Ming Yu

Papers

Total Citations

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About

Ming Yu is a leading researcher in robotics and intelligent control systems, with a primary focus on compliant actuation and precision force control. His most influential work, "An Improved PID Controller for the Compliant Constant-Force Actuator Based on BP Neural Network and Smith Predictor" (2021, 30 citations), addresses a critical challenge in robotic contact operations: the nonlinearity and time delay inherent in pneumatic systems. Yu’s major contribution lies in developing a hybrid control strategy that integrates a backpropagation (BP) neural network with a Smith predictor to enhance the performance of traditional PID controllers. This approach significantly improves the stability and accuracy of compliant constant-force actuators, which are essential for delicate tasks such as assembly, polishing, and human-robot interaction. By tackling the limitations of conventional methods, Yu’s work has advanced the practical deployment of robots in industrial and service applications. His research demonstrates a strong interdisciplinary impact, bridging control theory, neural networks, and mechatronics. With a growing citation record, Ming Yu is recognized for his innovative solutions to complex actuation problems, making him a notable figure in the field of intelligent robotic systems.