Research Interests

My interests include artificial intelligence and its applications to nonlinear adaptive control, system identification, and managing structure damage. I have been studying the sliding mode control and fuzzy theory. Controllers for a class of nonlinear control systems subjected to uncertainty and disturbance were proposed. They are combinations of adaptive fuzzy sliding mode controllers and compensators including fuzzy-based compensators. I have been also studying Artificial Neural Networks (ANN), Fuzzy Logic (FL), Wavelet Transform (WT), and their applications. I proposed new algorithms for training of ANN, building adaptive neuro-fuzzy inference systems (ANFIS), and solutions for wavelet quantification analysis. Based on these, identifying systems and establishing intelligent controllers for smart structures and systems such as semi-active magnetorheological (MR) vehicle suspensions were presented. Besides, I presented solutions for combination of wavelet quantification and ANN, ANFIS to identify and predict structure damages.

Topic 1

Synthesizing Adaptive Neuro-fuzzy Inference System (ANFIS) and Its Applications for Online Fault Managing of Bearing, Gear or Gear-box.

Topic 2

Establishing Intelligent Structures for Distilling Meaning Features from Big Data and Their Applications to Identifying and Predicting Damage of Mechanical Systems.

Topic 3

Unstructured Method for Managing Online Health of Train-Car’s Bearing, Gear or Gear-box based on Data-driven models, Big Data via Internet.

Topic 4

Developing Adaptive Nonlinear Control by a Fuzzy-based High-order Compensator for Uncertainty and Disturbance.

Topic 5

Sliding Control of Semi-active Railway Suspension Systems Enhanced by Fuzzy-based Compensator for Time Delay.

Topic 6

ANFIS-based Sliding Control of Active Railway Suspension System Subjected to Uncertainties and Disturbances.