Eric M. Gross

Modeling and control of cyclic systems in xerography

This paper is devoted to the scientific study and engineering application of cyclic systems. Cyclic systems are non-traditional plants, containing devices with rotating dynamics along with actuators and sensors fixed in inertial space. The combination of rotating dynamics and inertially-fixed inputs and outputs leads to one-per-revolution (or stroboscopic) actuation and sensing. Control of cyclic systems amounts to designing a regulator that uses stroboscopic actuation and sensing to force the system into the desired regime. Although cyclic systems are periodic, the general theory of periodic control is not immediately applicable due to stroboscopic actuation and sensing. Because of rotating dynamics, the theory of impulsive control is not applicable as well. This work develops an approach to the control of systems with both rotating dynamics and stroboscopic instrumentation, and reports the initial application to a xerographic process.

Cyclic Control: Reference Tracking and Disturbance Rejection

Cyclic control (CC) is concerned with systems comprised of multiple plants controlled by a single actuator and sensor. Such systems arise naturally in rotating machinery with actuators and sensors fixed in inertial space. This paper investigates the problem of reference tracking and disturbance rejection in CC systems and illustrates the results through the control of the fusing stage of a xerographic process.

Cyclic Control: Problem Formulation and Stability Analysis

This paper considers the problem of controlling rotating machinery with actuators and sensors fixed in inertial space. Such a problem arises in control of charging and fusing stages in the xerographic process, drilling and milling machines, and turbo machinery. If a rotating device is represented as a set of discrete wedges, the resulting system can be conceptualized as a set of plants (wedges) with a single actuator and sensor. In such architecture, each plant can be controlled only intermittently, in a stroboscopic manner. This leads to the problem of Cyclic Control (CC) considered in this paper. Specifically, the problem of stabilizability in CC architecture is considered, and the resulting stabilizability conditions are compared with those in the usual, permanently acting control (PAC). In this regard, it is shown that the domain of asymptotic stability under CC is an open disc in the open left half plane (OLHP), rather than the OLHP itself, and the controller gains that place the closed loop poles at the desired locations under CC are N times larger than those under PAC, where N is the number of wedges. The results are applied to temperature stabilization of the fusing stage of a xerographic process.

Cyclic Control: The Case of Static Output Feedback

Abstract This paper develops a control theory for systems comprised of multiple plants controlled by a single actuator and sensor. Such systems arise in rotating machinery with actuators and sensors fixed in inertial space. Representing the rotating device as a set of discrete wedges leads to a model mentioned above. In such systems, each plant can be controlled only intermittently, e.g., once per revolution. We refer to this situation as cyclic control (CC). The paper investigates the problems of stabilizability, reference tracking, and disturbance rejection in CC systems using static output feedback.

Interpretable Classifier for Identifying High-Value Child Support Cases

This work brings interpretable and accurate data analytics to child support agencies with the goal of substantially increasing their effectiveness. In the realm of child support, a custodial parent may be entitled to periodic child support payments from the noncustodial parent. In order to analyze this process, we have gathered case data from several child support agencies. The objective of the work is to develop analytical models that characterize and predict high-value child support cases. High-value cases are those that result in successful payments and require far fewer resources for enforcement. We create interpretable and accurate scoring models to identify these cases so that the key attributes driving their prediction are easily understood by the caseworkers. This information may be integrated with case management systems to schedule and prioritize the caseload.

Simulation-Based Optimization Using Greedy Techniques and Simulated Annealing for Optimal Equipment Selection Within Print Production Environments

Xerox has invented, tested, and implemented a novel class of operations-research-based productivity improvement offerings, marketed as Lean Document Production (LDP), for the

Systems and methods for correcting banding defects using feedback and/or feedforward control

100 billion printing industry in the United States. The software toolkit that enables the optimization of print shops is data-driven and simulation-based. It enables quick modeling of complex print production environments under the cellular production framework. The software toolkit automates several steps of the modeling process by taking declarative inputs from the end user and then automatically generating complex simulation models that are used to determine improved design and operating policies. This chapter describes the addition of another layer of automation consisting of simulation-based optimization using simulated annealing and greedy search techniques that enable the search of a large number of design alternatives in the presence of operational and cost constraints. The greedy search procedure quickly determines an acceptable solution in a web-based online application environment. The simulated annealing technique is more time consuming and is performed offline. The results of the application of this approach to real-world problems are described.