Szemináriumok

Adaptive Linear Multistep Methods - Designing Automatic Step Size Control for Multistep Methods

Időpont: 
2019. 04. 04. 10:15
Hely: 
H306
Előadó: 
Gustaf Söderlind

In a k-step adaptive linear multistep methods the coefficients depend on the k-1 most recent step size ratios. In a similar way, both the actual and the estimated local error will depend on these step ratios. The classical error model has been the asymptotic model, $r = ch^{p+1}y^{(p+1)}(t)$, based on the constant step size analysis, where all past step sizes simultaneously go to zero. This does not reflect actual computations with multistep methods, where step size control only affects future steps, not the the previous accepted steps. In variable step size implementations, therefore, even in the asymptotic regime, the error model must include the dependence on previous step sizes and step ratios. In this talk we develop dynamic asymptotic models for variable step size computations, and analyze a few new step size controllers accounting for the dynamics in the error model, while keeping the local error near a prescribed tolerance.

Modelling human balancing tasks

Időpont: 
2019. 03. 28. 10:15
Hely: 
H306
Előadó: 
Insperger Tamás (BME, Műszaki Mechanikai Tanszék)

Human balancing tasks are modelled by differential equations and are compared to experimental observations. First, the classical inverted pendulum model is revisited with respect to stabilizability. Namely, the relation between the reaction time delay and the shortest pendulum length (critical length) of the stick is derived and is demonstrated experimentally. Conclusions are drawn related to human tests, such as stick balancing on the fingertip, balancing a linearly driven inverted pendulum and virtual stick balancing.Second, the ball and beam balancing is considered, where the task is to stabilize a rolling ball at the mid-point of a beam by manipulating the angular position of the beam. Assuming a delayed proportional-derivative feedback mechanism, the governing equation is delay-differential equation. Performance of the control system is analyzed in terms of overshoot and settling time. Experiments over 5-days trials shows that control parameters are tuned to the optimal point associated with minimal overshoot and the shortest settling time. Finally, some further balancing tasks are briefly demonstrated and discussed.

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