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The purpose of this paper is to integrate the function of a speed controller for induction motor (IM) drive, such as the speed PI controller, the current vector controller, the slip speed estimator, the space vector pulse width modulation scheme, the quadrature encoder pulse, and analog to digital converter interface circuit, etc. into one field programmable gate array (FPGA).

First, the mathematical modeling of an IM drive, the field-oriented control algorithm, and PI controller are derived. Second, the very high speed IC hardware description language (VHDL) is adopted to describe the behavior of the algorithms above. Third, based on electronic design automation simulator link, a co-simulation work constructed by ModelSim and Simulink is applied to verify the proposed VHDL code for the speed controller intellectual properties (IP). Finally, the developed VHDL code will be downloaded to the FPGA for further control the IM drive.

In realization aspect, it only needs 5,590 LEs, 196,608 RAM bits, and 14 embedded 9-bit multipliers in FPGA to build up a speed control IP. In computational power aspect, the operation time to complete the computation of the PI controller, the slip speed estimator, the current vector controller are only 0.28 μs, 0.72 μs, and 0.96 μs, respectively.

Fast computation in FPGA can speed up the speed response of IM drive system to increase the running performance.

This is the first time to realize all the function of a speed controller for IM drive within one FPGA.

The proportional‐integral‐derivative (PID) controller has been a practical application in industry due to its simple architecture, being easily designed and its parameter tuning without complicated computation. However, the traditional PID controller usually needs some manual retuning before being used for practical application in industry. The purpose of this paper is to propose an auto‐tuning PID controller (ATPIDC) which can automatically tune the controller parameters based on the gradient descent method and the Lyapunov stability theorem. Finally, a field‐programmable gate array (FPGA) chip is adopted to implement the proposed ATPIDC scheme for possible low‐cost and high‐performance industrial applications, and it is applied to a DC servomotor to show its effectiveness.

To ensure the stability of the intelligent control system, a compensator usually should be designed. The most frequently used compensator is designed as a sliding‐mode control, which results in substantial chattering in the control effort. To tackle this problem, the proposed ATPIDC system is composed of a PID controller and a fuzzy compensator. The PID controller can automatically tune the gain factors of the controller gains based on the gradient descent method, and the fuzzy compensator is utilized to eliminate approximation error based on the Lyapunov stability theorem. The proposed fuzzy compensator not only can remove the chattering phenomena of conventional sliding‐mode control completely, but also can guarantee the stability of the closed‐loop system.

The proposed ATPIDC system is applied to a DC servomotor on a FPGA chip. The hardware implementation of the ATPIDC scheme is developed in a real‐time mode. Using the FPGA to implement, the ATPIDC system can achieve the characteristics of small size, fast execution speed and less memory. A comparison among the fuzzy sliding‐mode control, adaptive robust PID control and the proposed ATPIDC is made. Experimental results verify a better position tracking response can be achieved by the proposed ATPIDC method after control parameters training.

The proposed ATPIDC approach is interesting for the design of an intelligent control scheme. An on‐line parameter training methodology, using the gradient descent method and the Lyapunov stability theorem, is proposed to increase the learning capability. The experimental results verify the system stabilization, favorable tracking performance and no chattering phenomena can be achieved by using the proposed ATPIDC system. Also, the proposed ATPIDC methodology can be easily extended to other motors.

The purpose of the control method proposed in this paper is to address the problem of the poor anti-interference of the suspension winding current in the traditional bearingless induction motor (BL-IM) direct suspension force control process.

A model predictive direct suspension force control of a BL-IM based on sliding mode observer is proposed in this paper. The model predictive control (MPC) is introduced to the traditional direct suspension force control to improve the anti-interference of the suspension current. A sliding mode flux linkage observer is designed and applied to the MPC system, which reduces the error of the parameter observation and improves the robustness of the system. The strategy is designed and implemented in the MATLAB/Simulink and the two-level AC speed regulation platform.

The simulation and experimental results show that the performance of the BL-IM under the control method proposed in this paper is better than that under the traditional direct suspension force control, and the suspension performance of the motor and the anti-interference of the control system are improved.

This study helps to improve the suspension performance of the motor and the anti-interference of the control system.

This paper aims to present a cascaded pseudo derivative feedback (PDF) plus pseudo derivative feedback plus pseudo derivative feedforward (PDFF) controller for a permanent magnet synchronous motor (PMSM) to improve the transient response of the system.

Proportional integral (PI) plus PI controller and the proposed PDF plus PDFF controller are designed, stability analysis is performed using the extended root locus method, and the effect of the damping coefficient is also extensively studied to validate the robustness of the proposed controller.

When compared to a cascaded PI plus PI controller, the proposed control approach has a much shorter settling time for the entire system and a 50% reduction in overshoot in stator current under extensive variations in speed with load disturbance.

The proposed controller is programmed into an FPGA Altera Cyclone II and applied to a 1.5 kW laboratory prototype PMSM drive. The effectiveness of the proposed methods has been demonstrated experimentally throughout a wide variable speed range, from 0 to 157 rad/s at different load conditions.

Models of speed of internationalization have been built on narrowly defined resources, emphasizing the intangibles at the cost of tangibles and relying on controlled resources while overlooking nonterritorial ones. We build an integrative model for both established and unestablished firms, using three determinants of speed – global value chain experiences, resource adjusted expected return from internationalization and existence of e-commerce platforms. The first is under firms’ control while the last two are partially controlled or totally uncontrolled. Five strategies of internationalization are identified – internationalization through accelerated marketization, delayed internationalization, opportunistic (or on/off) internationalization, IB internationalization, and alliance internationalization, each associates with a different speed of internationalization.

The ideas expressed in this work are based on those put into practice at the Okuma Corporation of Japan, one of the world′s leading machine tool manufacturers. In common with many other large organizations, Okuma Corporation has to meet the new challenges posed by globalization, keener domestic and international competition, shorter business cycles and an increasingly volatile environment. Intelligent corporate strategy (ICS), as practised at Okuma, is a unified theory of strategic corporate management based on five levels of win‐win relationships for profit/market share, namely: ,1. Loyalty from customers (value for money) – right focus., 2. Commitment from workers (meeting hierarchy of needs) – right attitude., 3. Co‐operation from suppliers (expanding and reliable business) – right connections., 4. Co‐operation from distributors (expanding and reliable business) – right channels., 5. Respect from competitors (setting standards for business excellence) – right strategies. The aim is to create values for all stakeholders. This holistic people‐oriented approach recognizes that, although the world is increasingly driven by high technology, it continues to be influenced and managed by people (customers, workers, suppliers, distributors, competitors). The philosophical core of ICS is action learning and teamwork based on principle‐centred relationships of sincerity, trust and integrity. In the real world, these are the roots of success in relationships and in the bottom‐line results of business. ICS is, in essence, relationship management for synergy. It is based on the premiss that domestic and international commerce is a positive sum game: in the long run everyone wins. Finally, ICS is a paradigm for manufacturing companies coping with change and uncertainty in their search for profit/market share. Time‐honoured values give definition to corporate character; circumstances change, values remain. Poor business operations generally result from human frailty. ICS is predicated on the belief that the quality of human relationships determines the bottom‐line results. ICS attempts to make manifest and explicit the intangible psychological factors for value‐added partnerships. ICS is a dynamic, living, and heuristic‐learning model. There is intelligence in the corporate strategy because it applies commonsense, wisdom, creative systems thinking and synergy to ensure longevity in its corporate life for sustainable competitive advantage.

The post-pandemic emerging market is competitive and green, which has contributed to the growing pressure on firms to adopt into their business models green strategies with competitive outcomes. Therefore, this paper aims to draw from the natural resource-based view (NRBV) theory to examine how green intellectual capital (IC) can influence green competitive advantage of manufacturing firms in Ghana, by elucidating the mediating role of eco-innovation speed and quality in the relationship.

Cross-sectional survey data were obtained from 212 manufacturing firms in Ghana, using purposive sampling techniques. Exploratory and confirmatory factor analyses were conducted to determine the factor structure of the measurement models. Structural equation modelling technique was used to analyse the hypothesized relationships.

The study found that green IC has a positively significant effect on green competitive advantage of manufacturing firms. However, while eco-innovation speed positively mediates the relationship, eco-innovation quality plays a negative mediating role in the effect of green IC on green competitive advantage of manufacturing firms in Ghana.

The framework of this study provides to managers of manufacturing firms, a superior green strategy that is unique, valuable and non-substitutable with the capable to provide green competitive edge to firms in a turbulent sustainability-driven market.

Through the lens of the NRBV theory, this study provided a firstly knowledge on the crucial role of eco-innovation speed and quality in driving firms’ green competitive advantage within a post-covid emerging market.

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade Exchange for Auto Parts procurement by GM, Ford, Daimler‐Chrysler and Renault‐Nissan. Provides many case studies with regards to the adoption of technology and describes seven chief technology officer characteristics. Discusses common errors when companies invest in technology and considers the probabilities of success. Provides 175 questions and answers to reinforce the concepts introduced. States that this substantial journal is aimed primarily at the present and potential chief technology officer to assist their survival and success in national and international markets.

The Chief Financial Officer (CFO), despite being a critical organization member responsible for ensuring quality of financial reporting, audit and compliance, is under-researched. Grouped as a member of top management teams (TMS) in studies, factors influencing decision making in this group rely on static measures of characteristics without regard for dynamic and longitudinal influences of career trajectories and industry occupational group memberships. The relationship between the high-tech industry as a site of notable reported internal control (IC) weakness and influences on CFOs requires closer examination. The paper aims to discuss these issues.

The study draws together the upper echelons theory and occupational communities (OCs) to explore the impact of shared values and behavioral norms from different sources on executive decision making. Internal and external sources of OC are proposed and their influence on activities with respect to corporate IC is tested. The sample of 1,573 firm/year observations includes high-tech firms listed on major US exchanges was developed using data from five distinct databases. Executives’ biographic information was manually collected.

Results indicate that senior financial executives belong not only to their firm and its culture but also to OCs that extend beyond the firm. Membership in professional credential granting occupational groups has less impact on effective IC than experience in the high-tech industry. In combination, multiple OCs show evidence of compound and counteracting effects on IC. The OC that arises in the high-tech industry makes a measurable positive difference in the quality of IC in sample firms, in contrast with the OC among credentialed accounting and financial professionals.

This quantitative study of OC reveals the differential impact of different sources of OC and contributes to the literature on TMS a new framework for examining decision making. OC is typically studied through qualitative methods and, thus, potential exists to further explore the specific nature and dynamics of the OCs identified in this study.

The study highlights the role of broad affiliations and networks among senior financial executives which may have bearing on their ability to effectively manage IC. The role of these networks may also partially explain instances of CFO failure and thus dismissal. Knowledge of the role of OC may help boards of directors in the selection and promotion of senior financial officers of the firm.

The paper offers a different perspective on professional accounting expertise in one specific industry where incidence of IC weakness is high relative to other industries. Study results expand recent research on TMS to include sociological impacts of cohort groups. Despite generally weaker IC in the high-tech sector, this study demonstrates the value of exploring group membership within the industry as an important predictor of behavior. The result is a new perspective to CFO decision making which illustrates the relevance of OCs among upper echelons. The implications of findings for CFO recruitment and promotion are borne out in recent instances of senior financial executive failure in the sector.

As an alternative to the standard p and np charts along with their various modifications, beta control charts are used in the literature for monitoring proportion data. These charts in general use average of proportions to set up the control limits assuming in-control parameters known. The purpose of the paper is to propose a control chart for detecting shift(s) in the percentiles of a beta distributed process monitoring scheme when in-control parameters are unknown. Such situations arise when specific percentile of proportion of conforming or non-conforming units is the quality parameter of interest.

Parametric bootstrap method is used to develop the control chart for monitoring percentiles of a beta distributed process when in-control parameters are unknown. Extensive Monte Carlo simulations are conducted for various combinations of percentiles, false-alarm rates and sample sizes to evaluate the in-control performance of the proposed bootstrap control charts in terms of average run lengths (ARL). The out-of-control behavior and performance of the proposed bootstrap percentile chart is thoroughly investigated for several choices of shifts in the parameters of beta distribution. The proposed chart is finally applied to two skewed data sets for illustration.

The simulated values of in-control ARL are found to be closer to the theoretical results implying that the proposed chart for percentiles performs well with both positively and negatively skewed data. Also, the out-of-control ARL values for the percentiles decrease sharply with both downward and upward small, medium and large shifts in the parameters. The phenomenon indicates that the chart is effective in detecting shifts in the parameters. However, the speed of detection of shifts varies depending on the type of shift, the parameters and the percentile being considered. The proposed chart is found to be effective in comparison to the Shewhart-type chart and bootstrap-based unit gamma chart.

It is worthwhile to mention that the beta control charts proposed in the literature use average of proportion to set up the control limits. However, in practice, specific percentile of proportion of conforming or non-conforming items should be more useful as the quality parameter of interest than average. To the best of our knowledge, no research addresses beta control chart for percentiles of proportion in the literature. Moreover, the proposed control chart assumes in-control parameters to be unknown, and hence captures additional variability introduced into the monitoring scheme through parameter estimation. In this sense, the proposed chart is original and unique.