Fuzzy logic applied to speed control of a stepping motor drive

Nowadays, thanks to the development of microprocessors, stepping motors are widely used in robotics and in the numerical control of machine tools where they have to perform high-precision positioning operations. Nevertheless, the variations of the mechanical configuration of the drive, which are common to these two applications, can lead to a loss of synchronism for high stepping rates. Moreover, the classical open-loop speed control is weak and a closed-loop control becomes necessary. In this paper, the fuzzy logic principle is applied to control the speed of a stepping motor drive with feedback. An advanced test bed is used in order to evaluate the tracking properties and the robustness capacities of the fuzzy logic controller when variations of the mechanical configuration occur. The experiment has been performed using a low-cost 16 bit microcontroller in order to verify the design performance     

Fuzzy logic based on-line efficiency optimization control of anindirect vector-controlled induction motor drive

Improvement of adjustable speed drive system efficiency is important not only from the viewpoints of energy saving and cooling system operation, but also from the broad perspective of environmental pollution. The paper describes a fuzzy logic based on-line efficiency optimization control of a drive that uses an indirect vector controlled induction motor speed control system in the inner loop. At steady-state light-load condition, a fuzzy controller adaptively decrements the excitation current on the basis of measured input power such that, for a given load torque and speed, the drive settles down to the minimum input power, i.e., operates at maximum efficiency. The low-frequency pulsating torque due to decrementation of rotor flux is compensated in a feedforward manner. If the load torque or speed command changes, the efficiency search algorithm is abandoned and the rated flux is established to get the best transient response. The drive system with the proposed efficiency optimization controller has been simulated with lossy models of the converter and machine, and its performance has been thoroughly investigated. An experimental drive system with the proposed controller implemented on a TMS320C25 digital signal processor, has been tested in the laboratory to validate the theoretical development     

Design and implementation of a high-performance field-orientedinduction motor drive

The design and implementation of a high-performance controller for a field-oriented induction motor drive is presented. Dynamic modeling based on the stochastic technique is performed. Based on the estimated drive model, a two-degree-of-freedom controller is proposed so good dynamic responses in both the speed tracking and regulation characteristics can be achieved. The parameters of the controller are found using a proposed systematic design procedure according to the prescribed specifications. Having designed and tested the performance of the controller by simulation, the hardware implementation is successfully made, and some experimental results are given to demonstrate the effectiveness of the proposed controller     

Fuzzy logic control of an active power line conditioner

Fuzzy logic and active power line conditioners (APLC) are two tools that are being increasingly applied to power quality problems. In this paper, a switch-mode APLC that uses fuzzy logic to control the semiconductor switches is described. Frequency-domain analysis is used to determine the desired compensation current, and a rule-based piecewise-linear fuzzy proportional-integral controller (FPIC) provides the appropriate switching pattern of the APLC to generate the actual compensation current. MATLAB simulations and experimental measurements on a low-power (700 VA), digital signal processor-based, hardware prototype show that the APLC produces excellent results despite the use of a relatively low switching frequency, which is necessary to minimize semiconductor switching losses. The simulations and measurements are in good agreement and show that the APLC/FPIC system can significantly improve line current total harmonic distortion and power factor during both steady-state and transient operating conditions.     

An enhanced Z-source inverter topology-based permanent magnet brushless DC motor drive speed control

In this paper, an enhanced Z-source inverter (ZSI) is introduced for controlling the speed of permanent magnet brushless DC motor (PMBLDCM) drive. It is the extension of the conventional ZSI and the elements used in the circuit are the same as those of the conventional ZSI, except that the position of Inverter Bridge and diode would be exchanged from the classical circuit diagram. This exchanged circuit avoids the startup path of the inrush current and hence reduces the inrush current and improves the motor efficiency. Different modes of enhanced ZSI are studied with PMBLDCM. The voltage polarity of Z-source capacitors in the proposed circuit is the same as that of the input voltage polarity. Furthermore, to get the same voltage boost, the capacitor voltage stress is reduced to a significant extent. The speed control capability of the proposed brushless DC motor drive is compared with that of the conventional ZSI. The proposed ZSI is implemented in MATLAB/Simulink working platform and the output performance is evaluated. Also, the performance of voltage ratio is analysed both by simulation and mathematical models. All these analyses are known to express the innovative features of the proposed system.     

Fuzzy logic based intelligent control of a variable speed cagemachine wind generation system

The paper describes a variable speed wind generation system where fuzzy logic principles are used for efficiency optimization and performance enhancement control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which pumps power to a utility grid or can supply to an autonomous system. The generation system has fuzzy logic control with vector control in the inner loops. A fuzzy controller tracks the generator speed with the wind velocity to extract the maximum power. A second fuzzy controller programs the machine flux for light load efficiency improvement, and a third fuzzy controller gives robust speed control against wind gust and turbine oscillatory torque. The complete control system has been developed, analyzed, and validated by simulation study. Performances have then been evaluated in detail     

The visualisation of control logic and physical machine elements within an integrated machine design and control environment

The process of designing and implementing complex manufacturing machines relies heavily on the ability of systems designers and end users to provide consistent information on the desired and achieved operation of both the physical and logical elements that comprise the system. The information required varies throughout the life cycle of the machine implementation, i.e. the emphasis changes from obtaining results of “what if?” scenarios at the requirements and design stages to obtaining the variation of sensor values and current status of the control logic at the monitoring and operational stages. The most difficult part of the process is establishing a common representational scheme to facilitate communications between stakeholders.Visual representation and integration of the physical components and control logic in complex manufacturing machines in an Integrated Machine Design and Control (IMDC) environment is discussed in this paper. The approach taken is unique in that (a) the control logic and physical models of the elements can be investigated individually for correctness and completeness, (b) the control logic can be easily integrated with the physical models to animate the modelled physical machine and (c) reconfiguration enables the same control logic to be applied to real world physical control elements. Furthermore, the design of the environment has been based around enabling interaction with machine models rather than passive observation of the system behaviour. At any stage during the machine design and implementation process, the user of the environment can pause and question the validity of certain operations and control system parameters.Successful companies must use their manufacturing as a competitive weapon. The attainment of effective machine visualisation between the stakeholders in the design and implementation process is an essential element in effectively addressing the business need for an agile enterprise. In the context of machine design the term agile enterprise implies rapid response to “unforeseen” customer demands, at minimum cost and with maximum confidence in the final solution.     

Cross-coupled fuzzy logic control for multiaxis machine tools

This paper presents a design and implementation case study that focuses on contour control of a biaxial CNC machine tools. Since, it is difficult to obtain an accurate nonlinear mathematical model of cross-coupled multiaxis machine tools, here we investigate an alternative to conventional approaches where we employ crosscoupled fuzzy logic controllers for improving the contouring accuracy of multiaxis CNC machine tools. A new fuzzy rule-generated method which is based on a performance index of the contour error obtained from an on-line estimation algorithm is proposed. An adapted output scale factor is adopted to improve the system performance. Experimental results have shown that the desired contouring accuracy can be achieved, and the proposed approach outperforms over uncoupled approaches. In conventional control, increasing contour feedrate for productivity may result in larger contour errors. However, the experimental results have shown that the performance of the proposed approach is still quite good with increasing contour feedrate.     

Fuzzy logic congestion control for broadband wireless IPTV

All-IP broadband networks are being created with multimedia bandwidth requirements in mind. A unicast IPTV service forming a pipe or sub-channel on the converged network may need to negotiate a broadband wireless link. Where there is a need for multiple variable bit rate video streams to share the same pipe a problem of link utilisation arises [1], requiring congestion control at the server bank. Conventional controllers such as TCP-friendly rate control (TFRC) [2] and TCP emulation at receivers (TEAR) [3], originating in a TCP-dominated internet, will stream video up to the capacity of the pipe, but reacting to feedback may overestimate the capacity, resulting in packet loss, which leads to reduced video quality. In this Letter, fuzzy logic control (FLC) is shown to outperform conventional control in such a network by changing the quantisation parameter for live video or through a bit rate transcoder for pre-encoded video. Moreover, compared to prior use of traditional (type-1) fuzzy logic for similar purposes [4], interval type-2 (IT2) FLC has been employed, as this is robust to feedback measurement uncertainties.     

Fuzzy logic control of FES rowing exercise in paraplegia

An indoor personal rowing machine (Concept 2 Inc., Morrisville, VT) has been modified for functional electrical stimulation assisted rowing exercise in paraplegia. To successfully perform the rowing maneuver, the voluntarily controlled upper body movements must be coordinated with the movements of the electrically stimulated paralyzed legs. To achieve such coordination, an automatic controller was developed that employs two levels of hierarchy. A high level finite state controller identifies the state or phase of the rowing motion and activates a low-level state-dedicated fuzzy logic controller (FLC) to deliver the electrical stimulation to the paralyzed leg muscles. A pilot study with participation of two paraplegic volunteers showed that FLC spent less muscle energy, and produced smoother rowing maneuvers than the existing On-Off constant-level stimulation controller.     

Fuzzy logic for constant force control of end milling

The machining condition usually has significant variation resulting from the change of cutting depth and the intrinsic property of the workpiece. In order to maintain the performance of a classical proportional integral derivative control system, the tool life and machining quality, conservative feedrate, and cutting depth change are prespecified as the limitations of computer numerically controlled operators. Therefore, constant cutting force control is proposed as a useful approach for increasing the metal removal rate and the tool life. However, the model-based controller cannot handle the nonlinearity of a force control system due to cutting condition variations. Here, a fuzzy controller with learning ability was employed to improve both the system performance and the adaptability. This control approach vias implemented on a retrofit old-fashioned milling machine for the end milling process. The experimental results show that this control strategy has smooth feedrate and good cutting force dynamic responses     

Adaptive enhanced fuzzy sliding-mode control for electrical servo drive

The design and properties of an adaptive enhanced fuzzy sliding-mode control (AEFSMC) system for an indirect field-oriented induction motor (IM) drive to track periodic commands are addressed in this study. A newly designed EFSMC system, in which a translation-width idea is embedded into the FSMC, is introduced initially. Moreover, to confront the uncertainties existed in practical applications, an adaptive tuner, which is derived in the sense of the Lyapunov stability theorem, is utilized to adjust the EFSMC parameter for further assuring robust and optimal control performance. The indirect field-oriented IM drive with the AEFSMC scheme possesses the salient advantages of simple control framework, free from chattering, stable tracking control performance, and robust to uncertainties. In addition, numerical simulation and experimental results due to periodic sinusoidal commands are provided to verify the effectiveness of the proposed control strategy, and its advantages are indicated in comparison with FSMC and EFSMC systems.     

An ice machine adapted into an autonomous photovoltaic system without batteries using a variable‐speed drive

The adaptation of a commercially available ice machine for autonomous photovoltaic operation without batteries is presented. In this adaptation a 1040 W_p photovoltaic array directly feeds a variable‐speed drive and a 24 V_dc source. The drive runs an induction motor coupled by belt‐and‐pulley to an open reciprocating compressor, while the dc source supplies a solenoid valve and the control electronics. Motor speed and refrigerant evaporation pressure are set aiming at continuously matching system power demand to photovoltaic power availability. The resulting system is a simple integration of robust, standard, readily available parts. It produces 27 kg of ice in a clear‐sky day and has ice production costs around US$0.30/kg. Although a few machine features might be specific to Brazil, its technical and economical guidelines are applicable elsewhere. Copyright © 2010 John Wiley & Sons, Ltd.     

Mechatronic design and injection speed control of an ultra high-speed plastic injection molding machine

This paper presents pragmatic techniques for mechatronic design and injection speed control of an ultra high-speed plastic injection molding machine. Practical rules are proposed to select specifications of key mechatronic components in the hydraulic servo system, in order to efficiently construct an industry-level machine. With reasonable assumptions, a mathematical model of the injection speed control system is established and open-loop experimental data are then employed to validate the system model. By the model, a gain-scheduling PI controller and a fuzzy PI controller are presented, compared and then implemented into a digital signal processor (DSP) using standard C programming techniques. Experimental results are conducted to show that the two proposed controllers are capable of achieving satisfactory speed tracking performance. These developed techniques may provide useful references for engineers and practitioners attempting to design pragmatic, low-cost but high-performance ultra high-injection speed controllers.     

High-performance speed control of electric machine usinglow-precision shaft encoder

For a high-performance servo drive system, it is important to estimate and control the motor speed precisely over a wide-speed range. Therefore, the disturbance-rejection ability and the robustness to variations of the mechanical parameters such as inertia should be considered. This paper shows that the adaptive state estimator and self-tuning regulator based on the recursive extended least squares (RELS) parameter identification method can achieve high-performance speed control over a wide-speed range. The RELS method identifies the variations of mechanical parameters, and the estimated mechanical parameters are used to replace the role of manual tuning by adjusting the gain of the speed controller automatically for good dynamic response. Also, these estimated parameters are used to adapt the Kalman filter, which is an optimal state estimator, to provide good estimation performance for the rotor speed, rotor position and disturbance torque even in a noisy environment. Simulation and experimental results show an improved speed control performance in the wide-speed range     

Fuzzy logic rotor position estimation based switched reluctance motor DSP drive with accuracy enhancement

This paper describes a novel angle estimation scheme for a real time digital signal processor (DSP) based switched reluctance motor drive using fuzzy logic where several unique techniques are implemented to improve the estimation accuracy. First, an optimized fuzzy model of the motor was created using an adaptive neuro-fuzzy inference system (ANFIS) based on accurately measured flux linkage data. Secondly, an improved fuzzy optimal sensing phase selector was developed based on the analysis of both modeling error and measurement error. Lastly, a delayless polynomial predictive filter and an online phase winding resistance estimator are also implemented to further improve the position estimation accuracy. Both simulation and experiment results on a DSP based real time drive are presented to show the effectiveness of this scheme.     

A high-performance sensorless indirect stator flux orientation control of induction motor drive

A new method for the implementation of a sensorless indirect stator-flux-oriented control (ISFOC) of induction motor drives with stator resistance tuning is proposed in this paper. The proposed method for the estimation of speed and stator resistance is based only on measurement of stator currents. The error of the measured q-axis current from its reference value feeds the proportional plus integral (PI) controller, the output of which is the estimated slip frequency. It is subtracted from the synchronous angular frequency, which is obtained from the output integral plus proportional (IP) rotor speed controller, to have the estimated rotor speed. For current regulation, this paper proposes a conventional PI controller with feedforward compensation terms in the synchronous frame. Owing to its advantages, an IP controller is used for rotor speed regulation. Stator resistance updating is based on the measured and reference d-axis stator current of an induction motor on d-q frame synchronously rotating with the stator flux vector. Experimental results for a 3-kW induction motor are presented and analyzed by using a dSpace system with DS1102 controller board based on the digital signal processor (DSP) TMS320C31. Digital simulation and experimental results are presented to show the improvement in performance of the proposed method.     

A microcomputer-based control and simulation of an advanced IPMsynchronous machine drive system for electric vehicle propulsion

Describes a high-performance microcomputer-based control and digital simulation of an inverter-fed interior permanent magnet (IPM) synchronous machine that uses a neodymium-iron-boron magnet. The fully operational four-quadrant drive system includes a constant-torque region with zero speed operation and a high-speed field-weakening constant-power region. The control uses the vector or field-oriented technique in constant-torque region with the direct axis aligned to the stator flux, whereas the constant-power region control is based on torque angle orientation of the impressed square-wave voltage. All the key feedback signals for the control are estimated with precision. The drive system is basically designed with an outer torque control loop for electric vehicle application, but speed and position control loops can be added for other industrial applications. The distributed microcomputer-based control system is based on Intel-8096 microcontroller and Texas Instruments TMS32010 type digital signal processor     

无刷直流电机调速系统模糊神经元PID控制

针对传统PID控制应用于无刷直流电机调速系统存在调节时间长、动态调节特性差及抗干扰能力弱等问题,提出一种基于模糊神经元PID控制的无刷直流电机调速系统设计方法。首先采用神经元控制、比例控制和模糊控制设计了一种可在线调整参数的模糊神经元PID控制器,然后再用其设计无刷直流电机调速系统的转速调节器。仿真结果表明,基于模糊神经元PID控制的无刷直流电机调速系统具有响应速度快、动态和静态调节性能好、自适应能力和抗干扰能力强等优点。     

模糊PID在拉拔机控制系统中的应用

针对拉拔机在拉拔的过程中因负载大小不同而引起不稳定和抖动的现象,设计了模糊PID控制器。模糊PID以系统偏差和偏差变化率作为输入,通过修改PID控制器的参数来获得满意的动态和静态控制性能。仿真结果表明,模糊PID在上升时间和稳态时间上分别比传统PID控制器缩短了0.119 s和0.503 s,在快速性和稳定性上明显优于传统PID控制器。采用这种控制器改善了控制系统的动态性能,提高了系统的控制精度。