Showing papers by "Warren B. Jackson published in 1999"

Interactive distributed communication method and system for bidding on, scheduling, routing and executing a document processing job

Abstract: A method and system allows for interactive, distributed job processing, e.g., print job processing, using a network, e.g., the Internet, and self-aware, remote processing equipment. Self-awareness allows the equipment to provide information about its load and status to a system controller such as a system server, either directly or through location servers located near the remote processing equipment. The method and system provide the capability to perform scheduling, routing and bidding on execution of jobs as well as re-routing, re-scheduling, remote proofing and remote processing instruction modification.

Distributed control of non-linear coupled systems with a single output

Abstract: The present invention encompasses a control system and method for systems of producing and consuming units. The method of the invention includes the steps of setting each producing unit to have an output responsive to an analog signal representative of a market price, and connecting each producing unit to a marketwire, with the changes in the analog signal on the marketwire representing changes in the market price resulting from inputs from the consuming units and the output response of each producing unit.

Pneumatic paper path

Abstract: A pneumatic transport system (10) moves a thin, flexible object (F) between two spaced positions. The pneumatic transport system includes an air module (12) having top and bottom plates (14,16) defining a transport channel (18) that receives a thin, flexible object, such as paper. A source of air directs an air flow through the transport channel and onto opposite sides of the thin, flexible object in a process. The top and bottom plates constrain the air flow while the air flow forms an air bearing between the thin, flexible object and the top and bottom plates. A transport path (30) as provided downstream from the air module in the process direction and communicates with the transport channel (18). The transport path (30) is defined by two closely spaced substantially parallel walls (32,34) that extend in the process direction. This transport path constrains the air flow and allows non-contact transport of the thin, flexible object through the transport path (30). An output device (12) downstream from the transport path (30) receives the thin, flexible object from the transport path (30). The transport path (30) may be flexible to allow dynamic connection to any one of several output devices.

Gas type conveying system

Abstract: PROBLEM TO BE SOLVED: To convey an object at a non-contact state along the inside of a flexible conveying passage by being provided with a conveying channel accommodating the object such as a paper sheet; an air module having upper and lower plates; and a conveying passage connected to the downstream of the air module. SOLUTION: A gas type passage system 10 for a paper includes an air module 12 comprising a lower plate 14 and an upper plate 16 defining a conveying channel 18 and a paper sheet P is conveyed by a gas in the conveying channel 18. In the air module 12, one or more air jet 20 is formed and an air stream injected from the air jet 20 is restricted by plates 14, 16 to form an air bearing against the sheet P. A paper passage 30 is connected to an exit of the air module 12, however, in the case where the paper passage 30 is long and big or is formed to a curved passage, a flow booster portion 60 for supporting the air stream to ensure a smooth conveying of the sheet P.

Distribution of partitionable physical properties for market based control of actuators and sensors

Abstract: Distributed market based analog control of a system of actuators and sensors. The system is comprised of one or more producing units having an output responsive to a market price and one or more input units having an input responsive to a market price. Market price information is communicated through an information channel that is encoded as measurable changes in non-electrical partitionable physical properties. Such partitionable physical properties include pressure, thermal, chemical or acoustic properties.

Market based control of structural movement

Abstract: A distributed market based control assembly used in conjunction with fixed or movable structures. Typically multiple actuators are attached to the structure, with each of the multiple actuators having an actuator controller to control actuator applied force. Sensors are used for measuring structure movement, and a marketwire is connected to each actuator controller to convey price information to the actuator controllers by analog fluctuations in electrical characteristics of the marketwire. Actuators can be used to stabilize a fixed structure against movement, or alternatively can be used to control movement of movable structures from defined first positions to second positions (e.g. moving a robotic arm so its tip moves from point A to point B).

Hybrid Problems in Smart Matter Control

Abstract: *Warren B. Jackson, Markus P.J. Fromherz, A.A. Berlin, D.K. Biegelsen, and P. CheungXerox Palo Alto Research Center3333 Coyote Hill Road, Palo Alto, CA 94304{wjackson,fromherz}@parc.xerox.comMarch 22, 1999The remarkable increase in computer capabilities per unit price has led to an explosion of computer appli-cations in processing information. Similarly, the significant increase in sensor and actuator capabilitiesper unit price now under way combined with the aforementioned computer advances will enable a rapidincrease in the number of control systems, i.e., systems that can sense and manipulate their environment.Many of the machines of the industrial age can be rearchitected using a multitude of sensors, actuators,and control systems if the requisite component prices are sufficiently low. In particular, the number ofcontrollers can be sufficiently large that the statistical properties of the ensemble dominate over specificdetails of individual elements. Such systems have become known as smart matter [1]. Unlike traditionalmatter, the components are capable of complex continuous and discrete actions. Such changes in capabil-ity will require control algorithms capable of operating a multitude of interconnected discrete and con-tinuous sensors, actuators, and control systems in a robust and adaptable manner. In this paper, some ofthe challenges associated with creating such hybrid control systems for large numbers of components willbe discussed along with some of our initial work in this area.The development of smart matter control systems requires solutions to a number of problems. Because ofthe time, cost, and communication constraints imposed on smart matter, algorithms must be able to takeadvantage of the strengths of the particular hardware configuration and be very efficient. The problemsmust be solved within the imposed control loop time and with minimal processing power in order tominimize the costs of many controllers. Some of the critical areas requiring advancement include sensorfusion, goal or responsibility assignment, and actuator allocation.The sensor fusion problem involves the use of a large number of discrete sensors to obtain an accurateestimate of the (possibly continuous) state of the system being controlled (Fig. 1). Information from manysimilar sources such as arrays of identical optical sensors or from different modalities such as visual andauditory must be combined. Inaccurate and missing data must be handled and the remaining informationfused optimally into a measure of the state. Because the dimensionality of the state of the system is oftensignificantly less than the number of sensors for smart matter systems, sensor fusion is the creation of amany-to-few mapping between sensor outputs and the system state. Moreover, because most control sys-tems require knowledge about the rate of change of the state of the system, continuous and smooth fusionof the sensor data is required even though the data is derived from discrete sensors. Thus, the sensor fu-sion problem is both a many-to-few mapping problem and a discrete-to-continuous hybrid transformationproblem.Goal allocation refers to the decomposition of the goal of the system to a collection of control subsys-tems. The goal may be discrete or continuous, and it typically must be implemented by a collection ofcontrollers (Fig. 1). Responsibility for meeting the goal can be passed either continuously or discontinu-ously between controllers. In either case, the controllers must work together in a continuous fashion de-spite being distinct controllers. This allocation of goals amongst a large number of controllers is anotherdifficult problem that must be solved for robust implementation of effective smart matter controllers.The actuation allocation problem is in many respects the inverse problem to the sensor fusion problem(Fig. 1). Once the control system has decided on a control action, this action must be allocated to a dis-crete set of actuators. These actuators are often discrete components, such as valves, switches, or relays.Because typically a large number of actuators must implement a small number of actions, there are many