This paper investigates robust fault diagnosis strategies for the auto-balancing of an ergonomically designed two-wheeled cart which is inherently unstable and has a non-minimum phase. To endow the rider with robust stabilization, the normalized coprime factorization for steering is employed for allowing maximum model uncertainties and the driving orientation is achieved with an electronic differential steering control. A model-based fault-detection filter is designed to detect sensor faults. The observer gain obtained by solving an algebraic Riccati equation in the normalized coprime factorization approach offers some design convenience associated with the fault diagnosis filter. In order to promptly alert the rider for safety purposes in the event of a malfunction, the decision-making process to identify a critical failure is also investigated. Finally, evaluation examples are given to illustrate the performance of the proposed robust fault diagnosis strategies.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Human-Computer Interaction
- Hardware and Architecture
- Computer Science Applications