Open access
Date
2019Type
- Conference Paper
Abstract
While Approximate Dynamic Programming has successfully been used in many applications involving discrete states and inputs such as playing the games of Tetris or chess, it has not been used in many continuous state and input space applications. In this paper, we combine Approximate Dynamic Programming techniques and apply them to the continuous, non-linear and high dimensional dynamics of a quadcopter vehicle. We use a polynomial approximation of the dynamics and sum-of-squares programming techniques to compute a family of polynomial value function approximations for different tuning parameters. The resulting approximations to the optimal value function are combined in a point-wise maximum approach, which is used to compute the online policy. The success of the method is demonstrated in both simulations and experiments on a quadcopter. The control performance is compared to a linear time-varying Model Predictive Controller. The two methods are then combined to keep the computational benefits of a short horizon MPC and the long term performance benefits of the Approximate Dynamic Programming value function as the terminal cost. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000363979Publication status
publishedExternal links
Book title
Proceedings of the 18th European Control Conference (ECC 2019)Pages / Article No.
Publisher
IEEEEvent
Organisational unit
08814 - Smith, Roy (Tit.-Prof.)
03751 - Lygeros, John / Lygeros, John
Notes
Publisher miscounted conference number in the book title, is is actually the 17th conference.More
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