Abstract
This paper presents a method for synthesis of control alphabet policies, given continuum descriptions of physical systems and tasks. First, we describe a model predictive control scheme, called switched sequential action control (sSAC), that generates global state-feedback control policies with low computational cost, given a control alphabet. During synthesis, sSAC alphabet policies are directly encoded into finite state machines using a cell subdivision approach. As opposed to existing automata synthesis methods, controller synthesis is based entirely on the original nonlinear system dynamics and thus does not rely on but rather results in a lower-complexity symbolic representation. The method is validated for the cart-pendulum inversion problem and the double-tank system. The approach presents an opportunity for real-time task-oriented control of complex robotic platforms using exclusively sensor data with no online computation involved.
Original language | English (US) |
---|---|
Title of host publication | 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 |
Publisher | IEEE Computer Society |
Pages | 313-320 |
Number of pages | 8 |
ISBN (Electronic) | 9781509024094 |
DOIs | |
State | Published - Nov 14 2016 |
Event | 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 - Fort Worth, United States Duration: Aug 21 2016 → Aug 24 2016 |
Publication series
Name | IEEE International Conference on Automation Science and Engineering |
---|---|
Volume | 2016-November |
ISSN (Print) | 2161-8070 |
ISSN (Electronic) | 2161-8089 |
Other
Other | 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 |
---|---|
Country/Territory | United States |
City | Fort Worth |
Period | 8/21/16 → 8/24/16 |
Funding
This material is based upon work supported by the National Science Foundation under awards CMMI-1200321 and IIS-1426961.
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering