• Energy Research
• 9. Industry and infrastructure close
• CN close
• Transport Research close
• Energy Research close

Successful catch-up is an important channel to achieve sustainable development for emerging economies; however, it is a great challenge to catch up in complex products and systems (CoPS). Studies show limited evidence on how successful catch-up occurred in CoPS for emerging economies. This study holds the view that CoPS catch-up means a narrower gap in the innovation ecosystem between latecomers and leaders. This study disentangles the CoPS innovation ecosystem and uses China’s high-speed railway (HSR) as a longitudinal case with abundant data to explore how successful catch-up in CoPS is achieved. The results show that the CoPS innovation ecosystem presents a dynamic evolution in the technology innovation subsystem, the value creation subsystem, and the habitat. Four types of forces from the innovation ecosystem mix together to drive CoPS catch-up. Finally, this study proposes a CoPS catch-up process model following the basic logic of start point, activities, and performance, and CoPS industrial standards are used to measure CoPS catch-up performance. The study on CoPS catch-up from an innovation ecosystem perspective provides new insights and useful implications for governments and entities in CoPS of emerging economies.

<span lang="EN-US">A multi-point model predictive control (MPMPC) is widely used for many applications, including wind energy system (WES), notably enhanced power characteristics and oscillation regulation. In this work, MPMPC is adapted to condense the fatigue load of the WES and improve the lifetime of the turbine assembly. The lifetime examination is carried out by considering the three chief parameters: basic lifetime until failure, short-time damage equivalent loads (DELs), and lifetime DELs. The simulation study is performed for two cases: blade root bending moments and tower top bending. Further, fatigue load examination is demonstrated to analyze the effectiveness of the proposed controller. The observed results show that the lifetime analysis of the wind turbine system displayed more excellent characteristics, i.e., 49.50% greater than MPC. Also, the fatigue load mitigation showed greater magnitude due to the control action of the proposed controller, about 37.38% grander than MPC. Therefore, the attained outcomes exhibit outstanding performance compared with conventional controllers.</span>