2018 - Richard E. Bellman Control Heritage Award
2010 - Fellow of the International Federation of Automatic Control (IFAC)
2002 - Rufus Oldenburger Medal, The American Society of Mechanical Engineers
1997 - Charles Russ Richards Memorial Award, The American Society of Mechanical Engineers
1989 - Fellow of the American Society of Mechanical Engineers
His main research concerns Control theory, Control engineering, Control theory, Control system and Adaptive control. As part of his studies on Control theory, Masayoshi Tomizuka often connects relevant subjects like Motion control. The various areas that Masayoshi Tomizuka examines in his Control engineering study include Digital control, Robot, Trajectory and Automatic control.
His Control theory course of study focuses on Stability and Convergence. His Control system research is multidisciplinary, incorporating elements of Servomotor, Open-loop controller, Machine tool, Servomechanism and PID controller. His work on Backstepping as part of general Adaptive control study is frequently linked to Parametric statistics, therefore connecting diverse disciplines of science.
The scientist’s investigation covers issues in Control theory, Control engineering, Control theory, Control system and Artificial intelligence. His research ties Motion control and Control theory together. His research integrates issues of Trajectory, Control, Actuator, Robot and Robustness in his study of Control engineering.
As part of one scientific family, Masayoshi Tomizuka deals mainly with the area of Actuator, narrowing it down to issues related to the Torque, and often Simulation. His Control theory research is multidisciplinary, relying on both Stability, Tracking and Digital control. His studies in Artificial intelligence integrate themes in fields like Machine learning and Computer vision.
His primary areas of investigation include Artificial intelligence, Machine learning, Control theory, Robot and Trajectory. His work in Artificial intelligence tackles topics such as Computer vision which are related to areas like GRASP and Robustness. Control theory is closely attributed to Tracking in his work.
His Robot study combines topics in areas such as Control engineering, Task and Task. His work deals with themes such as Work, Vehicle dynamics and Automation, which intersect with Trajectory. He interconnects Stability, Control system and Motion control in the investigation of issues within Control theory.
His primary areas of study are Artificial intelligence, Machine learning, Trajectory, Probabilistic logic and Artificial neural network. His Machine learning study combines topics in areas such as Roundabout, Motion and Representation. His Trajectory study also includes
His Probabilistic logic study also includes fields such as
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Zero Phase Error Tracking Algorithm for Digital Control
Journal of Dynamic Systems Measurement and Control-transactions of The Asme (1987)
Fuzzy gain scheduling of PID controllers
Zhen-Yu Zhao;M. Tomizuka;S. Isaka.
systems man and cybernetics (1993)
Automated vehicle control developments in the PATH program
S.E. Shladover;C.A. Desoer;J.K. Hedrick;M. Tomizuka.
IEEE Transactions on Vehicular Technology (1991)
Analysis and Synthesis of Discrete-Time Repetitive Controllers
Masayoshi Tomizuka;Tsu-Chin Tsao;Kok-Kia Chew.
Journal of Dynamic Systems Measurement and Control-transactions of The Asme (1989)
Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form
Bin Yao;Masayoshi Tomizuka.
Robust motion controller design for high-accuracy positioning systems
Ho Seong Lee;M. Tomizuka.
IEEE Transactions on Industrial Electronics (1996)
Control issues in automated highway systems
J.K. Hedrick;M. Tomizuka;P. Varaiya.
IEEE Control Systems Magazine (1994)
Digital control of repetitive errors in disk drive systems
K.K. Chew;M. Tomizuka.
IEEE Control Systems Magazine (1990)
Control of Rotary Series Elastic Actuator for Ideal Force-Mode Actuation in Human–Robot Interaction Applications
Kyoungchul Kong;Joonbum Bae;M. Tomizuka.
IEEE-ASME Transactions on Mechatronics (2009)
Adaptive robust control of MIMO nonlinear systems in semi-strict feedback forms
Bin Yao;Masayoshi Tomizuka.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: