EECI09: Optimization-based control - Revision history

Murray: /* Lecture Materials */

2009-03-09T18:41:39Z

Lecture Materials

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	== Lecture Materials ==		== Lecture Materials ==
	* Lecture slides: {{eeci-sp09 pdf\|L2_obc.pdf\|Optimization-based control~~}} programming~~}}		* Lecture slides: {{eeci-sp09 pdf\|L2_obc.pdf\|Optimization-based control}}
	* Background reading: the material in this section is described in more detail in the course notes on [[AMwiki:Supplement: Optimization-Based Control\|Optimization-Based Control]]:		* Background reading: the material in this section is described in more detail in the course notes on [[AMwiki:Supplement: Optimization-Based Control\|Optimization-Based Control]]:
	:{\| width=100%		:{\| width=100%

Murray: /* Lecture Materials */

2009-03-09T18:41:24Z

Lecture Materials

← Older revision		Revision as of 18:41, 9 March 2009
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	== Lecture Materials ==		== Lecture Materials ==
	* Lecture slides: {{eeci-sp09 pdf\|L2_obc.pdf\|Optimization-based control}} ~~and {{eeci-sp09 pdf\|L2_embedded.pdf\|Embedded systems~~ programming}}		* Lecture slides: {{eeci-sp09 pdf\|L2_obc.pdf\|Optimization-based control}} programming}}
	* Background reading: the material in this section is described in more detail in the course notes on [[AMwiki:Supplement: Optimization-Based Control\|Optimization-Based Control]]:		* Background reading: the material in this section is described in more detail in the course notes on [[AMwiki:Supplement: Optimization-Based Control\|Optimization-Based Control]]:
	:{\| width=100%		:{\| width=100%

Murray: EECI09: Optimization-based control and embedded programming moved to EECI09: Optimization-based control

2009-03-09T18:41:06Z

EECI09: Optimization-based control and embedded programming moved to EECI09: Optimization-based control

← Older revision		Revision as of 18:41, 9 March 2009
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Murray: /* Lecture Materials */

2009-03-08T00:17:14Z

Lecture Materials

← Older revision		Revision as of 00:17, 8 March 2009
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	* Lecture slides: {{eeci-sp09 pdf\|L2_obc.pdf\|Optimization-based control}} and {{eeci-sp09 pdf\|L2_embedded.pdf\|Embedded systems programming}}		* Lecture slides: {{eeci-sp09 pdf\|L2_obc.pdf\|Optimization-based control}} and {{eeci-sp09 pdf\|L2_embedded.pdf\|Embedded systems programming}}
	* Background reading: the material in this section is described in more detail in the course notes on [[AMwiki:Supplement: Optimization-Based Control\|Optimization-Based Control]]:		* Background reading: the material in this section is described in more detail in the course notes on [[AMwiki:Supplement: Optimization-Based Control\|Optimization-Based Control]]:
	** Chapter 1: Trajectory Generation and Tracking		:{\| width=100%
	** Chapter 2: Optimal Control		\|-
	** Chapter 3: Receding Horizon Control		\| width=50% \|
	** Chapter 4: Stochastic Systems		* Chapter 1: Trajectory Generation and Tracking
	** Chapter 5: Kalman Filtering		* Chapter 2: Optimal Control
	** Chapter 6: Sensor Fusion		* Chapter 3: Receding Horizon Control
			\| width=50% \|
			* Chapter 4: Stochastic Systems
			* Chapter 5: Kalman Filtering
			* Chapter 6: Sensor Fusion
			\|}

	== Further Reading ==		== Further Reading ==

Murray at 00:16, 8 March 2009

2009-03-08T00:16:25Z

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	== Lecture Materials ==		== Lecture Materials ==
	* Lecture slides: {{eeci-sp09 pdf\|L2_obc.pdf\|Optimization-based control}} and {{eeci-sp09 pdf\|L2_embedded.pdf\|Embedded systems programming}}		* Lecture slides: {{eeci-sp09 pdf\|L2_obc.pdf\|Optimization-based control}} and {{eeci-sp09 pdf\|L2_embedded.pdf\|Embedded systems programming}}
			* Background reading: the material in this section is described in more detail in the course notes on [[AMwiki:Supplement: Optimization-Based Control\|Optimization-Based Control]]:
			** Chapter 1: Trajectory Generation and Tracking
			** Chapter 2: Optimal Control
			** Chapter 3: Receding Horizon Control
			** Chapter 4: Stochastic Systems
			** Chapter 5: Kalman Filtering
			** Chapter 6: Sensor Fusion


	== Further Reading ==		== Further Reading ==

Murray at 00:10, 8 March 2009

2009-03-08T00:10:58Z

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	* Embedded systems programming: we briefly describe some of the software infractructure used to implement modern networked control systems, with a focus on networked and distributed systems. We focus on the use of spread as a specific example of a low-level message transfer subsystem and describe how it can be used in a NCS context. We then describe the Pthreads programming environment, which provides a standardized API for managing process threads.		* Embedded systems programming: we briefly describe some of the software infractructure used to implement modern networked control systems, with a focus on networked and distributed systems. We focus on the use of spread as a specific example of a low-level message transfer subsystem and describe how it can be used in a NCS context. We then describe the Pthreads programming environment, which provides a standardized API for managing process threads.

	This lecture covers a number of important concepts that we will build upon in a very ~~short time, but we~~ assume that students are familiar with at least some of the basic concepts of optimal control and random processes.		This lecture covers a number of important concepts that we will build upon in a very concise manner. We assume that students are familiar with at least some of the basic concepts of optimal control, state estimators and random processes.

	== Lecture Materials ==		== Lecture Materials ==

Murray at 00:10, 8 March 2009

2009-03-08T00:10:22Z

← Older revision		Revision as of 00:10, 8 March 2009
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	* Embedded systems programming: we briefly describe some of the software infractructure used to implement modern networked control systems, with a focus on networked and distributed systems. We focus on the use of spread as a specific example of a low-level message transfer subsystem and describe how it can be used in a NCS context. We then describe the Pthreads programming environment, which provides a standardized API for managing process threads.		* Embedded systems programming: we briefly describe some of the software infractructure used to implement modern networked control systems, with a focus on networked and distributed systems. We focus on the use of spread as a specific example of a low-level message transfer subsystem and describe how it can be used in a NCS context. We then describe the Pthreads programming environment, which provides a standardized API for managing process threads.

	This lecture ~~very briefly summarizes~~ a number of important concepts that we build upon, but we assume that students are familiar with at least some of the basic concepts of optimal control and random processes.		This lecture covers a number of important concepts that we will build upon in a very short time, but we assume that students are familiar with at least some of the basic concepts of optimal control and random processes.

	== Lecture Materials ==		== Lecture Materials ==

Murray at 00:09, 8 March 2009

2009-03-08T00:09:41Z

← Older revision		Revision as of 00:09, 8 March 2009
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	* Embedded systems programming: we briefly describe some of the software infractructure used to implement modern networked control systems, with a focus on networked and distributed systems. We focus on the use of spread as a specific example of a low-level message transfer subsystem and describe how it can be used in a NCS context. We then describe the Pthreads programming environment, which provides a standardized API for managing process threads.		* Embedded systems programming: we briefly describe some of the software infractructure used to implement modern networked control systems, with a focus on networked and distributed systems. We focus on the use of spread as a specific example of a low-level message transfer subsystem and describe how it can be used in a NCS context. We then describe the Pthreads programming environment, which provides a standardized API for managing process threads.

			This lecture very briefly summarizes a number of important concepts that we build upon, but we assume that students are familiar with at least some of the basic concepts of optimal control and random processes.

	== Lecture Materials ==		== Lecture Materials ==

Murray: /* Kalman filtering and state estimation */

2009-03-08T00:08:38Z

Kalman filtering and state estimation

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	=== Kalman filtering and state estimation ===		=== Kalman filtering and state estimation ===
			* <p>[http://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf An Introduction to the Kalman Filter], G. Welch and G. Bishop. A brief introduction to the Kalman filter in discrete time. No proofs are given, but it is a good first read.</p>

			* <p>[http://en.wikipedia.org/wiki/Kalman_filter Wikipedia: Kalman Filter] A webpage that gives a proof and some applications.</p>

			* <p>[http://www.cs.unc.edu/~welch/kalman/kalmanPaper.html A New Approach to Linear Filtering and Prediction Problem], R.E. Kalman. ''Transactions of the ASME'', Series D, 1960. A classical paper. Still very readable. It uses different notation than the lecture, and present a different and more general proof. </p>

			* <p>[http://www.amazon.com/gp/product/0486439380/102-3301256-1504117?v=glance&n=283155 Optimal Filtering], B.D.O Anderson and J.B. Moore. Dover Books on Engineering, 2005. A reissue of a book from 1979. It contains a detailed mathematical presentation of filtering problems and the Kalman filter. A very good book.</p>

	=== Messaging Systems ===		=== Messaging Systems ===

Murray at 00:06, 8 March 2009

2009-03-08T00:06:58Z

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	* Optimization-based control: we describe how real-time optimization can be used to design feedback control algorithms for nonlinear, constrained systems. The receding horizon control (RHC) principle is described and the main ingredients required for its stability are discussed. Efficient numerical methods can then be used to find trajectories that satify the system dynamics and constraints, as well as minimizing a cost function. We concentrate on methods for real-time trajectory generation, and in particular the NTG software package.		* Optimization-based control: we describe how real-time optimization can be used to design feedback control algorithms for nonlinear, constrained systems. The receding horizon control (RHC) principle is described and the main ingredients required for its stability are discussed. Efficient numerical methods can then be used to find trajectories that satify the system dynamics and constraints, as well as minimizing a cost function. We concentrate on methods for real-time trajectory generation, and in particular the NTG software package.

	* Embedded systems programming: we describe some of the software infractructure used to implement ~~moder~~ networked control systems~~. We first discuss "message transfer systems"~~, ~~which is responsible for managing network communications between computers~~ and ~~software modules with the control system~~. We focus on the use of spread as a specific example of a low-level message transfer subsystem and describe how it can be used in a NCS context. We then describe the Pthreads programming environment, which provides a standardized API for managing process threads ~~and mutexes (to resolve data access conflicts)~~.		* State estimation: we briefly summarize the standard formalism for estimation and sensor fusion using Kalman filtering, as well as more recent approaches such as moving horizon estimation (MHE) and particle filters.

			* Embedded systems programming: we briefly describe some of the software infractructure used to implement modern networked control systems, with a focus on networked and distributed systems. We focus on the use of spread as a specific example of a low-level message transfer subsystem and describe how it can be used in a NCS context. We then describe the Pthreads programming environment, which provides a standardized API for managing process threads.

	== Lecture Materials ==		== Lecture Materials ==
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	* <p>[http://www.cds.caltech.edu/~murray/papers/2001n_mur+03-sec.html Online Control Customization via Optimization-Based Control], R. M. Murray et al. In Software-Enabled Control: Information Technology for Dynamical Systems, T. Samad and G. Balas (eds.), IEEE Press, 2001. This paper talks about the CLF-based nonlinear RHC approach and its application on the Caltech ducted fan using NTG.</p>		* <p>[http://www.cds.caltech.edu/~murray/papers/2001n_mur+03-sec.html Online Control Customization via Optimization-Based Control], R. M. Murray et al. In Software-Enabled Control: Information Technology for Dynamical Systems, T. Samad and G. Balas (eds.), IEEE Press, 2001. This paper talks about the CLF-based nonlinear RHC approach and its application on the Caltech ducted fan using NTG.</p>
	* <p>[http://www.seas.upenn.edu/~jadbabai/papers/TAC_jh_final.pdf Unconstrained Receding-Horizon Control of Nonlinear Systems], A. Jadbabaie, J. Yu and J. Hauser. IEEE Transactions on Automatic Control, May 2001, Vol. 46, No. 5, pp. 776-783. This paper might be a little dense for the first read, but contains an essence of A. Jadbabaie's PhD thesis on CLF-based nonlinear RHC.</p>		* <p>[http://www.seas.upenn.edu/~jadbabai/papers/TAC_jh_final.pdf Unconstrained Receding-Horizon Control of Nonlinear Systems], A. Jadbabaie, J. Yu and J. Hauser. IEEE Transactions on Automatic Control, May 2001, Vol. 46, No. 5, pp. 776-783. This paper might be a little dense for the first read, but contains an essence of A. Jadbabaie's PhD thesis on CLF-based nonlinear RHC.</p>

			=== Kalman filtering and state estimation ===

	=== Messaging Systems ===		=== Messaging Systems ===