Adaptive Fuzzy Robust Control of a Bionic Mechanical Leg With a High Gain Observer

In this paper, an observer-based adaptive fuzzy robust controller is proposed for trajectory tracking control of a bionic mechanical leg (BML) with unmeasured system states, dynamic uncertainties and external disturbances. A high gain observer (HGO) constructed to estimate the unavailable joint velocities using position feedback signals, while logic (AFLS) employed address lumped uncertainties. The nonlinear then synthesized via backstepping method improve performance. stability closed loop mathematically demonstrated Lyapunov’s theory. It proven that under all closed-loop signals are bounded errors converge small neighborhood origin appropriate design parameters. effectiveness scheme illustrated by simulation studies.