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The purpose of this paper is to introduce a high load capacity coaxial couple wheeled robot (CCWR) and investigate a simple structure but effective fuzzy equilibrium controller based on (Takagi‐Sugeno) T‐S for balance control in wide‐angle range.

By selecting the robot inclination angle and angular rate as input variables and the DC motors' rotation speed as output variables, a T‐S fuzzy controller (FC) is established.

Simplified robot dynamic equilibrium equations are feasible; the robot balance in wide‐angle range could be controlled by the T‐S FC. Despite the existence of small vibrations near the equilibrium position, the system can return to equilibrium within 3 s, showing strong robustness.

The robot can achieve self‐balance and pivot around, moreover, it provides a new way for balance control of CCWR in wide‐angle range. And at the same time, the robot can achieve its work in semi‐autonomous and tele‐operated mode.

The paper shows that designing the controller based on static analysis is feasible; simple structure T‐S fuzzy control way is introduced to balance control for CCWR in a wide angle scale; the development target is to provide a kind of robot platform for testing control algorithms or a personal transporter, and the project is supported by the High Technology Research and Development Program of China.

Under the big data background, there are many influencing factors for investors of new energy vehicles (NEV), and government subsidies promote the sustainable development of the new energy vehicle industry. Therefore, the purpose of the study is to provide solutions for the sustainable development of NEV.

The sustainable marketing strategy of NEV in China is put forward. This paper first analyzes the subsidy policy effect of NEV under the background of big data. It then establishes the online optimal leasing strategy under multiple strategy choices and the online leasing strategy of multiple vehicles under the inflation market.

With the fixed cost of NEV in each lease period, the optimal competition ratio of online decision-makers will continue to decrease with the increase of the difference between prepaid funds and government subsidies. In the decision-making of renting and purchasing multiple vehicles, the general strategy competition ratio is 2.922, while the optimal competition ratio of the online renting and purchasing strategy proposed by the research is 2.723.

The research is limited by the limited data and information collected, so the optimal decision-making model has some limitations. The authors need to find more representative data to optimize the model.

As an emerging industry, NEV have developed rapidly in recent years. Based on the online algorithm and competitive ratio theory, this paper solves the decision-making problem of operators and gives the optimal strategy to promote the green development of the new energy vehicle industry.

This paper proposes the optimal strategy for online investors of new energy vehicle operators by combining online algorithm and competitive ratio theory. The numerical analysis results of the optimal online model under multi strategy selection show that with the same difference between prepaid funds and government subsidies, the time point will be delayed and the time point will be advanced as the cost of leasing NEV in each period increases.