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The optimal control of musculoskeletal model by genetic algorithm

Explore the application of genetic algorithm in optimizing the control of musculoskeletal models. Discuss classical and non-classical optimal control theories, advantages, and disadvantages. Analyze the accuracy and obstructive possibilities with differentiable functions. Investigate parameter optimization algorithms, muscle control methods, and genetic algorithm techniques.

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The optimal control of musculoskeletal model by genetic algorithm

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  1. Presented by SoroushBagheriKoudakani The optimal control of musculoskeletal model by genetic algorithm

  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

  9. Conclusion

  10. THANK YOU FOR YOUR ATTENTION • SoroushBagheriKoudakani

  11. 5 4 2 G 1 Skeletal Model 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

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