Iterative learning control (ILC) [1] can achieve a high performance for repetitive setpoints. However, for different setpoints ILC should start over. In this work point-to-point movements rk(t) with different magnitudes are considered which are constructed by scaling a nominal setpoint r(t), i.e., rk(t) = Tkr(t). A second order ILC (SOILC) [2] method is developed to accurately track these setpo...

This note presents a list of physics processes for benchmarking the performance of proposed ILC detectors. This list gives broad coverage of the required physics capabilities of the ILC experiments and suggests target accuracies to be achieved. A reduced list of reactions, which capture within a very economical set the main challenges put by the ILC physics program, is suggested for the early s...

BACKGROUND Invasive lobular carcinoma (ILC) comprises approximately ~10-20% of breast cancers. In general, multifocal/multicentric (MF/MC) breast cancer has been associated with an increased rate of regional lymph node metastases. Tumor heterogeneity between foci represents a largely unstudied source of genomic variation in those rare patients with MF/MC ILC. METHODS We characterized gene exp...

This article investigates the iterative learning control (ILC) problem for a remote network control systems. To reduce wireless channel noise, a novel method of Kalman filtering is combined into the remote ILC system. The Kalman filtering reduce stochastic error on time axis, while the ILC operates on iteration axis. The convergence of the proposed system was analyzed and the convergence condit...

Iterative learning control (ILC) is a design technique which can achieve accurate tracking by learning over repeated task attempts. However, long-term stability remains a critical limitation to widespread application, and to-date robustness analysis has overwhelmingly considered structured uncertainties. This paper substantially expands the scope of existing ILC robustness analysis by addressin...

Human RORC(+) lymphoid tissue inducer cells are part of a rapidly expanding family of innate lymphoid cells (ILC) that participate in innate and adaptive immune responses as well as in lymphoid tissue (re) modeling. The assessment of a potential role for innate lymphocyte-derived cytokines in human homeostasis and disease is hampered by a poor characterization of RORC(+) innate cell subsets and...

Control of aerodynamic loads in wind turbines is a critical issue in terms of keeping them economically competitive with alternative energy sources. This paper continues the investigation of the use of Iterative Learning Control (ILC) for load control in wind turbines with smart devices on rotor blades. Smart devices controlled by ILC are used to modify the blade section aerodynamics such that ...

Based on a two-dimensional (2D) system description of a batch process, a robust closed-loop iterative learning control (ILC) scheme is proposed for batch processes with time-varying uncertainties. An important merit is that the proposed ILC method can be used for on-line optimization against batchto-batch process uncertainties to realize robust tracking of the setpoint trajectory in both the ti...

The iterative learning control (ilc) method improves performance of systems that repeat the same task several times. In this paper the standard norm-optimal ilc control law for linear systems is extended to an estimation-based ilc algorithm where the controlled variables are not directly available as measurements. The proposed ilc algorithm is proven to be stable and gives monotonic convergence...

Innate and adaptive immune cells work in concert to generate efficient protection at mucosal surface. Vaginal mucosa is an epithelial tissue that contains innate and adaptive immune effector cells. Our previous studies demonstrated that vaginal administration of Cholera toxin -based vaccines generate antigen-specific CD8 T cells through the stimulation of local dendritic cells (DC). Innate lymp...