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Adaptive Control for Pneumatic Muscle Systems by Nguyen Thu Ha is a document available to read on EtoBox.
This study presents an adaptive controller utilizing radial basis function neural networks (RBFNN) to improve control performance in pneumatic artificial muscle (PAM) systems. The proposed method addresses the challenges of nonlinearity and hysteresis in PAMs through neural approximation techniques, demonstrating enhanced precision and reliability in experimental tests. The results indicate significant potential for advancements in trajectory tracking control for PAM-based applications, particularly in reha
- Author
- Nguyen Thu Ha
- Language
- EN