Controller design of uncertain nonlinear systems based on T-S fuzzy model

A robust control for uncertain nonlinear systems based on T-S fuzzy model is discussed in this paper. First, a T-S fuzzy system is adopted to model the uncertain nonlinear systems. Then, for the system with input variables adopting standard fuzzy partitions, the efficient maximal overlapped-rules group （EMORG） is presented, and a new sufficient condition to check the stability of T-S fuzzy system with uncertainty is derived, which is expressed in terms of Linear Matrix Inequalities. The derived stability condition, which only requires a local common positive definite matrix in each EMORG, can reduce the conservatism and difficulty in existing stability conditions. Finally, a simulation example shows the proposed approach is effective.

Optimal Design for Anti-Skid Control of Electric Vehicles by Fuzzy Approach

In this paper,a new fuzzy approach is applied to optimal design of the anti-skid control for electric vehicles.The anti-skid control is used to maintain the wheel speed when there are uncertainties.The control is able to provide an appropriate torque for wheels when the vehicle is about to skid.The friction coefficient and the moments of inertia of wheels and motor are considered as uncertain parameters.These nonlinear,bounded and time-varying uncertainties are described by fuzzy set theory.The control is deterministic and is not based on IF-THEN fuzzy rules.Then,the optimal design for this fuzzy system and control cost is proposed by fuzzy information.In this way,the uniform boundedness and uniform ultimate boundedness are guaranteed and the average fuzzy performance is minimized.Numerical simulations show that the control can prevent vehicle skidding with the minimum control cost under uncertainties.

Integrated Fuzzy Robust Controller for Flight Control Design

μ-synthesis is a practical design approach and has been applied successfully to achieve a nominal and robust performance objectives. However, this design method suffers from the complexity of its practical implementation and high computational demand due to its high order dynamics. To overcome this problem, the interaction between fuzzy logic control which is a part of intelligence control theory and p-synthesis controller is carried out. This is called integrated fuzzy robust controller in this paper. It is obtained by coupling fuzzy pd with p-synthesis controller through the outer loop. Using this design strategy, we can keep the system performance and robustness even a high order p-synthesis controller is reduced into second order model. In order to test the effectiveness of this design method, the linear simulation results for a launch vehicle＇s attitude control motion are presented at the end of this paper.

Quadcopter UAV Modeling and Automatic Flight Control Design

The mathematical model of quadcopter-unmanned aerial vehicle （UAV） is derived by using two approaches： One is the Newton-Euler approach which is formulated using classical meehanics; and other is the Euler-Lagrange approach which describes the model in terms of kinetic （translational and rotational） and potential energy. The proposed quadcopter＇s non-linear model is incorporated with aero-dynamical forces generated by air resistance, which helps aircraft to exhibits more realistic behavior while hovering. Based on the obtained model, the suitable control strategy is developed, under which two effective flight control systems are developed. Each control system is created by cascading the proportional-derivative （PD） and T-S fuzzy controllers that are equipped with six and twelve feedback signals individually respectively to ensure better tracking, stabilization, and response. Both pro- posed flight control designs are then implemented with the quadcopter model respectively and multitudinous simulations are conducted using MATLAB/Simulink to analyze the tracking performance of the quadcopter model at various reference inputs and trajectories.

Design Method for the Magnetic Bearing Control System with Fuzzy-PID Approach

The five degree freedom magnetic bearing is researched and its structure and working principles are introduced also. Based on the fuzzy control technology, combining fuzzy algorithm and PID control method, identifying the transition process mode of the online system to get the PID parameters＇ self-adjusting, the magnetic beating system＇s Fuzzy-PID nonlinear controller is designed by analyzing the system control demands. The Fuzzy-PID nonlinear controller can deal with the magnetic bearing system＇ s open loop instability and strong nonlinearity, and the approach could improve the system＇s rapidity, adaptability, stability and dynamic characteristics. Comparative analysis and experiments are conducted between linear PID and nonlinear fuzzy- PID control methods, the results show that the fuzzy-PID controller is better, and the five-freedom magnetic bearing＇ s rotary precision experiments are conducted by the fuzzy-PID controller, it satisfies the control rotary precision demands and realizes the hearing＇s steady floating and rotating.

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.

Direct Adaptive Fuzzy Based Backstepping Control of Semi Strict Feedback Nonlinear Systems

In this paper, a direct adaptive fuzzy tracking control is proposed for a class of uncertain single-input single-output nonlinear semi-strict feedback systems. Based on Takagi-Sugeno type fuzzy systems, a direct adaptive fuzzy tracking controller is developed by using the backstepping approach. The main advantage of the developed method is that for an n-th order system, only one parameter is needed to be adjusted online. It is proven that, under the appropriate assumptions, the developed scheme can achieve that the output system converges to a small neighborhood of the reference signal and all the signals in the closed-loop system remain bounded. The efficacy of the proposed algorithm is investigated by an illustrative simulation example of one link robot.

Adaptive Fuzzy Backstepping Tracking Control for Flexible Robotic Manipulator

In this paper,an adaptive fuzzy state feedback control method is proposed for the single-link robotic manipulator system.The considered system contains unknown nonlinearfunction and actuator saturation.Fuzzy logic systems(FLSs)and a smooth function are used to approximate the unknownnonlinearities and the actuator saturation,respectively.By com-bining the command-filter technique with the backsteppingdesign algorithm,a novel adaptive fuuzy tracking backsteppingcontrol method is developed.It is proved that the adaptive fuuzycontrol scheme can guarantee that all the variables in the closed-loop system are bounded,and the system output can track thegiven reference signal as close as possible.Simulation results areprovided to illustrate the effectiveness of the proposed approach.

A novel robust design method for the sense mode of a MEMS vibratory gyroscope based on fuzzy reliability and Taguchi design

This paper proposes a novel robust design method for the sense mode of a MEMS vibratory gyroscope based on fuzzy reliability and Taguchi design. The principles of fuzzy reliability and Taguchi design are both introduced and described in detail. Experimental results demonstrate that the signal to noise ratio of the robust design scheme is better than those of the other experimental schemes.Over the full temperature range from -40 to 80°C, the temperature sensitivities of phase margin, gain margin, sensitivity margin,the maximum amplitude of open loop system, bandwidth of closed loop system, and the performance function of the robust design system are all smaller than those of the original design system. Meanwhile, the temperature sensitivity of the bandwidth of the robust design system is improved to 126 from 1075 ppm/°C. Moreover, the bias drift over the full temperature range of the robust design system is improved to 61°/h from 179°/h.

Fuzzy电压调节器的一种自动设计方法

将Ｆｕｚｚｙ控制表用一个带修正因子的数学式表达，利用优化方法提出了一种Ｆｕｚｚｙ电压调节器的自动设计方法。对一个单机－无穷大系统的数字仿真结果证明了新提出方法的实用性和有效性。

FUZZY控制器的开关设计及应用研究

本文在模糊控制理论的基础上 ,针对航空发动机的主状态控制系统 ,提出了一种快速设计模糊控制器的开关设计法 。

一种实用的自校正Fuzzy控制器

本文针对自组织 Fuzzy 控制器在控制规则校正中关系矩阵运算的困难,提出了一种用校正控制的输出量与基本 Fuzzy 控制规则的输出量直接相加作为调整后的控制器输出的方法,Fuzzy 控制规则的运算和调整因此而得到简化.该方法不仅设计原理简明,而且在微机上实施容易.通过仿真和在实验装置上的闭环运行表明:该 Fuzzy 控制器的主要性能优于一般 Fuzzy 控制器,具有工程实用可能.

双交叉参数自调整FUZZY-PI控制器在燃油锅炉调控中的应用

介绍了一种用于锅炉热负荷系统的复合控制器。对传统的P1控制与FUZZY控制作了仿真比较,为保证锅炉安全运行采用了双交叉控制。

倾斜控制系统的FUZZY控制

该控制方案舍去传统的校正环节，不用传统的PID 控制，而用FUZZY 控制设计反坦克导弹倾斜控制系统，给出了FUZZY 控制表求取规则和控制表。实验结果表明FUZZY 控制效果较传统的PID 控制效果好。

基于玻璃化转变的稻谷干燥变温控制系统设计与试验

针对稻谷在变温干燥过程中变温节点不明确、温度波动范围大和响应时间慢等问题,该研究设计了一种基于玻璃化转变的稻谷变温干燥控制系统。根据稻谷玻璃化转变曲线,确定变温控制策略,运用Logistic回归分析建立混配阀门开度和稻谷温度之间的控制模型并通过最小二乘法辨识模型参数。利用遗传算法对模糊隶属度函数进行优化,目标函数值迭代至0.118收敛,寻得最优幅宽。在Simulink仿真试验中,稻谷温度设定为42℃时,模糊PID控制的响应时间为66.43 s,且超调量为3.600%,优化后的模糊PID控制响应时间为37.06 s,且超调量为0.120%;在150 s加入5 s的外部信号干扰,优化后的模糊PID控制比模糊PID控制的调节时间少4.19 s且超调量减小0.050%;在稳态时输入升温信号,优化后的模糊PID控制比模糊PID控制的调节时间少16.79 s且超调量低0.338%。利用自主研制的干燥试验台进行变温试验,在变温响应试验中,优化后的模糊PID控制比模糊PID控制在目标温度和梯度升温调节时间中分别缩短了37.56 s和18.63 s;在温度稳定性试验中,稻谷温度变化范围为41.9~42.1℃,平均相对误差小于0.4%,变异系数小于0.5%;在建三江国家农业高新技术示范区浓江农场进行生产性验证,优化后的模糊PID控制系统响应时间小于30 s,稳态温度误差在±0.15℃,平均相对误差小于0.5%。测试数据表明变温干燥控制系统性能稳定,满足实际干燥作业的生产工艺需求。

扑翼飞行器定高飞行控制器的模型构建与仿真

针对传统飞行控制算法适应性差以及扑翼飞行器气动特性复杂,导致飞行控制算法需具备较强自适应性的问题,提出了一种基于模糊自适应PID算法的新型仿生扑翼机定高飞行控制器。通过复数矢量法设计了一款结构简单的新型扑翼结构,并通过运动学仿真与计算流体力学仿真建立了扑翼飞行器的定高飞行运动学模型。仿真测试了所设计的模糊自适应PID控制器对于该运动学模型的控制效果,并与基于传统算法的控制器进行了对比。实验结果表明,所设计的模糊自适应PID定高飞行控制器比传统控制器具有更好的响应特性和适应性。

基于模糊自适应PID控制器的夹具自适应控制研究

为提高夹具自适应控制的稳定性和响应速度,以电磁无心夹具为研究对象,提出一种基于模糊自适应比例-积分-微分(proportion integration differentiation, PID)控制器的控制方法。首先构建夹具数学模型,然后结合模糊控制和PID控制的优势,构建模糊自适应PID控制器对夹具进行自适应控制,最后通过在MATLAB软件上进行仿真。结果表明,该方法实现了阶跃信号、突加负载、正弦信号输入等不同条件下的夹具控制,且具有优异的控制性能。整个控制过程中,该方法超调量为2.11%,响应时间0.08 s。相较于PID控制器、模糊控制器、自抗扰控制器、模糊滑模控制器,该方法提高了夹具自适应控制的精度和响应速度,且可用于实际夹具自适应控制中,具有一定的实际应用价值。

应用于标准电容装置的高精度温控系统设计

在引力波探测的相关技术任务中,需要研究设计标准电容装置用于电容位移传感电路的标定测试。为了保证标准电容装置的高精度和高稳定性,设计了配套的大体积高精度温控系统。该系统由保温腔体、温控主机、上位机3个部分组成。温控主机是整套控制系统的核心,包含主控电路板、高精度线性电源、有机发光二极管(OLED)显示屏、通信接口、用户界面(UI)等,系统使用模糊PID控制算法进行温度控制。实验结果表明,温控系统的短期温度控制稳定性(24 h)能够达到±0.002℃。使用该系统给标准电容装置提供环境保障,能够实现10 h下2 aF(10-21 F)的短期稳定性。

基于模糊比例积分控制的商用车驻车空调控制器设计

驻车空调控制系统是一个非线性、强耦合复杂控制系统,传统驻车空调控制系统存在调节时间长、控制精度低、能耗高等问题,难以满足不同环境下的控制需求。基于模糊比例积分控制,设计了商用车驻车空调控制器。通过AMEsim软件建模分析,针对驻车空调的主要可控部件蒸发风机、冷凝风机、压缩机设计了各自独立的模糊比例积分控制器。采用AMEsim软件和MATLAB软件Simulink模块联合仿真,搭建驻车空调控制系统模型,并对传统比例积分控制和模糊比例积分控制进行对比。仿真结果表明,模糊比例积分控制相较于传统比例积分控制,在温度控制方面具有更高的控制精度和动态性能,调节时间明显缩短,无超调,同时还具有更高的能效比。

基于单片机的热处理炉温度PID控制系统设计与仿真

在冶炼等工业的生产过程中,热处理是决定锻件质量的重要步骤。工件淬火时温度过高会导致工件损坏,淬火时温度过低不足以消除工件成分中的应力,容易造成工件硬度不够。热处理炉是重要的工业冶炼设备,具有温度范围大、炉温控制严格等特点,热处理炉的温度控制一直是工业锻造、冶炼的重点的难点,炉温的调整会直接影响部件的质量。从热处理炉的运行入手分析,综合探讨了单片机的功能以及工作原理,提出了一种基于单片机的热处理炉温度PID控制系统设计方法,从软硬件开发角度详细介绍了温度控制系统的模块设置以及控制算法选择,使热处理炉炉温控制更加智能化,能够最大限度的提升工业热处理炉的温度控制精准度,为工业热处理的智能化和自动化发展提供参考性建议。