Iterative learning control for a class of nonlinear systems
Automatica (Journal of IFAC)
Iterative learning control in feedback systems
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Iterative Learning Control for Deterministic Systems
Iterative Learning Control for Deterministic Systems
Brief Sampled-data iterative learning control for nonlinear systems with arbitrary relative degree
Automatica (Journal of IFAC)
Brief paper: Adaptive learning control of linear systems by output error feedback
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Technical communique: Further results on adaptive iterative learning control of robot manipulators
Automatica (Journal of IFAC)
A reinforced iterative formalism to learn from human errors and uncertainty
Engineering Applications of Artificial Intelligence
Iterative learning control based tools to learn from human error
Engineering Applications of Artificial Intelligence
Hi-index | 22.15 |
In this paper, we derive an output tracking error model based on signals filtered from plant input and output, and then present a new output-based adaptive iterative learning controller for repeatable linear systems with unknown parameters, high relative degree, initial resetting error, input disturbance and output noise. The proposed controller solves the important robustness issues without assuming the bounds of uncertainties to be sufficiently small and can be applied to high relative degree plants without using output differentiation. Control parameters are updated between successive iterations so as to compensate for unknown system parameters and uncertainties. It is shown that the internal signals inside closed-loop learning system remain bounded and the output tracking error will asymptotically converge to a profile tunable by some design parameters. Furthermore, the learning speed is easily improved if the learning gain is increased.