Constrained Optimization-Based Neuro-Adaptive Control (CONAC)

• Paper Name: TBD
• State: TBD
• Template Version: Robot Branch

Note

This paper will be submitted to IEEE Transactions on Cybernetics.

You can find papers here:

• First submission:

About this Research

The objective of this research is to design neuro-adaptive controller using constrained optimization theory. The main features are as follows.

• Stability of controller is ensured in the sense of Lyapunov.
• Weights of neural network and tracking error are bounded over time.
• Constraints are satisfied while adaptation (learning)
  • Weight norm constraint.
  • Control input saturation constraint (which is convex).

Authors

• Myeongseok Ryu
• Donghwa Hong
• Kyunghwan Choi

Gantt Chart

gantt
    title CONAC
    dateFormat  YYYY-MM-DD
    axisFormat  CW%U
    section Writing
    Introduction: w1, 2025-04-14, 7d
    Method: w2, after w1, 27d
    section Validation
    Measurement: v1,  2025-05-03, 28d
    section Submission
    Test and evaluation: t1,   2025-05-31, 5d

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