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You searched for subject:(tuning functions). Showing records 1 – 4 of 4 total matches.

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Carnegie Mellon University

1. Silver, David. Learning Preference Models for Autonomous Mobile Robots in Complex Domains.

Degree: 2010, Carnegie Mellon University

 Achieving robust and reliable autonomous operation even in complex unstructured environments is a central goal of field robotics. As the environments and scenarios to which… (more)

Subjects/Keywords: Mobile Robots; Field Robotics; Learning from Demonstration; Imitation Learning; Inverse Optimal Control; Active Learning; Preference Models; Cost Functions; Parameter Tuning; Artificial Intelligence and Robotics

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APA (6th Edition):

Silver, D. (2010). Learning Preference Models for Autonomous Mobile Robots in Complex Domains. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/551

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Silver, David. “Learning Preference Models for Autonomous Mobile Robots in Complex Domains.” 2010. Thesis, Carnegie Mellon University. Accessed September 19, 2020. http://repository.cmu.edu/dissertations/551.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Silver, David. “Learning Preference Models for Autonomous Mobile Robots in Complex Domains.” 2010. Web. 19 Sep 2020.

Vancouver:

Silver D. Learning Preference Models for Autonomous Mobile Robots in Complex Domains. [Internet] [Thesis]. Carnegie Mellon University; 2010. [cited 2020 Sep 19]. Available from: http://repository.cmu.edu/dissertations/551.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Silver D. Learning Preference Models for Autonomous Mobile Robots in Complex Domains. [Thesis]. Carnegie Mellon University; 2010. Available from: http://repository.cmu.edu/dissertations/551

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Michigan

2. Runkle, Paul Robert. Optimization of head -related transfer functions using subjective criteria.

Degree: PhD, Electrical engineering, 2000, University of Michigan

 For many applications and devices directly involving an individual's perception, it is often desirable to incorporate the user's subjective preferences in the system design. Examples… (more)

Subjects/Keywords: Active Sensory Tuning; Criteria; Genetic Algorithm; Head-related Transfer Functions; Optimization; Subjective; Using

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APA (6th Edition):

Runkle, P. R. (2000). Optimization of head -related transfer functions using subjective criteria. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/132461

Chicago Manual of Style (16th Edition):

Runkle, Paul Robert. “Optimization of head -related transfer functions using subjective criteria.” 2000. Doctoral Dissertation, University of Michigan. Accessed September 19, 2020. http://hdl.handle.net/2027.42/132461.

MLA Handbook (7th Edition):

Runkle, Paul Robert. “Optimization of head -related transfer functions using subjective criteria.” 2000. Web. 19 Sep 2020.

Vancouver:

Runkle PR. Optimization of head -related transfer functions using subjective criteria. [Internet] [Doctoral dissertation]. University of Michigan; 2000. [cited 2020 Sep 19]. Available from: http://hdl.handle.net/2027.42/132461.

Council of Science Editors:

Runkle PR. Optimization of head -related transfer functions using subjective criteria. [Doctoral Dissertation]. University of Michigan; 2000. Available from: http://hdl.handle.net/2027.42/132461


Delft University of Technology

3. Van Gils, P. (author). Adaptive Incremental Backstepping Flight Control.

Degree: 2015, Delft University of Technology

This thesis deals with the development of Adaptive Incremental Backstepping control laws for a high-performance aircraft model (F-16), in order to make the airplane robustly… (more)

Subjects/Keywords: flight control; incremental control; robust control; adaptive control; fault-tolerant; backstepping; adaptive backstepping; incremental backstepping; parameter estimation; system identification; immersion and invariance; tuning functions; recursive least-squares

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APA (6th Edition):

Van Gils, P. (. (2015). Adaptive Incremental Backstepping Flight Control. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f62ac38d-5101-4230-ad90-d54543c1f1b8

Chicago Manual of Style (16th Edition):

Van Gils, P (author). “Adaptive Incremental Backstepping Flight Control.” 2015. Masters Thesis, Delft University of Technology. Accessed September 19, 2020. http://resolver.tudelft.nl/uuid:f62ac38d-5101-4230-ad90-d54543c1f1b8.

MLA Handbook (7th Edition):

Van Gils, P (author). “Adaptive Incremental Backstepping Flight Control.” 2015. Web. 19 Sep 2020.

Vancouver:

Van Gils P(. Adaptive Incremental Backstepping Flight Control. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2020 Sep 19]. Available from: http://resolver.tudelft.nl/uuid:f62ac38d-5101-4230-ad90-d54543c1f1b8.

Council of Science Editors:

Van Gils P(. Adaptive Incremental Backstepping Flight Control. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:f62ac38d-5101-4230-ad90-d54543c1f1b8

4. Gunbatar, Yakup. Nonlinear Adaptive Control and Guidance for Unstart Recovery for a Generic Hypersonic Vehicle.

Degree: PhD, Electrical and Computer Engineering, 2014, The Ohio State University

 This work presents the development of an integrated flight controller for a generic model of a hypersonic air-breathing vehicle. The flight control architecture comprises a… (more)

Subjects/Keywords: Aerospace Engineering; Engineering; Electrical Engineering; Computer Engineering; Hypersonic; unstart; adaptive control; nonlinear control; adaptive backstepping; trajectory optimization; optimal; tuning functions; longitudinal; 6-DOF; 3-DOF; Earth rotation; Control design model; coordinated turn; endurance; Equations of motion

tuning functions [21] and avoids filtering the virtual commands. Model… …Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7.1 Tuning of the stability… …of the longitudinal dynamics are represented as functions of the flat outputs, namely… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Gunbatar, Y. (2014). Nonlinear Adaptive Control and Guidance for Unstart Recovery for a Generic Hypersonic Vehicle. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1406160002

Chicago Manual of Style (16th Edition):

Gunbatar, Yakup. “Nonlinear Adaptive Control and Guidance for Unstart Recovery for a Generic Hypersonic Vehicle.” 2014. Doctoral Dissertation, The Ohio State University. Accessed September 19, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406160002.

MLA Handbook (7th Edition):

Gunbatar, Yakup. “Nonlinear Adaptive Control and Guidance for Unstart Recovery for a Generic Hypersonic Vehicle.” 2014. Web. 19 Sep 2020.

Vancouver:

Gunbatar Y. Nonlinear Adaptive Control and Guidance for Unstart Recovery for a Generic Hypersonic Vehicle. [Internet] [Doctoral dissertation]. The Ohio State University; 2014. [cited 2020 Sep 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1406160002.

Council of Science Editors:

Gunbatar Y. Nonlinear Adaptive Control and Guidance for Unstart Recovery for a Generic Hypersonic Vehicle. [Doctoral Dissertation]. The Ohio State University; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1406160002

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