Print Email Facebook Twitter Intelligent control systems Title Intelligent control systems: Learning, interpreting, verification Author Lin, Q. (TU Delft Cyber Security) Contributor Verwer, S.E. (copromotor) van den Berg, Jan (promotor) Degree granting institution Delft University of Technology Date 2019-09-05 Abstract Automatic control is a technique about designing control devices for controlling ma- chinery processes without human intervention. However, devising controllers using conventional control theory requires first principle design on the basis of the full under- standing of the environment and the plant, which is infeasible for complex control tasks such as driving in highly uncertain traffic environment. Intelligent control offers new op- portunities about deriving the control policy of human beings by mimicking our control behaviors from demonstrations. In this thesis, we focus on intelligent control techniques from two aspects: (1) how to learn control policy from supervisors with the available demonstration data; (2) how to verify the controller learned from data will safely control the process. Subject intelligent controlhybrid automata learningsafety verification To reference this document use: https://doi.org/10.4233/uuid:7b17a968-1414-4b84-bbf3-9a0c1197e1fd Part of collection Institutional Repository Document type doctoral thesis Rights © 2019 Q. Lin Files PDF phd_thesis_proof.pdf 6.14 MB Close viewer /islandora/object/uuid:7b17a968-1414-4b84-bbf3-9a0c1197e1fd/datastream/OBJ/view