Sandipan Mishra

High-speed and drop-on-demand printing with a pulsed electrohydrodynamic jet

We present a pulsed dc voltage printing regime for high-speed, high-resolution and high-precision electrohydrodynamic jet (E-jet) printing. The voltage pulse peak induces a very fast E-jetting mode from the nozzle for a short duration, while a baseline dc voltage is picked to ensure that the meniscus is always deformed to nearly a conical shape but not in a jetting mode. The duration of the pulse determines the volume of the droplet and therefore the feature size on the substrate. The droplet deposition rate is controlled by the time interval between two successive pulses. Through a suitable choice of the pulse width and frequency, a jet-printing regime with a specified droplet size and droplet spacing can be created. Further, by properly coordinating the pulsing with positioning commands, high spatial resolution can also be achieved. We demonstrate high-speed printing capabilities at 1 kHz with drop-on-demand and registration capabilities with 3–5 µm droplet size for an aqueous ink and 1–2 µm for a photocurable polymer ink.

Precision Positioning of Wafer Scanners Segmented Iterative Learning Control for Nonrepetitive Disturbances [Applications of Control]

Photolithography is a step in semiconductor manufacturing that uses a laser beam to transfer a pattern from a mask to the surface of a silicon wafer. This process is implemented by an optomechanical device called a wafer scanner. Wafer scanners require ultra-high-precision repetitive positioning capabilities. When the disturbances are repetitive, ILC improves performance of wafer-stage positioning from scan to scan. However, in the presence of nonrepetitive disturbances, ILC must be able to extract repetitive information, which is consistent from cycle to cycle, while avoiding nonrepetitive information.

Optimization-Based Constrained Iterative Learning Control

We consider the problem of synthesis of iterative learning control (ILC) schemes for constrained linear systems executing a repetitive task. The ILC problem with affine constraints and quadratic objective functions is formulated as a convex quadratic program, for which there exist computationally efficient solvers. The key difference between standard convex optimization and the corresponding constrained ILC problem is that each iteration in the latter requires an experiment run. We implement an interior-point-type method to reduce the number of iterations (and hence the number of experiment runs). We discuss the system-theoretic interpretations of the resulting optimization problem that lead to reductions in computational complexity and compare the performance of the implementation based on the interior-point method to another approach based on the active set method on a simulation example. We demonstrate the technique on a prototype wafer stage system with actuator saturation constraints and l2 norm of the tracking error as the objective function. The key contribution of this paper is the systematic use of numerical tools from constrained convex optimization in the ILC design.

Patterned Hydrogel Substrates for Cell Culture with Electrohydrodynamic Jet Printing

Cells respond to and are directed by physiochemical cues in their microenvironment, including geometry and substrate stiffness. The development of substrates for cell culture with precisely controlled physiochemical characteristics has the potential to advance the understanding of cell biology considerably. In this communication, E-jet printing is introduced as a method for creating high-resolution protein patterns on substrates with controlled elasticity. It is the first application of E-jet printing on a soft surface. Protein spots as small as 5 µm in diameter on polyacrylamide are demonstrated. The patterned hydrogels are shown to support cell attachment and spreading. Polyacrylamide substrates patterned by E-jet printing may be applied to further the study of cellular mechanobiology.

Projection-Based Iterative Learning Control for Wafer Scanner Systems

In this paper, an iterative learning controller (ILC) that uses partial but most pertinent information in the error signal from previous cycles is employed for precision control of a wafer stage. Typically, ILC schemes use the error signal from the previous cycle for updating the control input. This error contains both repetitive and nonrepetitive components. The nonrepetitive components of the error cause degradation of performance of the ILC scheme. Based on structural information about the plant and the disturbances, we can determine some basis functions along which the repetitive error is concentrated. This information is extracted by projecting the error signal onto the subspace spanned by these basis functions. The projected error signal is then used in the ILC update law. Stability and convergence conditions are presented for this projection-based ILC update law. The proposed idea is motivated by precision control of a wafer stage. For a constant velocity scan by the wafer stage, the major sources of repetitive error are found to be phase-mismatch and force ripple. These effects are mathematically modeled to obtain the subspace spanned by them. The projection-based ILC scheme using this subspace is then implemented on a prototype one DOF stage and its performance is compared to the standard ILC scheme that uses a frequency-domain filtering to remove nonrepetitive components of the error.

Fault-Tolerant Operation of Multiphase Permanent-Magnet Machines Using Iterative Learning Control

Fault-tolerant control (FTC) techniques for multiphase permanent magnet (PM) motors are usually designed to achieve maximum ripple-free torque under fault conditions with minimum ohmic losses. A widely accepted approach is based on flux distribution or back EMF (BEM) model of the machine to calculate healthy phase currents. This is essentially an open-loop technique where currents are determined (based on motor fault models) for each fault scenario. Therefore, it is highly model dependent. Since torque pulsation due to open-circuit faults and short-circuit faults are periodic, learning and repetitive control algorithms are excellent choices to minimize torque ripple. In this paper, iterative learning control (ILC) is applied as a current control technique for recovering performance in multiphase PM motor drives under fault conditions. The ILC-based FTC needs torque measurement or estimation, but avoids the need for complicated fault detection and fault diagnosis algorithms. Furthermore, BEM-based FTC and ILC-based FTC are proposed that initiates the learning from a model-based approximate guess (from the BEM method). Therefore, this method combines the advantages of both model information as well as robustness to model uncertainty through learning. Hence, the proposed method is well suited for high-performance safety critical applications. Finite element analysis and experimental results on a five-phase PM machine are presented for verification of the proposed control schemes.

Building temperature control: A passivity-based approach

This paper focuses on the temperature control in a multi-zone building. The lumped heat transfer model based on thermal resistance and capacitance is used to analyze the system dynamics and control strategy. The resulting thermal network, including the zones, walls, and ambient environment, may be represented as an undirected graph. The thermal capacitances are the nodes in the graph, connected by thermal resistances as links. We assume the temperature measurements and temperature control elements (heating and cooling) are collocated. We show that the resulting input/output system is strictly passive, and any passive output feedback controller may be used to improve the transient and steady state performance without affecting the closed loop stability. The storage functions associated with passive systems may be used to construct a Lyapunov function, to demonstrate closed loop stability and motivates the construction of an adaptive feedforward control. A four-room example is included to illustrate the performance of the proposed passivity based control strategy.

Automatic hotspot classification using pattern-based clustering

This paper proposes a new design check system that works in three steps. First, hotspots such as pinching/bridging are recognized in a product layout based on thorough process simulations. Small layout snippets centered on hotspots are clipped from the layout and similarities between these snippets are calculated by computing their overlapping areas. This is accomplished using an efficient, rectangle-based algorithm. The snippet overlapping areas can be weighted by a function derived from the optical parameters of the lithography process. Second, these hotspots are clustered using a hierarchical clustering algorithm. Finally, each cluster is analyzed in order to identify the common cause of failure for all the hotspots in that cluster, and its representative pattern is fed to a pattern-matching tool for detecting similar hotspots in new design layouts. Thus, the long list of hotspots is reduced to a small number of meaningful clusters and a library of characterized hotspot types is produced. This could lead to automated hotspot corrections that exploit the similarities of hotspots occupying the same cluster. Such an application will be the subject of a future publication.

Iterative learning control design for synchronization of wafer and reticle stages

This paper presents an iterative learning controller (ILC) design technique for synchronization in wafer scanning systems. In wafer scanners, synchronization of the wafer and reticle stages is critical for accurate pattern transfer. For synchronization, a master-slave configuration is used, with the wafer stage acting as the master, and the reticle stage as the slave. Since the scanning process is repetitive, ILC is used to improve tracking performance. However, the coupling between the reticle stage and wafer stage is unidirectional. Hence we propose an ILC scheme that takes into account this structural property of the overall system. A simple design procedure is presented which allows design of the ILC system for the wafer and reticle stages independently. This is done by first designing an ILC controller for the wafer (master) stage, and then using the synchronization error for ILC update for the reticle (slave) stage. Analytic conditions for stability and monotonic error convergence are then discussed. Finally, design and performance of the algorithm is illustrated by implementation on a single degree of freedom wafer stage, and a virtual (computer-simulated) reticle stage.

Modeling and feedback control of color-tunable LED lighting systems

This paper presents a color-science-based approach to feedback control design of color-tunable LED lighting systems for smart spaces. The general design problem is posed as the minimization of a cost function consisting of metrics that capture light quality, energy consumption and human comfort. A linear light transport map is used for modeling and identifying the optical fingerprint of the room. The feedback control law is then derived based on the identified model through gradient-based optimization of the cost function. Finally, experimental results are presented to highlight the performance of the feedback control law in terms of (1) energy savings, (2) delivered light quality, (3) adaptivity to external disturbances (such as daylighting) and (4) human comfort.