DOI: 10.3390/math14203769 ISSN: 2227-7390
Direct Neural Dynamic Programming Adaptive Control of Knee and Ankle Joints in a Simulated Prosthetic Leg Model
Jordan K. Kralev, Tsonyo N. Slavov, Asparuh Markovski, Vladislav SlavovEffective control of prosthetic legs is essential for restoring natural mobility and enhancing the quality of life for amputees. This paper presents a Direct Neural Dynamic Programming (DNDP) algorithm that leverages coupled action and critic neural networks to solve the optimal control problem for prosthetic gait trajectory tracking. By continuously learning and adapting to individual gait patterns, the DNDP action networks generate the control for the knee and ankle joints to reduce the gait tracking error. The proposed approach enables real-time optimization of control strategies without relying on precise system models, offering adaptability to subject-specific dynamics and varying conditions.