CDS 270-2, Spring 2006: Difference between revisions
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{{righttoc}} [[Category:Courses]] [[Category:2005-06 Courses]] | {{righttoc}} [[Category:Courses]] [[Category:2005-06 Courses]] | ||
== Networked Control Systems == | == Networked Control Systems == | ||
Increases in fast and inexpensive computing and communications have | |||
enabled a new generation information-rich control systems that rely on | |||
multi-threaded networked execution, distributed optimization, adaptation | |||
and learning, and contingency management in increasingly sophisticated | |||
ways. This course will describe a framework for building such systems and | |||
lay out some of the challenges to control theory that must be addressed | |||
to enable systematic design and analysis. A driving example is provided | |||
by Alice, an autonomous vehicle that competed in the 2005 DARPA Grand | |||
Challenge. Key features of Alice include a highly sensory-driven | |||
approach to fuse sensor data into speed maps used by real-time | |||
trajectory optimization algorithms, health and contingency management | |||
algorithms to manage failures at the component and system level, and a | |||
multi-threaded, networked control architecture that enables | |||
plug-and-play operations and testing. | |||
== Course Schedule == | == Course Schedule == | ||
Revision as of 00:08, 19 March 2006
Networked Control Systems
Increases in fast and inexpensive computing and communications have enabled a new generation information-rich control systems that rely on multi-threaded networked execution, distributed optimization, adaptation and learning, and contingency management in increasingly sophisticated ways. This course will describe a framework for building such systems and lay out some of the challenges to control theory that must be addressed to enable systematic design and analysis. A driving example is provided by Alice, an autonomous vehicle that competed in the 2005 DARPA Grand Challenge. Key features of Alice include a highly sensory-driven approach to fuse sensor data into speed maps used by real-time trajectory optimization algorithms, health and contingency management algorithms to manage failures at the component and system level, and a multi-threaded, networked control architecture that enables plug-and-play operations and testing.
Course Schedule
| Week | Date | Topic | Reading |
| 1 | Introduction to Networked Control Systems (R. Murray) | ||
| 27 Mar* (M) | No class | ||
| 29 Mar (W) | Course overview, applications and administration | ||
| 31 Mar (F) | Case study: Alice | Cremean et al, 2005 | |
| 2 | Networked embedded systems programming (R. Murray) | ||
| 3 Apr (M) | Message transfer systems: spread | ||
| 5 Apr (W) | Multi-threaded control systems: pthreads | ||
| 7Apr (F) | Alice: adrive, trajFollower | ||
| 3 | Real-time trajectory generation and receding horizon control (TBD) | ||
| 10 Apr (M) | Real-time trajectory generation | ||
| 12 Apr (W) | Receding horizon control | ||
| 14 Apr (F) | Alice: plannerModule | ||
| 4 | State estimation (TBD) | ||
| 17 Apr (M) | Kalman filtering | ||
| 19 Apr (W) | Moving horizon estimation | ||
| 21 Apr* (F) | Alice: astate | ||
| 5 | Packet-based estimation, I (Sinopoli?) | ||
| 24 Apr* (M) | |||
| 26 Apr* (W) | |||
| 28 Apr* (F) | |||
| 6 | Packet-based estimation, II (TBD) | ||
| 1 May* (M) | |||
| 3 May (W) | |||
| 5 May (F) | |||
| 7 | Distributed estimation and control (Gupta?) | ||
| 8 May* (M) | |||
| 10 May* (W) | |||
| 12 May (F) | |||
| 8 | Cooperative control of multi-agent systems | ||
| 15 May (M) | |||
| 17 May* (W) | |||
| 19 May (F) | |||
| 9 | Project Presentations (All) | ||
| 22 May (M) | No class | ||
| 24 May (W) | Project presentations | ||
| 26 May (F) | Project presentations | ||
