Authors:
Giuseppe Della Penna
1
;
Daniele Magazzeni
1
;
Alberto Tofani
1
;
Benedetto Intrigila
2
;
Igor Melatti
3
and
Enrico Tronci
3
Affiliations:
1
Università di L’Aquila, Italy
;
2
Università di Roma “Tor Vergata”, Italy
;
3
Università di Roma “La Sapienza”, Italy
Keyword(s):
Controller Synthesis, Controller Optimization, Model Checking, Nonlinear Systems.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Fuzzy Control
;
Fuzzy Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Soft Computing
Abstract:
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 controller
s with different degrees of robustness.
(More)