David Ofosu Amoateng

Control and Systems Engineering · 2016

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom David Ofosu Amoateng trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Shuzhi Sam Ge
  2. Yanjun Liu
  3. Wei He
  4. Chun Lung Philip Chen
  5. F. I. C. L. Philip Chen
  6. Keng Peng Tee

Who trusts David Ofosu Amoateng overall

  1. Wei He
  2. Chenguang Yang

Papers from David Ofosu Amoateng's perspective

Ordered by how strongly the researchers David Ofosu Amoateng trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks (IEEE Transactions on Neural Networks and Learning Systems)
  2. Adaptive neural control of uncertain MIMO nonlinear systems (IEEE Transactions on Neural Networks)
  3. Adaptive Neural Output Feedback Tracking Control for a Class of Uncertain Discrete-Time Nonlinear Systems (IEEE Transactions on Neural Networks)
  4. Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function (IEEE Transactions on Neural Networks)
  5. Neural-network control of nonaffine nonlinear system with zero dynamics by state and output feedback (IEEE Trans. Neural Networks)
  6. Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems (Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527))
  7. Control of fully actuated ocean surface vessels using a class of feedforward approximators (IEEE Transactions on Control Systems Technology)
  8. Fuzzy Neural Network-Based Adaptive Control for a Class of Uncertain Nonlinear Stochastic Systems (IEEE Transactions on Cybernetics)
  9. Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints (IEEE Transactions on Cybernetics)
  10. Barrier Lyapunov Functions for the control of output-constrained nonlinear systems (at - Automatisierungstechnik)

Their papers