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About

Guiqian Qin is a leading researcher in advanced robotics control, specializing in the modeling and precision control of redundantly actuated parallel robots. Her work focuses on the complex dynamics of multi-degree-of-freedom systems, particularly the 5-DOF 6PUS-UPU parallel robot, where she has pioneered novel force/position control schemes. Qin’s major contributions include the development of a model predictive control (MPC) algorithm that integrates force and position control to enhance stability and accuracy in redundant actuation systems. She has also advanced fuzzy identification and delay compensation techniques, using Takagi-Sugeno (T–S) fuzzy models to predict driving forces based on platform pose, significantly improving real-time control performance. Her most cited work, “The study of model predictive control algorithm based on the force/position control scheme of the 5-DOF redundant actuation parallel robot” (2016), has garnered 46 citations, reflecting its impact on the field. Qin’s innovative hybrid algorithms—combining MPC with PID and fuzzy logic—address traditional control limitations, offering robust solutions for industrial robotics. Her research is essential for engineers developing high-precision, redundant manipulators, and her publications continue to influence modern parallel robot control strategies.