模糊控制理论在柔性结构振动主动控制中的应用

阐述了模糊控制理论在柔性结构振动主动控制中的应用;论述了运用模糊控制理论进行结构振动控制的必要性和可行性;详细介绍了振动模糊控制方法的过程及神经网络技术与模糊控制相结合的问题;指出了振动模糊控制中需发展的几个问题。     

Variable-order fuzzy fractional PID controller

In this paper, a new tuning method of variable-order fractional fuzzy PID controller (VOFFLC) is proposed for a class of fractional-order and integer-order control plants. Fuzzy logic control (FLC) could easily deal with parameter variations of control system, but the fractional-order parameters are unable to change through this way and it has confined the effectiveness of FLC. Therefore, an attempt is made in this paper to allow all the five parameters of fractional-order PID controller vary along with the transformation of system structure as the outputs of FLC, and the influence of fractional orders λ and μ on control systems has been investigated to make the fuzzy rules for VOFFLC. Four simulation results of different plants are shown to verify the availability of the proposed control strategy.     

超声电机基于模糊-PI技术的位置控制

通过超声电机的工作原理分析,选定驱动频率作为其速度控制变量。将模糊-PI技术用于超声电机的控制。其中,PI控制在于减小稳态误差,模糊控制旨在实现电机快速定位。为设计模糊控制器,选定位置偏差和转速为其输入变量、驱动频率为其输出变量,并分别以三角、高斯型函数定义了输入、输出变量的模糊子集;根据电机手动操作经验,建立了超声电机模糊控制规则;基于GO-400控制卡构建控制系统,实现了电机控制;实验结果表明模糊-PI技术可实现超声电机快速高精度(偏差≤0.17°)定位。     

H∞ synchronization of uncertain fractional order chaotic systems: adaptive fuzzy approach

This paper presents a novel adaptive fuzzy logic controller (FLC) equipped with an adaptive algorithm to achieve H(∞) synchronization performance for uncertain fractional order chaotic systems. In order to handle the high level of uncertainties and noisy training data, a desired synchronization error can be attenuated to a prescribed level by incorporating fuzzy control design and H(∞) tracking approach. Based on a Lyapunov stability criterion, not only the performance of the proposed method is satisfying with an acceptable synchronization error level, but also a rather simple stability analysis is performed. The simulation results signify the effectiveness of the proposed control scheme.     

Fuzzy sliding mode observer with dual SOGI-FLL in sensorless control of PMSM drives

To improve the performance of permanent-magnet synchronous motor (PMSM) drives, a sensorless control scheme based on a sliding mode observer (SMO) with a fuzzy logic controller (FLC) and a dual second-order generalized integrator-frequency locked loop (DSOGI-FLL) is proposed in this paper. The major drawbacks of the conventional SMO, namely chattering phenomena, high-order harmonics and external noise, are discussed. These drawbacks affect the estimated accuracy of the SMO and reduce the control reliability of the system. To eliminate these drawbacks, an FLC is designed and integrated into the SMO to adjust the observer gain in a self-adaptive manner and to reduce the chattering; an existing dual synchronous frequency extract filter-phase locked loop (DSFF-PLL) is used to filter out the main components of high-order harmonics and to calculate the rotor position and speed precisely. Furthermore, to obtain an accurate fundamental frequency for the phase locked loop (PLL) and filter out the remaining harmonics and external noise signals, DSOGI-FLL processing is developed and incorporated into the DSFF-PLL. An overall PMSM sensorless control system based on the proposed SMO is designed, and an experimental platform using the TMS320F28335 DSP controller is built. Comparative experiments using the proposed SMO and the conventional SMO are performed to validate the effectiveness of the proposed FLC and the DSFF-DSOGI-FLL-PLL structures. Performance experiments of the overall proposed SMO-based sensorless control scheme are performed to verify the robustness and control reliability of the system. The results show that the proposed SMO has satisfactory performances and can be used in practical engineering.     

Adaptive fuzzy sliding mode control for an automatic arc welding system

This paper describes an automatic welding control system developed for alternating current shielded metal arc welding (SMAW). This method could replace manual operations which require a well-trained technician. We have derived a mathematical model of the welding control system and identified the system’s parameters. The sliding surface is used as the input variable to reduce the number of fuzzy reasoning rules, in comparison with the conventional two-dimensional fuzzy logic control (FLC) algorithm. An adaptive fuzzy sliding mode controller (AFSMC) consists of an equivalent control part and a hitting control part. An adaptive law derived from a Lyapunov function is used to obtain the FLC’s parameters, and is applied to approximate the equivalent control part of the sliding mode control (SMC), so that the system states can be forced to zero. By using three-rules FLC, the control part that satisfies the hitting conditions of the SMC can force the system’s states to reach and remain on the sliding surface. Therefore, the stability of the AFSMC can be guaranteed and can be used to modulate the rate of the electrode feeding mechanism that regulates the arc current of the SMAW. The simulation and the experimental results both show that this automatic welding control system, based on the AFSMC, can perform effectively.     

A new self-tuned PID-type fuzzy controller as a combination of two-term controllers

The present paper is a venture into the domain of proportional-integral-derivative (PID) -type adaptive fuzzy logic controllers (FLC's) and proposes a new algorithm which is realized by a self-tuned PI-type FLC (in velocity form) in parallel with a self-tuned PD-type FLC (in position form). Each of these PI/PD controllers implements a supervisory static FLC for adaptive online modification of the output scaling factor (SF) of a static PI/PD FLC. The proposed scheme is developed with a view to having a PID-type FLC with an architecture, simple enough for practical implementation, which at the same time has substantially satisfactory performance for a wide class of processes. Simulation studies on a range of processes reveal that the proposed controller has better performance compared to many of its existing counterparts.     

Adaptive fuzzy sliding mode control for an automatic arc welding system

This paper describes an automatic welding control system developed for alternating current shielded metal arc welding (SMAW). This method could replace manual operations which require a well-trained technician. We have derived a mathematical model of the welding control system and identified the system’s parameters. The sliding surface is used as the input variable to reduce the number of fuzzy reasoning rules, in comparison with the conventional two-dimensional fuzzy logic control (FLC) algorithm. An adaptive fuzzy sliding mode controller (AFSMC) consists of an equivalent control part and a hitting control part. An adaptive law derived from a Lyapunov function is used to obtain the FLC’s parameters, and is applied to approximate the equivalent control part of the sliding mode control (SMC), so that the system states can be forced to zero. By using three-rules FLC, the control part that satisfies the hitting conditions of the SMC can force the system’s states to reach and remain on the sliding surface. Therefore, the stability of the AFSMC can be guaranteed and can be used to modulate the rate of the electrode feeding mechanism that regulates the arc current of the SMAW. The simulation and the experimental results both show that this automatic welding control system, based on the AFSMC, can perform effectively.     

直流串激电机调速的模糊控制仿真研究

在MATLAB环境下使用模糊控制对直流串激电机的调速系统进行仿真研究。设计的模糊控制器以电机的转速偏差及转速偏差率为输入,输出量用于控制斩波调速的PWM占空比。仿真结果表明该系统响应快,低速平稳,稳态误差小,调速精度高。     

Active fault tolerant control based on interval type-2 fuzzy sliding mode controller and non linear adaptive observer for 3-DOF laboratory helicopter

In this paper, a robust controller for a three degree of freedom (3 DOF) helicopter control is proposed in presence of actuator and sensor faults. For this purpose, Interval type-2 fuzzy logic control approach (IT2FLC) and sliding mode control (SMC) technique are used to design a controller, named active fault tolerant interval type-2 Fuzzy Sliding mode controller (AFTIT2FSMC) based on non-linear adaptive observer to estimate and detect the system faults for each subsystem of the 3-DOF helicopter.The proposed control scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller.Exponential stability of the closed loop is guaranteed by using the Lyapunov method. The simulation results show that the AFTIT2FSMC can greatly alleviate the chattering effect, providing good tracking performance, even in presence of actuator and sensor faults.     

模糊控制在大射电望远镜中的应用

针对大射电望远镜悬索粗调系统为一非线性慢时变大滞后系统的特点,提出采用模糊控制来实现馈源轨迹跟踪策略,并与工程上广泛应用的PID控制进行了对比研究,通过对阶跃信号响应的数值仿真,证明了模糊控制在大射电望远镜工程中应用的可行性。     

Rapid prototyping of fuzzy controller pneumatic servo-system

The results of simulation and experimental tests conducted for pneumatic servo-drive with FLC (fuzzy logic controller) are presented. For positioning control and teaching/play-back control of pneumatic servo-drive, a fuzzy PD (proportional-derivative) controller was designed and constructed by means of xPC Target software of Matlab-Simulink package for rapid prototyping and hardware-in-the-loop simulation. The non-linear simulation model of pneumatic servo-drive was constructed and used to tune fuzzy PD controller by means of Fuzzy Logic Toolbox of Matlab-Simulink package. The fuzzy logic PD controller enables precise positioning of pneumatic servo-drive with the precision specified for industrial manipulators. A lot of simulation and experimental tests were carried on pneumatic servo-drive with fuzzy controller which was used for its transpose and follow-up control. The designed fuzzy system is efficient, stable, and resistant to disturbances and can be applied in any configurations of pneumatic servo-drive without the necessity to tune the regulator, apply signal filtration, or additional operations in track control or restrict the signals generated. Pneumatic servo-drives with teaching/playback control system have considerable practical significance, especially in the control of manipulating machines, manipulators, and industrial robots as well as rehabilitation and physiotherapy manipulators.     

ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

0 INTRODUCTION(The satisfied control of the overall weld process is not easily accomplished, largely due to the inadequacies of the available process models. Without exceptions, most welding control methods are based upon the analytical welding models. Although these models are derived directly from the physical laws that govern the main features of the weld pool, a number of assumptions are made to obtain the mathematical solutions and some variables are ignored due to the complexity of t…     

Machining force control with intelligent compensation

Force control is an effective means of improving the quality and efficiency of machining operations, so various approaches for force control have been proposed. However, due to the nonlinear, time-varying and uncertain characteristics of machining processes, it is difficult to develop force control systems that are stable and robust over the full range of operating conditions. This study proposed two control schemes to address such difficulties in the field of nonlinear force control by using a linear feedback proportional-derivate (PD) controller respectively with two different nonlinear intelligent compensators: fuzzy logic compensator (FLC) and neural network compensator (NNC). The PD controller is used to improve the transient response while maintaining the stability of the process system, and the FLC or NNC is employed to eliminate the steady-state error and compensate for the system nonlinearity (or uncertainty). The applications of the proposed schemes in machining processes show that the controllers adapt well to nonlinearity under time-varying cutting conditions in comparison to PID, PD, and FLC. The online updating of the NNC parameters through the Feedback-Error Learning can further improve the system performance.     

Implementation of fuzzy-sliding mode based control of a grid connected photovoltaic system

The present work describes an optimal operation of a small scale photovoltaic system connected to a micro-grid, based on both sliding mode and fuzzy logic control. Real time implementation is done through a dSPACE 1104 single board, controlling a boost chopper on the PV array side and a voltage source inverter (VSI) on the grid side. The sliding mode controller tracks permanently the maximum power of the PV array regardless of atmospheric condition variations, while The fuzzy logic controller (FLC) regulates the DC-link voltage, and ensures via current control of the VSI a quasi-total transit of the extracted PV power to the grid under a unity power factor operation. Simulation results, carried out via Matlab–Simulink package were approved through experiment, showing the effectiveness of the proposed control techniques.     

转子电流变阻尼器系统振动模糊控制的实验研究

电流变液是一种智能材料 ,它具有控制方便、反应快等特点 ,适合于振动控制方面的应用。本文针对摩擦板式电流变阻尼器转子振动系统设计了自适应模糊逻辑控制策略 ,进行了转子系统振动主动控制的实验研究 ,验证了自适应模糊控制方法的有效性。实验表明 ,模糊逻辑控制方法具有算法实现简易、善于利用专家的经验以及自适应能力强等诸多优点 ;转子电流变阻尼器振动系统在模糊逻辑控制器的控制之下 ,不但一阶临界振动得到有效抑制 ,而且其它转速下的振动幅值也大大降低     

A simplified type-2 fuzzy logic controller for real-time control

Increasingly, genetic algorithms (GAs) are used to optimize the parameters of fuzzy logic controllers (FLCs). Although GAs provide a systematic design approach, the optimization process is generally performed off-line using a plant model. Differences between the model and physical plant may result in unsatisfactory control performance when the FLCs are deployed in practice. Type-2 FLCs are an attractive alternative because they can better cope with modeling uncertainties. Unfortunately, type-2 FLCs are computationally intensive. This paper presents a simplified type-2 FLC that is suitable for real-time applications. The key idea is to only replace some critical type-1 fuzzy sets by type-2 sets. Experimental results indicate that the proposed simplified type-2 FLC is as robust as a conventional type-2 FLC, while lowering the computational cost.     

Full-order Luenberger observer based on fuzzy-logic control for sensorless field-oriented control of a single-sided linear induction motor

This paper investigates sensorless indirect field oriented control (IFOC) of SLIM with full-order Luenberger observer. The dynamic equations of SLIM are first elaborated to draw full-order Luenberger observer with some simplifying assumption. The observer gain matrix is derived from conventional procedure so that observer poles are proportional to SLIM poles to ensure the stability of system for wide range of linear speed. The operation of observer is significantly impressed by adaptive scheme. A fuzzy logic control (FLC) is proposed as adaptive scheme to estimate linear speed using speed tuning signal. The parameters of FLC are tuned using an off-line method through chaotic optimization algorithm (COA). The performance of the proposed observer is verified by both numerical simulation and real-time hardware-in-the-loop (HIL) implementation. Moreover, a detailed comparative study among proposed and other speed observers is obtained under different operation conditions.     

模糊控制在移动机器人路径跟踪控制中的应用

对含不确定性的移动机器人系统设计了自适应模糊路径跟踪控制方法,此方法采用模糊逻辑系统逼近控制器中的不确定函数,基于时变死区函数对模糊逻辑系统中的未知参数进行自适应调节,并对时变死区设计了自适应律。文中证明了此方法可使跟踪误差收敛到原点的小邻域内。仿真算例验证了此方法的有效性。     

INTELLIGENT CONTROL SYSTEM OF PULSED MAG WELDING INVERTER BASED ON DIGITAL SIGNAL PROCESSOR

A fuzzy logic intelligent control system of pulsed MAG welding inverter based on digital signal processor （DSP） is proposed to obtain the consistency of arc length in pulsed MAG welding. The proposed control system combines the merits of intelligent control with DSP digital control. The fuzzy logic intelligent control system designed is a typical two-input-single-output structure, and regards the error and the change in error of peak arc voltage as two inputs and the background time as single output. The fuzzy logic intelligent control system is realized in a look-up table （LUT） method by using MATLAB based fuzzy logic toolbox, and the implement of LUT method based on DSP is also discussed. The pulsed MAG welding experimental results demonstrate that the developed fuzzy logic intelligent control system based on DSP has strong arc length controlling ability to accomplish the stable pulsed MAG welding process and controls pulsed MAG welding inverter digitally and intelligently.