Combined indirect and direct method for adaptive fuzzy output feedback control of nonlinear system

A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.

The Application of Synthetic Fuzzy Assessing Method in Measurement and Control System of Plating Solution Evaporator

The synthetic fuzzy assessing method is usually applied to sensory evaluation. The method has simple and reliable virtue, and it is consistent with objective evaluation results. Using this method, system status of plating solution evaporator is evaluated, and the result is applied to compensate a fuzzy controller. Experimental results have shown the correctness and the validity of the proposed approach.

FUZZY ADAPTIVE CONTROL OF FLEXIBLE-LINK ROBOT MANIPULATOR

A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.

ADAPTIVE FUZZY CONTROL FOR ROBOT ARM MANIPULATOR WITH 5-DOF

To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.

Design and Analysis of a Novel Tension Control Method for Winding Machine

Filament winding has emerged as the main process for carbon fiber reinforced plastic(CFRP) fabrication, and tension control plays a key role in enhancing the quality of the winding products. With the continuous improvement of prod?uct quality and e ciency, the precision of the tension control system is constantly improving. In this paper, a novel tension control method is proposed, which can regulate the fiber tension and transport speed of the winding process by governing the outputs of three di erent driven rollers(the torque of the unwind roll, the torque of the magnetic powder brake roller, and the speed of the master speed roller) in three levels. The mechanical structures and dynamic models of the driven rollers and idle rollers are established by considering the time?varying features of the roller radius and inertia. Moreover, the influence of parameters and speed variation on fiber tension is investigated using the increment model. Subsequently, the control method is proposed by applying fiber tension in three levels accord?ing to the features of the three driven rollers. An adaptive fuzzy controller is designed for tuning the PID parameters online to control the speed of the master speed roller. Simulation is conducted for verifying the performance and sta?bility of the proposed tension control method by comparing with those of the conventional PID control method. The result reveals that the proposed method outperforms the conventional method. Finally, an experimental platform is constructed, and the proposed system is applied to a winding machine. The performance and stability of the tension control system are demonstrated via a series of experiments using carbon fiber under di erent reference speeds and tensions. This paper proposes a novel tension control method to regulate the fiber tension and transport speed.

Fuzzy Torque Control of the Bionic Flexible Manipulator Actuated by Pneumatic Muscle Actuators

A bionic flexible manipulator driven by pneumatic muscle actuator(PMA)can better reflect the flexibility of the mechanism.Current research on PMA mainly focuses on the modeling and control strategy of the pneumatic manipulator system.Compared with traditional electro-hydraulic actuators,the structure of PMA is simple but possesses strong nonlinearity and flexibility,which leads to the difficulty in improving the control accuracy.In this paper,the configuration design of a bionic flexible manipulator is performed by human physiological map,the kinematic model of the mechanism is established,and the dynamics is analyzed by Lagrange method.A fuzzy torque control algorithm is designed based on the computed torque method,where the fuzzy control theory is applied.The hardware experimental system is established.Through the co-simulation contrast test on MATLAB and ADAMS,it is found that the fuzzy torque control algorithm has better tracking performance and higher tracking accuracy than the computed torque method,and is applied to the entity control test.The experimental results show that the fuzzy torque algorithm can better control the trajectory tracking movement of the bionic flexible manipulator.This research proposes a fuzzy torque control algorithm which can compensate the error more effectively,and possesses the preferred trajectory tracking performance.

Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

In heating, ventilating and air-conditioning （HVAC） systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno （T-S） fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.

Hardware Type 2 Fuzzy Logic Position Controller Based on Karnik-Mendel Algorithms

This paper presents an analysis of the KM （Karnik-Mendel） algorithms performance under real time implementation using 3 types： the non-iterative, the iterative and the enhanced, and their feasibility for real-time interval type 2 fuzzy logic control system applications. The results are also compared against NT （Nie-Tan） method that is one of the fastest and simplest defuzzification methods. Because the DC （direct current） servo-motor is one of the most used motors in different industrial applications and the model of the motor is nonlinear, this motor was selected for validating the implementation in real time hardware. This DC motor is a perfect option for studying the real time performance of KM algorithms in order to show up its limits and possibilities for real-time control system applications. These methodologies are implemented in National Instruments LabVIEW FPGA （field programmable gate array） module hardware which is one of the most used platforms in the industry. The results show that the E-KM （enhanced KM） algorithm and the NT method present good results for implementing real-time control applications in real time hardware. Although fuzzy logic type 2 is a good option for working with nonlinear and noise from the sensors, the defuzzification method has to react in a short period of time in order to allow good control response. Hence, a complete study of defuzzification is needed for improving the real time implementations of fuzzy type 2.

Stability analysis of the simplest Takagi-Sugeno fuzzy control system using circle criterion

A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.

Simulation research on the energy dissipation and shock absorption performance of a swing column device based on fuzzy control

Double-column bridge piers are prone to local damage during earthquakes,leading to the destruction of bridges.To improve the earthquake resistance of double-column bridge piers,a novel swing column device(SCD),consisting of a magnetorheological(MR)damper,a current controller,and a swing column,was designed for the present work.To verify the seismic energy dissipation ability of the SCD,a lumped mass model for a double-column bridge pier with the SCD was established according to the low-order modeling method proposed by Steo.Furthermore,the motion equation of the double-column bridge pier with the SCD was established based on the D′Alembert principle and solved with the use of computational programming.It was found that the displacement response of the double-column bridge pier was effectively controlled by the SCD.However,due to rough current selection and a time delay,there is a significant overshoot of the bridge acceleration using SCD.Hence,to solve the overshoot phenomenon,a current controller was designed based on fuzzy logic theory.It was found that the SCD design based on fuzzy control provided an ideal shock absorption effect,while reducing the displacement and acceleration of the bridge pier by 36.43%‒40.63%and 30.06%‒33.6%,respectively.

On Fuzzy Control of Soybean Aphid

This paper uses a methodology based in Fuzzy Sets Theory in order to describe the interaction between the prey, Aphis glycines (Hemiptera: Aphididae)—the soybean aphid, and its predator, Orius insidiosus (Hemiptera: Anthocoridae) and to propose a biological control to soybean aphid. Economic thresholds were already developed for this pest. The model includes biotic (predator) and abiotic (temperature) factors, which affect the soybean aphid population dynamics. The dynamic model results in a fuzzy model that preserves the biological meaning and nature of the predator-prey model. The paper also includes a comparison between the fuzzy model and real data reported in the literature. Subsequently, we propose a biological control to soybean aphid by another fuzzy rule-based system. This model has allowed to predict timing and releasing number of predators for soybean aphid biological control. On the one hand, the soybean aphid has still not found in Brazil. Therefore, before any eventual invasion, a predictive model to enhance biological control program is desirable. On the other hand, the soybean aphid has become the most devastating insect pest of soybeans in the United States. Brazil is the second largest exporter of soybean at present, after the USA and before Argentina. According to the Bureau of Agriculture of the USA, it has been estimated that Brazil will be the largest soybean exporter in 2023.

Solution and Analysis of the Fuzzy Volterra Integral Equations viaHomotopy Analysis Method

Homotopy Analysis Method(HAM)is semi-analytic method to solve the linear and nonlinear mathematical models which can be used to obtain the approximate solution.The HAM includes an auxiliary parameter,which is an efficient way to examine and analyze the accuracy of linear and nonlinear problems.The main aim of this work is to explore the approximate solutions of fuzzy Volterra integral equations(both linear and nonlinear)with a separable kernel via HAM.This method provides a reliable way to ensure the convergence of the approximation series.A new general form of HAM is presented and analyzed in the fuzzy domain.A qualitative convergence analysis based on the graphical method of a fuzzy HAM is discussed.The solutions sought by the proposed method show that the HAM is easy to implement and computationally quite attractive.Some solutions of fuzzy second kind Volterra integral equations are solved as numerical examples to show the potential of the method.The results also show that HAM provides an easy way to control and modify the convergence area in order to obtain accurate solutions.

Fuzzy Synthetic Evaluation Model for Smart Washing Machine

Generally fuzzy control system (FCS) is worked in washing machine. For the fuzzy set theory, membership functions are the building blocks. In a fuzzy set, fuzziness is determined by its membership functions. The shapes of membership functions are important, because it has an effect on fuzzy inference system. The shapes of membership functions can be triangular, trapezoidal and gaussian. The most widely used triangular membership function is used in this paper, because it can capture the short time period. In washing machine, open loop control system is found. This paper applies a fuzzy synthetic evaluation method (FSEM) for washing cloth in washing machine as FSEM can handle the multiple criteria with the help of evaluation matrix generated from membership function and weight matrix generated by Analytical Hierarchy Process (AHP). The purpose of this research is to minimize the wash time. By applying FSEM, we get a wash time which is less than that wash time got from applying the Mamdani approach in FCS. An example is given for illustration. For more reduction of wash time, statistical averaging method is also used. To reduce the wash time, statistical averaging method can be used in Mamdani approach also.

基于PSO-Fuzzy PID的重载无人叉车液压马达同步控制策略

为保证重载无人叉车正常运行,减小对液压马达的同步控制偏差,提出一种基于粒子群优化的模糊PID方法(PSO-Fuzzy PID)的重载无人叉车液压马达同步控制策略。首先建立叉车液压马达的数学模型,其次基于叉车运行参数获得改进特征函数,利用特征值表示叉车运行状态,并作为PID方法、模糊PID方法和粒子群优化的模糊PID方法的输入。最后,相同条件下,通过比较三种不同方法下转速变化以及角度变化,验证了PSO-Fuzzy PID方法抗干扰能力好、调节能力佳。

融合反步法的无人驾驶汽车轨迹跟踪控制方法

为了解决无人驾驶汽车轨迹跟踪控制的准确性、稳定性和快速性问题,将反步法分别融合滑模变结构控制和模糊自适应控制.建立车辆三自由度运动学位姿误差微分方程,推导了基于反步法的车速和横摆角速度控制律,结合Lyapunov稳定性判据验证了系统稳定性.分别建立融合反步法的滑模变结构和模糊自适应轨迹跟踪控制方法,结合轨迹跟踪稳态误差、超调量和调整时间,验证、比较了控制方法准确性、稳定性和快速性3种性能的优劣.结果表明:融合反步法的滑模变结构轨迹跟踪控制的稳定性最好,轨迹跟踪超调量接近于0;融合反步法的模糊自适应轨迹跟踪控制快速性最好,轨迹跟踪调整时间相对于反步法缩短了18.2%.

基于组合赋权云模型的塔台管制系统运行安全评估

随着我国民航业的迅猛发展,空中交通流量不断攀升,机场塔台管制系统的运行安全面临严峻考验,因此,正确识别和评估风险成为有效提高塔台管制系统运行安全水平的重要前提。为精准且有效地完成对塔台管制系统运行的安全评估,构建了基于模糊决策实验室分析法(Decision-Making Trial and Evaluation Laboratory,DEMATEL)网络层次分析法(Analytic Network Process,ANP)熵权法云模型的塔台管制系统运行安全评估模型。首先,通过流程图法并结合人机环管的思想建立塔台管制系统运行安全评估指标体系,并采用模糊DEMATEL法确定评估指标间的相互影响关系,绘制评估指标之间的网络结构图;然后,通过ANP法确定各评估指标的主观权重,采用熵权法确定各评估指标的客观权重,并通过博弈论方法计算评估指标的综合权重;最后,将权重结果与评语层云模型结合使用对各级安全评估指标进行安全评估,通过MATLAB软件完成算例的仿真分析。结果表明:该塔台管制系统运行安全等级在一般和良好之间,仍需采取有效措施对某些风险因素进行控制;同时验证了该模型在塔台管制系统运行安全评估中具有可行性和准确性,对塔台管制系统安全评估具有指导意义。

基于模糊PID汽车变速箱自动控制方法

为改善汽车变速箱的目标速度跟踪水平,提升汽车的动力性,基于模糊PID汽车变速箱自动控制方法,确定汽车行驶的目标车速,计算目标车速与实际车速之间的偏差,以及速度偏差的变化率,将上述结果作为PID控制器的输入,利用参数整定后的PID控制器,确定汽车变速箱的控制变量,控制汽车传动机构输出理想车速。实验结果表明,汽车以阶跃信号、斜坡信号和正弦信号状态行驶时,该方法均可以精准跟踪汽车变速箱的速比,控制效果与动态跟踪性能优异,为保持汽车的最佳动力性能提供了良好的控制策略。

水资源污染综合治理措施及其防治效果评估研究

长期的水污染会破坏水环境,造成生态系统的破坏和失衡,影响人类的生产和生活。为此,研究水资源污染综合治理措施并评估防治效果。在分析了水资源污染物的4种主要类型后,从工业生产、市政管理以及工程保障3方面提出相应的治理措施,并使用模糊综合评价法对治理后的效果评价,将评价结果分为5个等级,利用加权平均原则对评价结果定量计算。将所提治理措施应用在某市生态公园调节塘内,经一段时间后检验该塘水质有了明显改善,防治效果评估结果为优秀,证明所提方法在水资源污染治理方面具有可行性。

基于模糊排序的永磁同步电动机模型预测电流控制

针对永磁同步电动机模型预测电流控制的成本函数中权重系数不容易确定的问题,提出一种基于模糊排序法的模型预测电流控制策略。首先,通过排序法对不同电压矢量所对应的电流误差及切换时的开关频率进行排序,从而无须再对权重系数进行设计。由于控制目标重要性并不完全等同,设计一种带有变增益系数的排序优化方法,调节控制目标的重要程度。传统的权重系数有着连续的取值范围,而变增益系数的取值范围有着离散性和分段性的特点,相比较之下,后者的调整和设计过程更加的简易。再通过模糊控制,对变增益系数进行动态优化,从而更好地适应电机不断变化的运行状态。最后,仿真和半实物实验结果证明了所提方法的有效性和可行性。

芦岭煤矿10号煤层瓦斯赋存及其控制因素综合评价

为准确、快速预测矿井煤层瓦斯赋存情况并确定其控制因素,利用分源预测法和模糊物元评价方法,分析了芦岭煤矿10号煤层瓦斯赋存规律,并开展了瓦斯赋存控制因素综合评价。研究结果表明:10号煤层瓦斯涌出量总体较高,具有“中、西部高,东南部低”的分布特点,且瓦斯涌出量随着深度的增加而增大,其涌出量范围在9.23~16.11 m^(3)/t;研究区根据控制因素评价划分为3类区域,其中西南浅部为Ⅰ类区域,东北深部多为Ⅱ类、Ⅲ类区域。