵活性和极端情况的安全性。仿真结果表明,采用tube-based MPC对比传统MPC在高速下除雪车综合跟踪性能提升80.22%,车身稳定性提升66.62%;加入多层模糊控制和可变终端约束的tube-based MPC对比可变终端约束的tube-based MPC在高速情况下除雪车综合跟踪性能提升71.77%,车身稳定性提升26.27%。

车辆主动悬架自适应变论域T-S模糊控制研究

针对传统变论域模糊控制存在过度依赖专家经验、伸缩因子参数不能自适应调整的问题,提出一种车辆主动悬架自适应变论域T-S模糊控制策略,从而提高车辆的行驶平顺性。结合神经网络和T-S模糊推理建立基于自适应神经模糊推理的一阶T-S模糊控制器,利用神经网络的自学习特性产生完善的模糊规则,进而在传统函数型伸缩因子的基础上,将系统误差和误差变化率作为动态参数引入伸缩因子中,实现伸缩因子参数的自适应调整,解决了传统函数型伸缩因子因参数确定难度大导致控制效果差的问题。通过随机工况下的仿真分析和基于相似理论的缩尺实验,对所提出算法的有效性和工况自适应性进行了验证。结果表明,所提出的自适应变论域T-S模糊控制策略具有较强的工况适应性,在不同车速、路面激励下均可有效提高车辆的平顺性并保证轮胎接地安全性。

基于变论域模糊PI控制的M3C外环控制策略

模块化多电平矩阵变换器可为远程交流电网提供频率控制支持,在高压低频交流输电系统中具有良好的应用前景,但传统外环比例积分(PI)控制器易受到自身参数和负荷变化的影响,控制效果稳定性不高。为此,这里提出了一种变论域模糊PI自适应外环控制策略。利用变论域模糊PI控制的自动感应和自适应能力,实现了外环输入误差大小的自适应和自调整。同时,利用基于函数的伸缩因子方法为输入/输出论域设计伸缩因子,以提高控制精度。仿真和实验结果表明,与传统PI控制相比,该控制不仅提高了系统稳定性,而且增强了自适应调节能力。