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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.

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.

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.

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

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

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

The purpose of this paper is to present a prototype simulation system for driving performance of an electromagnetic unmanned robot applied to automotive test (URAT) to solve that it is difficult and dangerous to online debug control program and to quickly obtain test vehicle dynamic performance.

The driving performance of the electromagnetic URAT can be evaluated by the prototype simulation system. The system can simulate various driving conditions of test vehicles. An improved vehicle longitudinal dynamics model matching to the electromagnetic URAT is established. The proposed model has good real-time, and it is easy to implement. The displacement of throttle mechanical leg, brake mechanical leg, clutch mechanical leg and shift mechanical arm is used for the system input. Test vehicle speed and engine speed are used for the system output, and they are obtained by the computation of the established vehicle longitudinal dynamics model.

Driving conditions simulation test and vehicle emission test are performed using a Ford Focus car. Simulation and experiment results show that the proposed prototype simulation system in the paper can simulate the driving conditions of actual vehicles, and the performance that electromagnetic URAT drives an actual vehicle is evaluated by the simulation system.

Future research will focus on improving the real time of the proposed simulation system.

The autonomous driving performance of electromagnetic URAT can be evaluated by the proposed prototype simulation system.

A prototype simulation system for driving performance of an electromagnetic URAT based on an improved vehicle longitudinal dynamics model is proposed in this paper, so that it can solve the difficulty and danger of online debugging control program, quickly obtaining the test vehicle performance.

One of the major shortcomings in the data process of the traditional wheel force transducers (WFTs) is the theoretical errors of initial value determination. A new method to identify the initial values of the WFT for the solution of this problem is proposed in this paper. The paper aims to discuss these issues.

With this method, the initial values can be obtained by equations which are established based on multiple stops on horizontal road.

The calibration and contrast tests on the MTS calibration platform illustrate the better performance with the new method. Moreover, the real vehicle test confirms the effectiveness in practice.

The test results show that the new method of initial calibration has an advanced performance compared to the traditional one. In addition, it is effective in the brake test with a real vehicle.

This paper investigates the relationship between human capital, economic freedom, governance performance, and economic growth and whether institutional factors such as governance performance and economic freedom mediate the association between human capital and economic growth.

In this study, the authors apply the panel data regression method to verify five hypotheses and check the robustness of the empirical findings from four aspects (chow test, panel unit root test, granger test and generalized method of moments) based on the data covering China, India, Russia, Brazil and South Africa from 2000 to 2018.

After multiple tests with mixed methods, the empirical results show that the relationship between human capital and economic growth is not linear but inverted U-shaped. Furthermore, human capital has a positive effect on economic growth only in a certain period of time, and governance performance positively moderates the effect of human capital on economic growth in BRICS.

First, the impact of human capital on economic growth is not linear but an inverted U-shaped and governance performance moderates the effect of human capital on economic growth in BRICS. The study and research model enhances the authors’ insights on the advantage and challenges of human capital in the future. Second, the proposed multi-methods in the study accurately forecast economic growth which partially solves endogenous problems because of reverse causality.

This study aims to analyze the subsequent investment success of EMNCs after their strategic asset-seeking foreign direct investments (FDIs), while internationalization trajectories of multinational corporations from emerging economies (EMNCs) have been extensively studied, Post-internationalization investment success of EMNCs is defined as extensive technological knowledge access and transfer for knowledge combination. This paper focuses on EMNC explicit knowledge access and transfer.

This study analyzes US patents granted between 2000 and 2014 to leading innovation-oriented EMNCs from China and India as well as to their key competitors from mature industrialized countries (MMNCs). Wilcoxon Rank Sum Test is used to compare the explicit technological knowledge access and transfer patterns of EMNCs and MMNCs. With MMNCs as the benchmark, the comparison allows to imply the patterns and extent of technological knowledge access and transfer of EMNCs.

While subsidiary reverse knowledge transfer is largely missing, EMNCs adopt a parent-centric approach in which the parent directly accesses and transfers explicit knowledge from the external environment of host locations. In doing so, EMNCs at least partially achieve the knowledge access and transfer goals of strategic asset-seeking FDIs.

This study contributes to an in-depth understanding of EMNCs by empirically testing key predictions in extant EMNC literature, namely, the strategic asset-seeking in host locations and the systematic integration of accessed knowledge and resources with home country activities. This study also pioneers the use of the US patent and citation data to empirically study EMNCs.