Adaptive control tutorial
By Petros A. Ioannou, Baris Fidan. Advances in design and control, 2006
821 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/9f01a22d2a6bf2de6f1bfaec5a720f5ee47c1b5a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Vijay R. Kumar
- Daniel Mellinger
- Huaguang Zhang
- Guanghong Yang
- John J. McPhee
- Frank L. Lewis
- Quentin Lindsey
- Michael Shomin
In Control and Systems Engineering
- Frank L. Lewis
- Vijay R. Kumar
- Derong Liu
- Kyriakos G. Vamvoudakis
- Huaguang Zhang
- Yanhong Luo
- Daniel Mellinger
- Hamidreza Modares
Citations in the corpus
- Design, modeling, estimation and control for aerial grasping and manipulation (2011, methodology): “We use methods which require the unknown parameters, θ, to appear linearly in the equations of motion [10], [9].”
- Adaptive optimal control for continuous-time linear systems based on policy iteration (2009, neutral): “The class of techniques called adaptive control (e.g. see Ioannou & Fidan, 2006) was developed in order to deal with the problem of designing controllers for systems with unknown or uncertain parameter models (e.g. systems for which parameters can drift slowly over time).”
- Leader-Based Optimal Coordination Control for the Consensus Problem of Multiagent Differential Games via Fuzzy Adaptive Dynamic Programming (2015, background): “to be sufficiently rich signals, which contain as least n/2 distinct nonzero frequencies (see [20], [39], and [45]).”
- Reinforcement Learning and Feedback Control: Using Natural Decision Methods to Design Optimal Adaptive Controllers (2012, background): “Adaptive control [1], [2] and optimal control [3] represent different philosophies for designing feedback controllers.”
- Parameter identification in dynamic systems using the homotopy optimization approach (2011, background): “Off-line identification algorithms are used when the main goal is to develop a mathematical model for system simulation; on-line identification algorithms are more popular in adaptive control applications [15].”
- Robust adaptive droop control for DC microgrids (2017, background): “According to [32], among control methodologies, the adaptive control does not require in-depth knowledge about the system for control design.”