This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Nanjing University of Aeronautics and Astronautics. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: Yahui Gao: Innovator in Neural Network-Based Control Methods
Introduction
Yahui Gao is a prominent inventor based in Jiangsu, China. He has made significant contributions to the field of control systems through his innovative approaches. His work primarily focuses on utilizing neural networks to enhance control methods for complex systems.
Latest Patents
Yahui Gao holds a patent for a "Neural network-based NARMA-L2 multivariable control method." This invention discloses a method that derives a NARMA-L2 multivariable control law for nonlinear discrete systems. The approach involves using neural networks to offline identify nonlinear functions within the control law. The design includes a closed-loop control system for a specific type of turbofan engine, incorporating online updates of neural network errors to correct controller parameters. The goal is to minimize the quadratic performance index for the errors of the engine's high-pressure rotating speed and pressure ratio. By combining neural networks with the deduced NARMA-L2 multivariable control law, Gao has developed a dual-variable controller that effectively manages the engine's control variables, including fuel flow and the critical interface area of the exhaust nozzle.
Career Highlights
Yahui Gao is affiliated with Nanjing University of Aeronautics and Astronautics, where he continues to advance his research in control systems. His innovative work has garnered attention in the academic and engineering communities, showcasing the potential of neural networks in practical applications.
Collaborations
Gao has collaborated with notable colleagues, including Jinquan Huang and Jie Tang, who contribute to his research endeavors. Their combined expertise enhances the development of advanced control methods.
Conclusion
Yahui Gao's contributions to neural network-based control methods exemplify the intersection of innovation and technology. His work not only advances theoretical understanding but also has practical implications in engineering applications.