CDS 270-2, Spring 2006: Difference between revisions
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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. Two examples will be used to illustrate the results and to serve as testbeds for course projects: [[Alice]], an autonomous vehicle that competed in the 2005 DARPA Grand | 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. Two examples will be used to illustrate the results and to serve as testbeds for course projects: [[Alice]], an autonomous vehicle that competed in the 2005 DARPA Grand | ||
Challenge and [[RoboFlag]], a robotic version of capture the flag. Key features of these systems include highly sensory-driven, information rich feedback systems, higher levels of decision making for goal and contingency management, and multi-threaded, networked control architectures. | Challenge and [[RoboFlag]], a robotic version of capture the flag. Key features of these systems include highly sensory-driven, information rich feedback systems, higher levels of decision making for goal and contingency management, and multi-threaded, networked control architectures. | ||
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* Graduate instructors: Vijay Gupta, Zhipu Jin, Ling Shi, Demetri Spanos | * Graduate instructors: Vijay Gupta, Zhipu Jin, Ling Shi, Demetri Spanos | ||
* Lectures: MWF 2-3 pm, 125 Steele | * Lectures: MWF 2-3 pm, 125 Steele | ||
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* [http://listserv.cds.caltech.edu/mailman/listinfo/cds270 Course mailing list] | * [http://listserv.cds.caltech.edu/mailman/listinfo/cds270 Course mailing list] | ||
* [[CDS 270: Information for Lecturers|Information for lecturers]] | * [[CDS 270: Information for Lecturers|Information for lecturers]] | ||
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Revision as of 21:52, 25 March 2006
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Networked Control Systems |
| Spring 2006 |
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. Two examples will be used to illustrate the results and to serve as testbeds for course projects: Alice, an autonomous vehicle that competed in the 2005 DARPA Grand Challenge and RoboFlag, a robotic version of capture the flag. Key features of these systems include highly sensory-driven, information rich feedback systems, higher levels of decision making for goal and contingency management, and multi-threaded, networked control architectures.
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Course Schedule
| Week | Date | Topic | Reading |
| 1 | Introduction to Networked Control Systems (R. Murray) | ||
| 27 Mar (M) | Course overview, applications and administration | Syllabus, NCS: Introduction | |
| 29 Mar (W) | Case study: Alice | Alice: Introduction, Cremean et al, 2005 | |
| Networked embedded systems programming (R. Murray) | |||
| 31 Mar (F) | Message transfer systems: spread | NCS: Message Transfer Systems | |
| 2 | 3 Apr (M) | Multi-threaded control systems: pthreads | NCS: Multi-Threaded Control Systems |
| 5 Apr (W) | Alice: adrive, trajFollower | Alice: Vehicle Control | |
| 7 Apr* (F) | No class | ||
| 3 | Real-time trajectory generation and receding horizon control (R. Murray) | ||
| 10 Apr (M) | Real-time trajectory generation | ||
| 12 Apr* (W) | Receding horizon control (T. Keviczky?) | ||
| 14 Apr (F) | Alice: plannerModule | ||
| 4 | State estimation (H. Sandberg) | ||
| 17 Apr (M) | Kalman filtering | ||
| 19 Apr (W) | Moving horizon estimation | ||
| 21 Apr* (F) | Alice: road estimation (Lars) | ||
| 5 | Packet-based estimation and control, I (B. Sinopoli) | ||
| 24 Apr* (M) | |||
| 26 Apr* (W) | |||
| 28 Apr* (F) | |||
| 6 | Packet-based estimation and control, II (L. Shi?, Y. Mostofi) | ||
| 1 May* (M) | |||
| 3 May (W) | |||
| 5 May (F) | |||
| 7 | Distributed estimation and control (V. Gupta) | ||
| 8 May* (M) | |||
| 10 May* (W) | |||
| 12 May (F) | |||
| 8 | Cooperative control of multi-agent systems (Z. Jin?, T. Keviczky) | ||
| 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 | ||
Course Administration
This course is a special topics course in which advanced students will prepare and present much of the lecture material. There is no required homework and no midterm or final exam. Course grades will be based on a course project.
Course Project
All students in the course will demonstrate their knowledge of the material by implementing a networked control system algorithm. At the present time, two testbeds are available for implementation:
