Inter-organizational supply chain performance: How the relationship factors influence the Australian beef industry?

This study examines supply chain structures and inter-organizational relationship factors that influence the supply chain performance in the Australian beef industry. It investigated the extent to which aggregated relationship strength is a source of supply chain performance for the industry. The effect of antecedent factors such as vertical coordination, negotiation power and the use of IOS in the relationship strength were also investigated. Data were collected through a telephone survey in 315 firms including input suppliers, producers, processors and retailers in the beef industry of Western Australia and Queensland. The results support both the direction of theoretical underpinnings from RBV and TCE in the beef industry, that durable buyer-supplier relationships in the supply chain are developed from the level of commitment and trust, interdependence and mutual investment and can be a strategic economic resource to by-pass the cost of traditional market transactions. Results suggest the following key success factors for the beef industry in Australia: (a) the operational adoption of a lean supply chain between producer and processors or processors and retailers; (b) a transparent interdependent relationship with a strong consolidation/integration of business activities; and (c) synchronized information flows for greater compliance with carcass specifications in the supply chain

Prospects of Hyperloop Transportation Technology: A Case of China

Hyperloop transportation technology is amongst the most promising sustainable and climate-friendly transportation systems of the modern era. Now China has taken steps to build this transportation system in Tongren city, which located on Guizhou's eastern part [8]. So far, not much work has been conducted on the prospects of this technology, especially for China. In this paper based on extensive literature review, we have analyzed the prospects of this technology in China. Furthermore, this article also discusses the possible hurdles and proposes some suggestions for overcoming the problems in the adoption of this climate-friendly technology

Effect of Hartmann Number on Free Convective Flow in a Square Cavity with Different Positions of Heated Square Block

This paper is concerned with the effect of Hartmann number on the free convective flow in a square cavity with different positions of heated square block. The two-dimensional Physical and mathematical model have been developed, and mathematical model includes the system of governing mass, momentum and energy equations are solved by the finite element method. The calculations have been computed for Prandtl number Pr=0.71, the Rayleigh number Ra=1000 and the different values of Hartmann number. The results are illustrated with the streamlines, isotherms, velocity and temperature fields as well as local Nusselt number

A new fuzzy logic controller based IPM synchronous motor drive

This paper presents a novel fuzzy logic controller (FLC) scheme for speed control of an interior permanent magnet synchronous motor (IPMSM) drive. The proposed FLC is designed to have less computational burden, which makes it suitable for online implementation. The FLC parameters are optimized by genetic algorithm. The complete vector control scheme incorporating the FLC is successfully implemented in real-time using a digital signal processor board DS 1102 for a laboratory 1 hp interior permanent magnet (IPM) motor. The efficacy of the proposed FLC based IPMSM drive is verified by simulation as well as experimental results at different dynamic operating conditions such as sudden load change, parameter variations, step change of command speed, etc. The proposed fuzzy logic controller is found to be a robust controller for application in IPMSM drive

A new fuzzy logic controller based IPM synchronous motor drive

This paper presents a novel fuzzy logic controller (FLC) scheme for speed control of an interior permanent magnet synchronous motor (IPMSM) drive. The proposed FLC is designed to have less computational burden, which makes it suitable for online implementation. The FLC parameters are optimized by genetic algorithm. The complete vector control scheme incorporating the FLC is successfully implemented in real-time using a digital signal processor board DS 1102 for a laboratory 1 hp interior permanent magnet (IPM) motor. The efficacy of the proposed FLC based IPMSM drive is verified by simulation as well as experimental results at different dynamic operating conditions such as sudden load change, parameter variations, step change of command speed, etc. The proposed fuzzy logic controller is found to be a robust controller for application in IPMSM drive

Real-Time Performance Evaluation of a Genetic Algorithm Based Fuzzy Logic Controller for IPM Motor Drives

This work presents a novel speed control scheme using a genetic-based fuzzy logic controller (GFLC) for an interior permanent-magnet synchronous motor (IPMSM) drive. The proposed GFLC is developed to have less computational burden, which makes it suitable for real-time implementation. The parameters for the GFLC are tuned by genetic algorithm (GA). The complete drive incorporating the GFLC is successfully implemented in real-time using a digital signal processor board DS 1102 for a laboratory 1-hp interior permanent magnet motor. The efficacy of the proposed GFLC-based IPMSM drive is verified by simulation as well as experimental results at various operating conditions. A performance comparison with a conventional proportional-integral controller is also provided to show the superiority of the proposed controller. The proposed GFLC is found to be robust for high-performance industrial drive applications

Real-Time Performance Evaluation of a Genetic Algorithm Based Fuzzy Logic Controller for IPM Motor Drives

This work presents a novel speed control scheme using a genetic-based fuzzy logic controller (GFLC) for an interior permanent-magnet synchronous motor (IPMSM) drive. The proposed GFLC is developed to have less computational burden, which makes it suitable for real-time implementation. The parameters for the GFLC are tuned by genetic algorithm (GA). The complete drive incorporating the GFLC is successfully implemented in real-time using a digital signal processor board DS 1102 for a laboratory 1-hp interior permanent magnet motor. The efficacy of the proposed GFLC-based IPMSM drive is verified by simulation as well as experimental results at various operating conditions. A performance comparison with a conventional proportional-integral controller is also provided to show the superiority of the proposed controller. The proposed GFLC is found to be robust for high-performance industrial drive applications

Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives

A hybrid neuro-fuzzy scheme for online tuning of a genetic-based proportional-integral (PI) controller for an interior permanent-magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under various system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed FBFN-based PI controller provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed controller is successfully implemented in real time using a digital signal processor board DS 1102 for a laboratory 1-hp IPMSM. The effectiveness of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed controller is found to be robust for applications in an IPMSM drive

Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives

A hybrid neuro-fuzzy scheme for online tuning of a genetic-based proportional-integral (PI) controller for an interior permanent-magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under various system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed FBFN-based PI controller provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed controller is successfully implemented in real time using a digital signal processor board DS 1102 for a laboratory 1-hp IPMSM. The effectiveness of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed controller is found to be robust for applications in an IPMSM drive