2023 - Research.com Electronics and Electrical Engineering in Singapore Leader Award
2022 - Research.com Electronics and Electrical Engineering in Singapore Leader Award
His primary areas of investigation include Control theory, Nonlinear system, Control engineering, Adaptive control and Control theory. Adaptive system is closely connected to Artificial neural network in his research, which is encompassed under the umbrella topic of Control theory. His Nonlinear system research is multidisciplinary, incorporating perspectives in Discrete time and continuous time, Bounded function and Fuzzy control system.
His Control engineering course of study focuses on Linear system and Controllability, Reachability, Observability and Process control. His work in Adaptive control tackles topics such as Compensation which are related to areas like Trajectory. His study in Control theory is interdisciplinary in nature, drawing from both Iterative learning control, Dead time and Pendulum.
Control theory, Control engineering, Nonlinear system, Control theory and Adaptive control are his primary areas of study. His work on Artificial neural network expands to the thematically related Control theory. The Control engineering study combines topics in areas such as Iterative learning control, Control, Robot, Motion control and Robustness.
His research integrates issues of Discrete time and continuous time, Bounded function and Mathematical optimization in his study of Nonlinear system. His Adaptive control research incorporates themes from Tracking error, Lyapunov function and Adaptive system. The concepts of his Servomechanism study are interwoven with issues in Servo and Actuator.
Tong Heng Lee mainly focuses on Control theory, Mathematical optimization, Control theory, Control engineering and Artificial intelligence. His Control theory research integrates issues from Mechatronics and Impedance control. Tong Heng Lee has included themes like Probabilistic logic, Model predictive control and Nonlinear system in his Mathematical optimization study.
His Control theory study incorporates themes from Stability and Parameterized complexity. His Control engineering research is multidisciplinary, relying on both Automation, Control, Pendulum and Robot control. His research in Artificial intelligence intersects with topics in Detector, Computer vision and Pattern recognition.
Tong Heng Lee mostly deals with Control theory, Trajectory, Control engineering, Mathematical optimization and Control theory. His Control theory research includes elements of Measure and Bearing. His Control engineering study combines topics from a wide range of disciplines, such as Actuator, Flight test, Avionics and Pendulum.
He combines subjects such as Probabilistic logic, Model predictive control and Nonlinear system with his study of Mathematical optimization. In his research, Applied mathematics is intimately related to Gauss–Seidel method, which falls under the overarching field of Control theory. As a part of the same scientific family, Tong Heng Lee mostly works in the field of Adaptive control, focusing on PID controller and, on occasion, Spacecraft.
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Stable Adaptive Neural Network Control
S. S. Ge;C. C. Hang;T. H. Lee;Tao Zhang.
(2001)
Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function
Beibei Ren;Shuzhi Sam Ge;Keng Peng Tee;Tong Heng Lee.
IEEE Transactions on Neural Networks (2010)
Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients
S.S. Ge;Fan Hong;Tong Heng Lee.
systems man and cybernetics (2004)
Composite nonlinear feedback control for linear systems with input saturation: theory and an application
B.M. Chen;T.H. Lee;Kemao Peng;V. Venkataramanan.
IEEE Transactions on Automatic Control (2003)
Controllability and reachability criteria for switched linear systems
Zhendong Sun;S. S. Ge;T. H. Lee.
Automatica (2002)
Unmanned Rotorcraft Systems
Guowei Cai;Ben M. Chen;Tong Heng Lee.
(2011)
PID tuning for improved performance
Qing-Guo Wang;Tong-Heng Lee;Ho-Wang Fung;Qiang Bi.
IEEE Transactions on Control Systems and Technology (1999)
Evolutionary Algorithms for Multi-Objective Optimization: Performance Assessments and Comparisons
K. C. Tan;T. H. Lee;E. F. Khor.
Artificial Intelligence Review (2002)
Multiobjective Evolutionary Algorithms and Applications
Kay Chen Tan;Tong Heng Lee;k-c-tan;Eik Fun Khor.
(2005)
Adaptive neural network control of nonlinear systems with unknown time delays
S.S. Ge;Fan Hong;Tong Heng Lee.
IEEE Transactions on Automatic Control (2003)
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