Abstract
This paper proposes a new model-following adaptive control design technique for nonlinear systems that are nonaffine in control. The adaptive controller uses online neural networks that guarantee tracking in the presence of unmodeled dynamics and/or parameter uncertainties present in the system model through an online control adaptation procedure. The controller design is carried out in two steps: (i) synthesis of a set of neural networks which capture the unmodeled (neglected) dynamics or model uncertainties due to parametric variations and (ii) synthesis of a controller that drives the state of the actual plant to that of a reference model. This method is tested using a three degree of freedom model of a UAV. Numerical results which demonstrate these features and clearly bring out the potential of the proposed approach are presented in this paper.
| Original language | American English |
|---|---|
| Journal | Proceedings of the 2006 American Control Conference |
| DOIs | |
| State | Published - Jan 1 2006 |
Keywords
- Adaptive Control
- Adaptive Control Design
- Aerospace Control
- Control System Synthesis
- Degree of Freedom Model
- Neuroadaptive Model
- Neurocontrollers
- Nonaffine UAV Model
- Nonlinear Control Systems
- Nonlinear System
- Online Neural Network
- Parameter Uncertainty
- Remotely Operated Vehicles
- Unmanned Aerial Vehicle
- Unmodeled Dynamics
Disciplines
- Aerospace Engineering
- Mechanical Engineering
Fingerprint
Dive into the research topics of 'Neuroadaptive Model Following Controller Design for a Nonaffine UAV Model'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS