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Book part
Publication date: 14 October 2009

Rune Elvik, Alena Høye, Truls Vaa and Michael Sørensen

Abstract

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The Handbook of Road Safety Measures
Type: Book
ISBN: 978-1-84855-250-0

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Book part
Publication date: 15 December 1998

A D Mason and A W Woods

We use a combination of continuum and car-following models to explore the potential impact of speed-controls on (i) decreasing travel times at times of congested flow; and…

Abstract

We use a combination of continuum and car-following models to explore the potential impact of speed-controls on (i) decreasing travel times at times of congested flow; and (ii) increasing the safety of motorway flow approaching the site of an accident.

Details

Mathematics in Transport Planning and Control
Type: Book
ISBN: 978-0-08-043430-8

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Article
Publication date: 5 January 2010

Czeslaw T. Kowalski and Jacek D. Lis

The purpose of this paper is to present a fixed‐point implementation of a complete direct torque control (DTC) algorithm connected with a rotor speed estimation algorithm…

Abstract

Purpose

The purpose of this paper is to present a fixed‐point implementation of a complete direct torque control (DTC) algorithm connected with a rotor speed estimation algorithm for the induction motor drive, using field‐programmable gate array (FPGA).

Design/methodology/approach

The parallel processing approach is described, which requires a decomposition of the control and estimation algorithms for the converter‐fed induction motor to several tasks, realised in parallel. The advanced data processing techniques are described, like PIPELINE technique for data streams design, coordinate rotation digital computer algorithm for transformation of stator flux vector components from Cartesian to polar coordinates. Moreover, the method for the qualitative analysis of the full‐order state observer's sensitivity to the variations of the induction motor equivalent circuit parameters is presented.

Findings

It is shown that the developed FPGA‐based DTC structure enables designing an efficient application for the induction motor control. Owing to the high‐processing frequency, the digital FPGA‐based DTC application is similar in its features to the analogue realisation based on the comparators. Yet all the advantages of the digital structure, i.e. high flexibility, parameterization capability, etc. remain unchanged. Furthermore, FPGA is hardware realisation of a digital data processing algorithm; hence the reliability of the control system is improved.

Research limitations/implications

The investigations are performed in the developing prototype setup, based on PXI‐1042 Industrial PC equipped with Xilinx Virtex‐II FPGA matrix, programmed with LabVIEW.

Practical implications

The experimental tests of the FPGA‐based implementation of the whole control structure of the sensorless DTC drive system are demonstrated. It is also shown, that the full‐order state observer with the speed adaptation loop is significantly sensitive to motor parameter variations in the low‐speed region, which must be taken into account while designing the adaptation algorithm for speed estimation in real application.

Originality/value

The paper's value lies in the overall, FPGA‐based design of the speed sensorless DTC structure for the induction motor including motor speed, torque and stator flux control loops, stator flux and rotor speed estimation.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 29 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 1 October 2006

G.R. Arab Markadeh and J. Soltani

To propose and adaptive nonlinear controller for adjustable speed sensorless induction motor drive, using a novel adaptive rotor flux observer. The adaptive flux observer…

Abstract

Purpose

To propose and adaptive nonlinear controller for adjustable speed sensorless induction motor drive, using a novel adaptive rotor flux observer. The adaptive flux observer scheme in this paper provides the simultaneous estimation of the rotor speed, rotor resistance and stator resistance.

Design/methodology/approach

The IM rotor speed and rotor flux controllers are designed based on combination of input‐output feedback linearizing, linear optimal feedback control and sliding‐mode (SM) control methods. In addition a novel adaptive rotor flux observer is designed based on Lyapunov theory. The proposed control method is tested by simulation and experimental results.

Findings

The composite rotor speed and rotor flux observer in combination with adaptive rotor flux scheme guarantees a perfect speed, torque and flux tracking control for the IM sensorless drive.

Research limitations/implications

The proposed control method has a drawback in the IM low speed operating region. Additional research may be able to solve this problem as well as should analyze the sensitivity of the IM drive system performance with respect to variation of the system controller and adaptive flux observer gains. In addition, this research should also analyze the influence of sampling rate, truncation errors, measurement noise, simplifying model assumption and magnetic saturation.

Practical implications

The proposed control method can be used for adaptive and robust control of the IM drive where an optimal efficiency is desired subject to the variable load torque demand.

Originality/value

Based on Lyapunov theory, a novel adaptive rotor flux observer is introduced in which the rotor speed, rotor resistance and stator resistance are treated as the unknown constant parameters.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 25 no. 4
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 23 August 2021

Murali Dasari, A. Srinivasula Reddy and M. Vijaya Kumar

The principal intention behind the activity is to regulate the speed, current and commutation of the brushless DC (BLDC) motor. Thereby, the authors can control the torque.

Abstract

Purpose

The principal intention behind the activity is to regulate the speed, current and commutation of the brushless DC (BLDC) motor. Thereby, the authors can control the torque.

Design/methodology/approach

In order to regulate the current and speed of the motor, the Multi-resolution PID (MRPID) controller is proposed. The altered Landsman converter is utilized in this proposed suppression circuit, and the obligation cycle is acclimated to acquire the ideal DC-bus voltage dependent on the speed of the BLDC motor. The adaptive neuro-fuzzy inference system-elephant herding optimization (ANFIS-EHO) calculation mirrors the conduct of the procreant framework in families.

Findings

Brushless DC motor's dynamic properties are created, noticed and examined by MATLAB/Simulink model. The performance will be compared with existing genetic algorithms.

Originality/value

The presented approach and performance will be compared with existing genetic algorithms and optimization of different structure of BLDC motor.

Details

International Journal of Intelligent Computing and Cybernetics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 16 August 2013

Gang Chen, Wei‐gong Zhang and Xiao‐na Zhang

The paper aims to overcome the shortcomings that proportional‐integral‐derivative (PID) control for unmanned robot applied to automotive test (URAT) needs a priori manual…

Abstract

Purpose

The paper aims to overcome the shortcomings that proportional‐integral‐derivative (PID) control for unmanned robot applied to automotive test (URAT) needs a priori manual retuning, has large speed fluctuations and is hard to adjust control parameters. A novel control approach based on fuzzy neural network applied to URAT was proposed.

Design/methodology/approach

According to the target vehicle speed and driving command table, the multiple manipulator coordinated control model was established. After that, the displacement of throttle mechanical leg, clutch mechanical leg, brake mechanical leg and shift mechanical arm for URAT was used as input of fuzzy neural network (FNN) model, and vehicle speed was used as output of FNN model. The number of membership functions was three, and the type of that was generalized bell membership function (gbellmf). The hybrid learning algorithm which combined with back propagation algorithm and least square method was applied to train the model. The Sugeno model was selected as fuzzy reasoning model.

Findings

Experimental results demonstrated that compared with PID control method, the proposed approach can greatly improve the accuracy of vehicle speed tracking. The approach can accurately realize the vehicle speed tracking of given driving test cycle. Therefore, it can ensure the accuracy and effectiveness of automotive test results.

Research limitations/implications

Future work will focus on improving the efficiency of this learning algorithm.

Practical implications

The paper provides effective methods for improving the accuracy of speed tracking and repeatability.

Originality/value

After establishing the multiple manipulator coordinated control model, this paper proposes a novel control approach based on FNN for URAT.

Details

Industrial Robot: An International Journal, vol. 40 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

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Article
Publication date: 26 July 2013

Xiaohui Xie, Cui Ma, Qiang Sun and Ruxu Du

Bar‐tacking is a specialized sewing stitch designed to provide immense tensile strength to the garment which requires a high‐speed precision bar‐tacking sewing machine…

Abstract

Purpose

Bar‐tacking is a specialized sewing stitch designed to provide immense tensile strength to the garment which requires a high‐speed precision bar‐tacking sewing machine. This paper aims to present an event‐driven multi‐axis cooperative control method for a bar‐tacking sewing machine.

Design/methodology/approach

The control method consists of two parts: the multi‐axis cooperative control and the needle stop positioning control. The challenges include the high speed and the precision. For example, the needle must stop at a set position in milliseconds.

Findings

The presented multi‐axis cooperative control can ensure the high speed response and the precision of the cooperative control. The needle stop positioning control is based on a combination of the velocity control and the position control with velocity feed‐forward and limitation.

Research limitations/implications

The bar‐tacking sewing machine requires high‐speed start and stop response and coordination of displacement and velocity only at some given points. Therefore, the conventional multi‐axis cooperative control methods are not suitable. In addition, it requires high‐speed precision control under varying loading conditions.

Practical implications

While there are a number of commercial textile machines available in the market, designing a smart bar‐tacking sewing machine with good speed and precision performance remains a challenge.

Originality/value

The bar‐tacking sewing machine requires highly accurate multi‐axes cooperative control. The presented event‐driven multi‐axis control method is effective. It has not only the required high accuracy but also the fast time response.

Details

International Journal of Clothing Science and Technology, vol. 25 no. 4
Type: Research Article
ISSN: 0955-6222

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Abstract

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Traffic Safety and Human Behavior
Type: Book
ISBN: 978-1-78635-222-4

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Article
Publication date: 15 July 2019

Yong Li, Yanjun Huang and Xing Xu

Sensorless interior permanent magnet in-wheel motor (IPMIWM), as an exemplar of modular automation system, has attracted considerable interests in recent years. This paper…

Abstract

Purpose

Sensorless interior permanent magnet in-wheel motor (IPMIWM), as an exemplar of modular automation system, has attracted considerable interests in recent years. This paper aims to investigate a novel hybrid control approach for the sensorless IPMIWM from a cyber-physical systems (CPS) perspective.

Design/methodology/approach

The control approach is presented based on the hybrid dynamical theory. In the standstill-low (S-L) speed, the rotor position/speed signal is estimated by the method of the high frequency (HF) voltage signal injection. The least square support vector machine (LS-SVM) is used to acquire the rotor position/speed signal in medium-high (M-H) speed operation. Hybrid automata model of the IPMIWM is established due to its hybrid dynamic characteristics in wide speed range. A hybrid state observer (HSO), including a discrete state observer (DSO) and a continuous state observer (CSO), is designed for rotor position/speed estimation of the IPMIWM.

Findings

The hardware-in-the-loop testing based on dSPACE is carried out on the test bench. Experimental investigations demonstrate the hybrid control approach can not only identify the rotor position/speed signal with a certain load but also be able to reject the load disturbance. The reliability and the effectiveness of the proposed hybrid control approach were verified.

Originality/value

The proposed hybrid control approach for the sensorless IPMIWM promotes the deep combination and coordination of sensorless IPMIWM drive system. It also theoretically supports and extends the development of the hybrid control of the highly integrated modular automation system.

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Article
Publication date: 10 August 2021

Vanchinathan Kumarasamy, Valluvan KarumanchettyThottam Ramasamy and Gnanavel Chinnaraj

The puspose of this paper, a novel systematic design of fractional order proportional integral derivative (FOPID) controller-based speed control of sensorless brushless DC…

Abstract

Purpose

The puspose of this paper, a novel systematic design of fractional order proportional integral derivative (FOPID) controller-based speed control of sensorless brushless DC (BLDC) motor using multi-objective enhanced genetic algorithm (EGA). This scheme provides an excellent dynamic and static response, low computational burden, the robust speed control.

Design/methodology/approach

The EGA is a meta-heuristic-inspired algorithm for solving non-linearity problems such as sudden load disturbances, modeling errors, power fluctuations, poor stability, the maximum time of transient processes, static and dynamic errors. The conventional genetic algorithm (CGA) and modified genetic algorithm (MGA) are not very effective in solving the above-mentioned problems. Hence, a multi-objective EGA optimized FOPID (EGA-FOPID) controller is proposed for speed control of sensorless BLDC motor under various conditions such as constant load conditions, varying load conditions, varying set speed (Ns) conditions, integrated conditions and controller parameters uncertainty.

Findings

This systematic design of the multi-objective EGA-FOPID controller is implemented in MATLAB 2020a with Simulink models for optimal speed control of the BLDC motor. The overall performance of the EGA-FOPID controller is observed and evaluated for computational burden, time integral performance indexes, transient and steady-state characteristics. The hardware experiment results confirm that the proposed EGA-FOPID controller can precisely change the BLDC motor speed is desired range with minimal effort.

Research limitations/implications

The conventional real time issues such as nonlinearity characteristics, poor controllability and stability.

Practical implications

It is clearly evident that out of these three intelligent controllers, the EGA optimized FOPID controller gives enhanced performance by minimizing the time domain parameters, performance Indices error and convergence time. Also, the hardware experimental setup and the results of the proposed EGA-FOPID controller are presented.

Originality/value

It shows the effectiveness of the proposed controllers is completely verified by comparing the above three intelligent optimization algorithms. It is clearly evident that out of these three intelligent controllers, the EGA optimized FOPID controller gives enhanced performance by minimizing the time domain parameters, performance Indices error and convergence time. Also, the hardware experimental setup and the results of the proposed EGA-FOPID controller are presented.

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