We present a methodology for the synthesis of controllers, which exploits (explicit) model checking techniques. That is, we can cope with the systematic exploration of a very large state space. This methodology can be applied to systems where other approaches fail. In particular, we can consider systems with an highly non-linear dynamics and lacking a uniform mathematical description (model). We can also consider situations where the required control action cannot be specified as a local action, and rather a kind of planning is required. Our methodology individuates first a raw optimal controller, then extends it to obtain a more robust one. A case study is presented which considers the well known truck-trailer obstacle avoidance parking problem, in a parking lot with obstacles on it. The complex non-linear dynamics of the truck-trailer system, within the presence of obstacles, makes the parking problem extremely hard. We show how, by our methodology, we can obtain optimal controllers with different degrees of robustness. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Penna, G. D., Magazzeni, D., Tofani, A., Intrigila, B., Melatti, I., & Tronci, E. (2008). Automated generation of optimal controllers through model checking techniques. In Lecture Notes in Electrical Engineering (Vol. 15, pp. 107–119). https://doi.org/10.1007/978-3-540-79142-3_10
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