A sensitivity approach to optimal spline robot trajectories
Automatica (Journal of IFAC)
More matrix forms of the arithmetic-geometric mean inequality
SIAM Journal on Matrix Analysis and Applications
Initial state iterative learning for final state control in motion systems
Automatica (Journal of IFAC)
Objective-driven ILC for point-to-point movement tasks
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
ACC'09 Proceedings of the 2009 conference on American Control Conference
Iterative Learning Control: Brief Survey and Categorization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
| Hi-index | 22.14 |
In this paper, we present two iterative learning control (ILC) frameworks for tracking problems with specified data points that are desired points at certain time instants. To design ILC systems for such problems, unlike traditional ILC approaches, we first develop an algorithm in which not only the control signal but also the reference trajectory is updated at each trial. We investigate the relationship between the reference trajectory and ILC tracking control as it relates to the rate of convergence. Second, a new ILC scheme is proposed to produce output curves that pass close to the desired points. Here, the control signals are generated by solving an optimal ILC problem with respect to the desired sampling points. One of the key advantages of the proposed approaches is a significant reduction of the computational cost.