Adaptive output feedback control of nonlinear systems using neural networks

By A. Calise, Naira Hovakimyan, M. Idan. at - Automatisierungstechnik, 2001

456 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/3298339dcd39e839954dad13a6a2c2b36bd408cf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Zhouhua Peng
2. Jun Wang
3. Dan Wang
4. Girish V. Chowdhary
5. Eric N. Johnson
6. Shuzhi Sam Ge

In Control and Systems Engineering

1. Jun Wang
2. Zhouhua Peng
3. Dan Wang
4. Girish V. Chowdhary
5. Eric N. Johnson
6. Shaocheng Tong
7. Yong-ming Li
8. Shuzhi Sam Ge

Citations in the corpus

• Distributed Maneuvering of Autonomous Surface Vehicles Based on Neurodynamic Optimization and Fuzzy Approximation (2018, methodology): “Similar to [46] and [47], the input and output data are fed into the fuzzy system to approximate the unknown function.”
• Theory and Flight-Test Validation of a Concurrent-Learning Adaptive Controller (2011, methodology): “Calise et al. [4], Johnson et al. [5] [6] [7] [8], Kannan [9], and others have developed model reference adaptive control (MRAC) methodology for control of unmanned aerial systems (UASs).”