The optimal control of musculoskeletal model by genetic algorithm Presented by Soroush Bagheri Koudakani

Introduction Human Movement Modeling The optimal control theory Classical Non-classical Advantage & Disadvantage Continuation & Differentiable function Obstructive possibility Accuracy

Introduction Parameter optimization algorithm (Pandy 1992) Computed Muscle Control (CMC) PD controller * Genetic Algorithm

Method Musculoskeletal model Skeletal model Constrain Muscles model Excitation to Activation

Muscle Excitation Generator Genetic Algorithm Chromosome Population Selection Mutation

Vertical jump simulation

Result The validity of muscle excitation algorithm After 26 Iterations 

Result Iteration Height of COM (Cm) 60 98.047 450 101.016 533 121.679

Conclusion

THANK YOU FOR YOUR ATTENTION Soroush Bagheri Koudakani

Skeletal Model 1 : Calcaneus 2 : Talus 3 : Knee 4 : Hip 5 : Pelvis 5 4 G 1 2 4 5 3 1 : Calcaneus 2 : Talus 3 : Knee 4 : Hip 5 : Pelvis

Contrain Foot-Ground Anderson 1999

Muscle model Thanlen 2003

Moment Arm

Excitation - Activation Zajac1989 Thalen2003