Feng Lu

Title: Innovations of Feng Lu in Neural Network-Based Control Methods.

Introduction

Feng Lu is an accomplished inventor based in Jiangsu, China. He has made significant contributions to the field of control systems, particularly through his innovative use of neural networks. His work focuses on enhancing the performance of multivariable control methods, which are crucial in various engineering applications.

Latest Patents

Feng Lu 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 utilizes neural networks to offline identify nonlinear functions within the control law. The design includes a closed-loop control system specifically for turbofan engines, incorporating online updates of neural network errors to correct controller parameters. The goal is to minimize the quadratic performance index for the errors related to the engine's high-pressure rotating speed and pressure ratio. By combining neural networks with the deduced NARMA-L2 multivariable control law, Feng Lu has successfully designed a dual-variable controller that manages the engine's control variables, including fuel flow and the critical interface area of the exhaust nozzle. He has 1 patent to his name.

Career Highlights

Feng Lu is affiliated with Nanjing University of Aeronautics and Astronautics, where he contributes to research and development in aeronautics and astronautics. His work has been instrumental in advancing control methods that enhance the efficiency and reliability of aerospace systems.

Collaborations

Feng Lu has collaborated with notable colleagues, including Jinquan Huang and Jie Tang. Their joint efforts have furthered research in control systems and neural network applications.

Conclusion

Feng Lu's innovative contributions to neural network-based control methods exemplify the intersection of advanced technology and practical engineering solutions. His work continues to influence the field of control systems, particularly in aerospace applications.