Iterative learning control: analysis, design, integration and applications
Iterative learning control: analysis, design, integration and applications
Model-based iterative learning control with a quadratic criterion for time-varying linear systems
Automatica (Journal of IFAC)
Brief paper: All-pass filtering in iterative learning control
Automatica (Journal of IFAC)
Brief paper: Suppressing intersample behavior in iterative learning control
Automatica (Journal of IFAC)
Brief paper: Iterative Learning Control for uncertain systems: Robust monotonic convergence analysis
Automatica (Journal of IFAC)
Neuro-Adaptive Output Feedback Control for a Class of Nonlinear Non-Minimum Phase Systems
Journal of Intelligent and Robotic Systems
Norm optimal ILC with time-varying weighting matrices
ACC'09 Proceedings of the 2009 conference on American Control Conference
Low-order system identification and optimal control of intersample behavior in ILC
ACC'09 Proceedings of the 2009 conference on American Control Conference
Model inverse based iterative learning control using finite impulse response approximations
ACC'09 Proceedings of the 2009 conference on American Control Conference
Iterative learning control with saturation constraints
ACC'09 Proceedings of the 2009 conference on American Control Conference
Iterative Learning Control-Monotonicity and Optimization
International Journal of Applied Mathematics and Computer Science - Selected Problems of Computer Science and Control
Brief paper: Robust adaptive control of nonlinear non-minimum phase systems with uncertainties
Automatica (Journal of IFAC)
Brief paper: Linear computational complexity robust ILC for lifted systems
Automatica (Journal of IFAC)
Technical communique: A note on causal and CITE iterative learning control algorithms
Automatica (Journal of IFAC)
A computationally efficient norm optimal iterative learning control approach for LTV systems
Automatica (Journal of IFAC)
Hi-index | 22.16 |
Iterative learning control (ILC) based on minimization of a quadratic criterion in the control error and the input signal is considered. The focus is on the frequency domain properties of the algorithm, and how it is able to handle non-minimum phase systems. Experiments carried out on a commercial industrial robot are also presented.