Thanh Hai Tran

Industrial University of Ho Chi Minh City

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About

Thanh Hai Tran is an emerging researcher specializing in intelligent control systems and robotics, with a particular focus on parallel robotic systems and advanced neural network-based control architectures. Their work addresses a critical challenge in modern robotics: developing sophisticated yet efficient control strategies for parallel robot systems, which offer significant advantages over traditional serial robots in terms of payload capacity, operational speed, and precision — making them invaluable across transportation and manufacturing industries. Tran's most notable contribution involves the development and application of the Modified T2FHC (Type-2 Fuzzy Hybrid Control) algorithm for robotic controllers, demonstrated through a two-link robot system and accumulating 4 citations since its 2023 publication. Building on this foundation, their 2025 work introduces an innovative adaptive single-input tracking controller that ingeniously combines Brain Emotion Learning and Cerebellar Model Articulation Control (CMAC) networks enhanced with wavelet functions — representing a sophisticated fusion of bio-inspired computing paradigms for improved robotic tracking performance. Though early in their research career, Tran's interdisciplinary approach — merging fuzzy logic, neural architectures, and adaptive control theory — positions them as a promising contributor to the next generation of intelligent robotic control systems.