Art Krener, Feb 2016 - Revision history

Yleong: /* Schedule */

2016-02-18T20:44:10Z

Schedule

← Older revision		Revision as of 20:44, 18 February 2016
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	* 12:00 - Lunch with Richard, Doug		* 12:00 - Lunch with Richard, Doug
	* 1:30 - Ivan Papusha, 231 Annenberg		* 1:30 - Ivan Papusha, 231 Annenberg
	* 2:15 - Yoke Peng		* 2:15 - Yoke Peng, 230 Annenberg
	* 3:00 - Doyle		* 3:00 - Doyle
	* 3:45 - Stop by Richard's office on the way out		* 3:45 - Stop by Richard's office on the way out

Murray at 00:59, 18 February 2016

2016-02-18T00:59:35Z

← Older revision		Revision as of 00:59, 18 February 2016
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	* 2:15 - Yoke Peng		* 2:15 - Yoke Peng
	* 3:00 - Doyle		* 3:00 - Doyle
	* 3:45 - ~~open (if needed)~~		* 3:45 - Stop by Richard's office on the way out
	* 4:30 - done for the ~~day~~

	=== Abstract ===		=== Abstract ===

Ipapusha: /* Schedule */

2016-02-12T22:03:43Z

Schedule

← Older revision		Revision as of 22:03, 12 February 2016
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	* 11:00 - Seminar, 115 Gates-Thomas		* 11:00 - Seminar, 115 Gates-Thomas
	* 12:00 - Lunch with Richard, Doug		* 12:00 - Lunch with Richard, Doug
	* 1:30 - ~~open~~		* 1:30 - Ivan Papusha, 231 Annenberg
	* 2:15 - Yoke Peng		* 2:15 - Yoke Peng
	* 3:00 - Doyle		* 3:00 - Doyle

Yleong: /* Schedule */

2016-02-12T18:04:12Z

Schedule

← Older revision		Revision as of 18:04, 12 February 2016
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	* 12:00 - Lunch with Richard, Doug		* 12:00 - Lunch with Richard, Doug
	* 1:30 - open		* 1:30 - open
	* 2:15 - ~~open~~		* 2:15 - Yoke Peng
	* 3:00 - Doyle		* 3:00 - Doyle
	* 3:45 - open (if needed)		* 3:45 - open (if needed)

Doyle: /* Schedule */

2016-02-12T17:46:24Z

Schedule

← Older revision		Revision as of 17:46, 12 February 2016
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	* 1:30 - open		* 1:30 - open
	* 2:15 - open		* 2:15 - open
	* 3:00 - ~~open~~		* 3:00 - Doyle
	* 3:45 - open (if needed)		* 3:45 - open (if needed)
	* 4:30 - done for the day		* 4:30 - done for the day

Murray at 15:37, 12 February 2016

2016-02-12T15:37:22Z

← Older revision		Revision as of 15:37, 12 February 2016
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	* ~10:15 - Richard Murray, 109 Steele Lab		* ~10:15 - Richard Murray, 109 Steele Lab
	* 10:45 - set up for seminar		* 10:45 - set up for seminar
	* 11:00 - Seminar, ~~213 or 121 Annenberg~~		* 11:00 - Seminar, 115 Gates-Thomas
	* 12:00 - Lunch with Richard, Doug		* 12:00 - Lunch with Richard, Doug
	* 1:30 - open		* 1:30 - open
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	Arthur J. Krener, Naval Postgraduate School<br>		Arthur J. Krener, Naval Postgraduate School<br>
	18 Feb (Thu) - 11:00am PST, ~~121/213 Annenberg~~		18 Feb (Thu) - 11:00am PST, 115 Gates-Thomas

	Abstract: Adaptive Horizon Model Predictive Control (AHMPC) is a scheme for varying the horizon length of Model Predictive Control (MPC) as needed. Its goal is to achieve stabilization with horizons as small as possible so that MPC can be used on faster or more complicated dynamic processes. Beside the standard requirements of MPC including a terminal cost that is a control Lyapunov function, AHMPC requires a terminal feedback that turns the control Lyapunov function into a standard Lyapunov function in some domain around the operating point. But this domain need not be known explicitly. MPC does not compute off-line the optimal cost and the optimal feedback over a large domain instead it computes these quantities on-line when and where they are needed. AHMPC does not compute off-line the domain on which the terminal cost is a control Lyapunov function instead it computes on-line when a state is in this domain.		Abstract: Adaptive Horizon Model Predictive Control (AHMPC) is a scheme for varying the horizon length of Model Predictive Control (MPC) as needed. Its goal is to achieve stabilization with horizons as small as possible so that MPC can be used on faster or more complicated dynamic processes. Beside the standard requirements of MPC including a terminal cost that is a control Lyapunov function, AHMPC requires a terminal feedback that turns the control Lyapunov function into a standard Lyapunov function in some domain around the operating point. But this domain need not be known explicitly. MPC does not compute off-line the optimal cost and the optimal feedback over a large domain instead it computes these quantities on-line when and where they are needed. AHMPC does not compute off-line the domain on which the terminal cost is a control Lyapunov function instead it computes on-line when a state is in this domain.

Murray at 20:56, 10 February 2016

2016-02-10T20:56:37Z

← Older revision		Revision as of 20:56, 10 February 2016
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	Arthur J. Krener, Naval Postgraduate School<br>		Arthur J. Krener, Naval Postgraduate School<br>
	18 Feb (Thu) - 11:00am PST, 12/~~2131~~ Annenberg		18 Feb (Thu) - 11:00am PST, 121/213 Annenberg

	Abstract: Adaptive Horizon Model Predictive Control (AHMPC) is a scheme for varying the horizon length of Model Predictive Control (MPC) as needed. Its goal is to achieve stabilization with horizons as small as possible so that MPC can be used on faster or more complicated dynamic processes. Beside the standard requirements of MPC including a terminal cost that is a control Lyapunov function, AHMPC requires a terminal feedback that turns the control Lyapunov function into a standard Lyapunov function in some domain around the operating point. But this domain need not be known explicitly. MPC does not compute off-line the optimal cost and the optimal feedback over a large domain instead it computes these quantities on-line when and where they are needed. AHMPC does not compute off-line the domain on which the terminal cost is a control Lyapunov function instead it computes on-line when a state is in this domain.		Abstract: Adaptive Horizon Model Predictive Control (AHMPC) is a scheme for varying the horizon length of Model Predictive Control (MPC) as needed. Its goal is to achieve stabilization with horizons as small as possible so that MPC can be used on faster or more complicated dynamic processes. Beside the standard requirements of MPC including a terminal cost that is a control Lyapunov function, AHMPC requires a terminal feedback that turns the control Lyapunov function into a standard Lyapunov function in some domain around the operating point. But this domain need not be known explicitly. MPC does not compute off-line the optimal cost and the optimal feedback over a large domain instead it computes these quantities on-line when and where they are needed. AHMPC does not compute off-line the domain on which the terminal cost is a control Lyapunov function instead it computes on-line when a state is in this domain.

Murray at 20:55, 10 February 2016

2016-02-10T20:55:14Z

← Older revision		Revision as of 20:55, 10 February 2016
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	=== Schedule ===		=== Schedule ===
	* ~10:00 - Richard Murray, 109 Steele Lab		* ~10:15 - Richard Murray, 109 Steele Lab
			* 10:45 - set up for seminar
	* 11:00 - Seminar, 213 or 121 Annenberg		* 11:00 - Seminar, 213 or 121 Annenberg
	* 12:00 - Lunch with Richard, Doug		* 12:00 - Lunch with Richard, Doug

Murray: Created page with "Art Krener will be visiting Caltech on 18 Feb (Thu). If you would like to meet with him, sign up below. === Schedule === * ~10:00 - Richard Murray, 109 Steele Lab * 11:00 -..."

2016-02-10T20:54:08Z

Created page with "Art Krener will be visiting Caltech on 18 Feb (Thu). If you would like to meet with him, sign up below. === Schedule === * ~10:00 - Richard Murray, 109 Steele Lab * 11:00 -..."

New page

Art Krener will be visiting Caltech on 18 Feb (Thu). If you would like to meet with him, sign up below.

=== Schedule ===
* ~10:00 - Richard Murray, 109 Steele Lab
* 11:00 - Seminar, 213 or 121 Annenberg
* 12:00 - Lunch with Richard, Doug
* 1:30 - open
* 2:15 - open
* 3:00 - open
* 3:45 - open (if needed)
* 4:30 - done for the day

=== Abstract ===

Adaptive Horizon Model Predictive Control

Arthur J. Krener, Naval Postgraduate School<br>
18 Feb (Thu) - 11:00am PST, 12/2131 Annenberg

Abstract: Adaptive Horizon Model Predictive Control (AHMPC) is a scheme for varying the horizon length of Model Predictive Control (MPC) as needed. Its goal is to achieve stabilization with horizons as small as possible so that MPC can be used on faster or more complicated dynamic processes. Beside the standard requirements of MPC including a terminal cost that is a control Lyapunov function, AHMPC requires a terminal feedback that turns the control Lyapunov function into a standard Lyapunov function in some domain around the operating point. But this domain need not be known explicitly. MPC does not compute off-line the optimal cost and the optimal feedback over a large domain instead it computes these quantities on-line when and where they are needed. AHMPC does not compute off-line the domain on which the terminal cost is a control Lyapunov function instead it computes on-line when a state is in this domain.