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

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

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

4. Method Musculoskeletal model Skeletal model Constrain Muscles model
Excitation to Activation

5. Muscle Excitation Generator
Genetic Algorithm
Chromosome
Population
Selection
Mutation

6. Vertical jump simulation

7. Result The validity of muscle excitation algorithm
After 26 Iterations 

8. Result
Iteration
Height of COM (Cm) 60
98.047
450
533

9. Conclusion

10. THANK YOU FOR YOUR ATTENTION
Soroush Bagheri Koudakani

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

12. Contrain
Foot-Ground
Anderson 1999

13. Muscle model
Thanlen 2003

14. Moment Arm

15. Excitation - Activation
Zajac1989
Thalen2003