Computer-directed distributed control systems

Process control systems have increased in complexity as electronic control systems were replaced by computer-directed distributed control systems (DCS). Gone are the control rooms full of panels and gauges, switches, meters, and charts. They have been replaced with something that looks like a space shuttle control panel. Processes run faster, more safely, and produce higher quality product using the latest methods of statistical quality control. Improvements in information technology make it possible for the employees to know almost immediately what each piece of equipment under their control is doing. 

Control System Included in this classification are Supervisory Control and Data Acquisition Systems (SCADA), Distributed Control Systems (DCS), Statistical Process Control systems (SPC), Programmable Logic Controllers (PLCs), intelligent electronic devices, and computer systems that control manufacturing equipment or receive data directly from manufacturing equipment PLCs. 

Modern process MS analyzers are controlled by microcontrollers and PC computers. Many incorporate internal processors that permit stand-alone operation, with a PC only required for initial configuration. The processor then handles all measurement and quantitation, as well as data interfacing, fault diagnosis and alarming, and calibration. Process mass spectrometers can be directly interfaced to plant distributed control systems, programmable loop controllers, or other process control systems. 

Computer systems are used worldwide in the pharmaceutical industry and have direct bearing on product quality. The purpose of validation is to demonstrate that the intended product manufactured, packed, or distributed using a computerized controlled system will meet the safety, efficacy, and potency requirements per the individual monograph. 

Two other computer facilities are a data collection system which monitors remotely located data acquisition and experiment-control computers via asynchronous serial lines and the two Evans and Sutherland LDS-1 interactive graphics terminals. A PDP 10 included in the network configuration as an alternate file transport concentrator and auxiliary network development machine also performs the role of worker computer with the Evans and Sutherland display equipment. Other subnetworks have been designed for inclusion in the Octopus network to direct the on-line operation of LLL high-speed printer and microfilm recorder output facilities, to administer a second, expanded television monitor system providing 256 channels of video input for distribution to 512 additional monitors, and to control a CDC on-line tape library of 8.7 x 10 bits scheduled for delivery in 1975. The Computer Hardcopy Output Recording System (CHORS) concentrators are two Modcomp II computers, and TMDS-II will utilize two PDP 11/45s both subnetworks are to become operational during the... 

The chip is a standalone microsensor system that does not need any external measurement equipment for sensor control and readout. The sensor system chip has been connected to a computer via an f C-to-USB converter box, i.e., in this box is a microcontroller that translates the I C format coming from the chip into USB format for the computer or laptop. The power supply of the chip is also provided by the USB connection. The sensor system can be read out directly by a microcontroller and is, therefore, well suited for handheld devices or distributed sensor networks. 

The prototype TFRT instrument consists of a thin-film resistive heater, two fans, thermocouple, controller, software, and a computer. The heating element has an effective face area of 15 x 15 mm and a resistance of 15 2 (Fig. 1A). The PCR capillaries are coupled directly to the heater. For cooling, two fans are positioned on opposite sides of the test section. The fans and the heating element are powered by 9VDC (see Note 1). The system temperature is sensed by a thermocouple (see Notes 2 and 3) mounted inside a capillary and mounted on the heater in a symmetrical fashion to the capillaries that hold the PCR mixtures. For prototype development, thermocouples were mounted in each of the capillaries to map the temperature distribution on the surface of the heating element. 

Using a direct search technique on the performance index and the steepest ascent method, Seinfeld and Kumar (1968) reported computational results on non-linear distributed systems. Computational results were also reported by Paynter et al. (1969). Both the gradient and the accelerated gradient methods were used and reported (Beveridge and Schechter, 1970 Wilde, 1964). All the reported computational results were carried out through discretization. However, the property of hyperbolic systems makes them solvable without discretization. This property was first used by Chang and Bankoff (1969). The method of characteristics (Lapidus, I962a,b) was used to synthesize the optimal control laws of the hyperbolic systems. 

Power input can be supplied by an AC or DC power supply and recorded by multimeters with signals sent directly to a personal computer which can be used to control the entire system. The heat source should be well insulated to reduce convective losses to the environment. A number of temperature sensors are attached to the heat pipe surfaces to measure the temperature distribution along the heat pipe and temperature variation with power input. All of the measured data are sent to a data acquisition system controlled by a personal computer. Prior to the start of the experiment, the system is allowed to equilibrate and reach steady state such that the temperatures of the cooling media and the heat pipe are constant. When the desired steady-state condition has been obtained, the input power is increased in small increments. Previous tests indicate that a time of approximately 5-30 min is necessary to reach a steady state. To obtain the data for the next successive power level, the power is incremented every 5-30 min. During the tests, the power input and the temperature data are simultaneously recorded using a data acquisition system controlled by a personal computer. 

Finally, finite-element models have potential sqiplicability in CAD of prosthetic sockets. Current prosthetic CAD systems emulate the hand-rectification process, whereby the socket geometry is manipulated to control the force distribution on the residual limb. Incorporation of the finite-element technique into future CAD would enable prescription of the desired interface stress distribution (i.e., based on tissue tolerance). The CAD would then compute the shape of the new socket that would theoretically yield this optimal load distribution. In this manner, prosthetic design would be directly based on the residual limb-prosthetic socket interface stresses. 

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