His scientific interests lie mostly in Control theory, Control theory, Fuzzy logic, Fuzzy control system and Control system. Jianqiang Yi has researched Control theory in several fields, including Control engineering and Artificial neural network. His Control theory research is multidisciplinary, relying on both Simulation, Trajectory and Motion control.
His work on Fuzzy set as part of general Fuzzy logic research is often related to Pendulum, thus linking different fields of science. His research integrates issues of Defuzzification and Inverted pendulum in his study of Fuzzy control system. His Control system research includes themes of Overshoot, Exponential stability, Feedforward neural network and Variable sampling.
His primary areas of study are Control theory, Control theory, Fuzzy logic, Control engineering and Fuzzy control system. His studies in Control system, Nonlinear system, Adaptive control, Lyapunov function and Sliding mode control are all subfields of Control theory research. His work carried out in the field of Control theory brings together such families of science as Artificial neural network and Trajectory.
Jianqiang Yi combines subjects such as Mathematical optimization and Interval with his study of Fuzzy logic. His Control engineering research integrates issues from Mobile manipulator, Aerodynamics, Control, Vehicle dynamics and Robustness. His work on Adaptive neuro fuzzy inference system is typically connected to Pendulum as part of general Fuzzy control system study, connecting several disciplines of science.
Jianqiang Yi focuses on Control theory, Adaptive control, Lyapunov function, Fuzzy logic and Control theory. His Control theory study frequently links to adjacent areas such as Hypersonic speed. His studies in Adaptive control integrate themes in fields like Artificial neural network and Tracking.
His Lyapunov function study also includes
Jianqiang Yi mainly focuses on Control theory, Fuzzy logic, Lyapunov function, Vehicle dynamics and Backstepping. His Control theory study focuses on Control theory in particular. Jianqiang Yi interconnects Tracking and Hypersonic vehicle in the investigation of issues within Control theory.
His biological study spans a wide range of topics, including Algorithm design, Mathematical optimization and Multivariable calculus. His Aerodynamics research focuses on subjects like Control system, which are linked to Disturbance observer and Robustness. The concepts of his Parametric statistics study are interwoven with issues in Interval and Nonlinear system.
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Adaptive sliding mode fuzzy control for a two-dimensional overhead crane
Diantong Liu;Jianqiang Yi;Dongbin Zhao;Wei Wang.
A computed torque controller for uncertain robotic manipulator systems: Fuzzy approach
Zuoshi Song;Jianqiang Yi;Dongbin Zhao;Xinchun Li.
Fuzzy Sets and Systems (2005)
BP neural network prediction-based variable-period sampling approach for networked control systems
Jianqiang Yi;Qian Wang;Dongbin Zhao;John T. Wen.
Applied Mathematics and Computation (2007)
Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach
Dong Xu;Dongbin Zhao;Jianqiang Yi;Xiangmin Tan.
systems man and cybernetics (2009)
Building Energy Consumption Prediction: An Extreme Deep Learning Approach
Chengdong Li;Zixiang Ding;Dongbin Zhao;Jianqiang Yi.
A Class of Adaptive Extended State Observers for Nonlinear Disturbed Systems
Zhiqiang Pu;Ruyi Yuan;Jianqiang Yi;Xiangmin Tan.
IEEE Transactions on Industrial Electronics (2015)
Neural network control for a semi-active vehicle suspension with a magnetorheological damper
D. L. Guo;H. Y. Hu;J. Q. Yi.
Journal of Vibration and Control (2004)
Anti-swing and positioning control of overhead traveling crane
Jianqiang Yi;Naoyoshi Yubazaki;Kaoru Hirota.
Information Sciences (2003)
Stabilization fuzzy control of inverted pendulum systems
Jianqiang Yi;Naoyoshi Yubazaki.
Artificial Intelligence in Engineering (2000)
A new fuzzy controller for stabilization of parallel-type double inverted pendulum system
Jianqiang Yi;Naoyoshi Yubazaki;Kaoru Hirota.
Fuzzy Sets and Systems (2002)
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