Chidentree Treesatayapun
Investigador Titular Robótica y Manufactura Avanzada
Investigador Cinvestav 3C
Categoría en el SNI: Nivel II
Teléfono y extensión: 8444389600/8506
Correo Electrónico: chidentree@cinvestav.edu.mx
Semblanza:
Research fields on adaptive control systems and artificial intelligence, particularly for discrete-time, nonlinear, and uncertain dynamic systems. Emphasis is placed on model-free and data-driven control techniques, like fuzzy rules and quantum-inspired networks, to manage complex dynamics without requiring exact system models. Applications span fields from robotics to healthcare, focusing on adaptive algorithms for cancer drug dosing and policy modeling for COVID-19 interventions. Robust and fault-tolerant control approaches ensure stability and optimal performance, addressing disturbances or faults. Integrating AI, these contributions tackle real-world challenges in dynamic, highly uncertain environments.
Líneas de Investigación:
- Advanced control systems and artificial intelligence applications, particularly in adaptive control.
- Discrete-time systems
- Robotics.
- Dynamic systems.
Laboratorio:
A.I. control and signal processing
Principales Equipos.
Proyectos Representativos Recientes:
- Fuzzy R; Fuzzy Rules Emulated Networks and Estimated Cost Function for Discrete-Time Robotic Control Systems in Contact with the Environment # 84791
- Human support machines: signal conditioning, machine interface and controller based on human knowledge and data driven algorithm # 257253
Publicaciones Representativas Recientes:
- Finite-time adaptive control based on output feedback and auxiliary variables for time-varying parameters and disturbances, C Treesatayapun, Journal of the Franklin Institute 361 (18), 107273.
- Fuzzy Rules Data-Driven Equivalent Model with Multi-gradient Learning for Discrete-Time Nearly Optimal Control, C Treesatayapun, International Journal of Fuzzy Systems, 1-12.
- Dynamic data model and robust controller with high‐frequency component reduction for unknown time‐varying discrete‐time systems, C Treesatayapun, International Journal of Robust and Nonlinear Control 34 (9), 6021-6044.
- Adaptive controller based on quantum computation and coherent superposition fuzzy rules network with unknown nonlinearities, C Treesatayapun, Applied Intelligence, 1-14.
- Discrete-time robust event-triggered actuator fault-tolerant control based on adaptive networks and reinforcement learning, C Treesatayapun,Neural Networks 166, 541-554.