Abstract
A novel design approach is proposed for point-to-point iterative learning control (ILC), enabling system constraints to be satisfied while simultaneously addressing the requirement for high-performance tracking. It is shown that point-to-point ILC design can be formulated and solved using a successive projection first proposed by J. von Neumann, allowing a number of new point-to-point ILC algorithms to be developed and analyzed. To illustrate this framework, two new algorithms are derived with different convergence and computational properties for the constrained point-to-point ILC design problem. The proposed algorithms are validated on a robotic arm with experimental results demonstrating their effectiveness.
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