Showing papers on "Control variable published in 1998"

Evidence and inference in the comparative case study

Abstract: Comparative case studies often rely on a practice known as selecting on the dependent variable This technique involves choosing some phenomenon of political interest, gathering data on occurrences of the phenomenon, then determining what characteristics the occurrences have in common A methodological strategy with a long history, selecting on the dependent variable has found numerous applications in political science, including the study of economic growth, social revolutions, and international conflict' Selecting on the dependent variable has provided an important method for gathering information when there is relatively little data, though it is not limited to such situations Its use has recently come under rather sharp attack If observations are selected based on the value of the dependent variable, then estimates obtained by ordinary least squares will be biased This bias can not be corrected by the introduction of control variables Gathering more data will not solve the problem; the bias remains even if the number of observations goes to infinity In short, inferences drawn from cases selected on the dependent variable are highly suspect2 Impressive treatments of the problem from the position of comparative case study work have been presented by Barbara Geddes and by Gary King, Robert Keohane, and Sidney Verba3 They have not only alerted the discipline to an important problem but have suggested concrete ways to deal with problems of selection bias4 I would like to offer a qualified defense of analyses of a small number of cases selected on the dependent variable As is well-known, selecting on the dependent variable is perfectly admissible if one is evaluating necessary (as opposed to sufficient) conditions5 However, with a few exceptions, this argument has gone unnoticed in the debate on case selection6 By concentrating on the logic of testing necessary conditions, this paper attempts to show that the methodological implications of selecting on the dependent variable are much less threatening to the validity of small-n comparative case study work than has often been claimed

Control allocation approaches

Abstract: The control allocation problem is defined in terms of solving or approximately solving a system of linear equations subject to constraints for redundant actuator control variable commands. There is one equation for each controlled axis. The constraints arise from actuation rate and position limits. An axis priority weighting is introduced when the equations cannot be solved exactly because of the constraints. A actuator command preference weighting and preferred values are introduced to uniquely solve the equations when there are more unknowns than equations. Several approaches to this problem are discussed. The approaches are broadly grouped into linear and quadratic programming approaches. While the linear programming approach is well suited to solving the general problem a computationally faster but approximate solution was found with the quadratic programming approach. Example results based on tailless aircraft flight control are presented to illustrate the key aspects of the approaches to control allocation. Conclusions and recommendations are stated relative to the various approaches.

Accelerated simulation for pricing Asian options

Abstract: When pricing options via Monte Carlo simulations, precision can be improved either by performing longer simulations, or by reducing the variance of the estimators. Two methods for variance reduction are combined: the control variable and the change of measure (or likelihood) methods. We specifically consider Asian options, and show that a change of measure can very significantly improve the precision when the option is deeply out of the money, which is the harder estimation problem. We also show that the simulation method itself can be used to find the best change of measure. This is done by incorporating an updating rule, based on an estimate of the gradient of the variance. The paper includes simulation results.

Predictive bursty real-time traffic control for telecommunications switching systems

Abstract: A traffic control system (and associated method) according to the present invention includes a feedback control mechanism in which the controlled variable is processor occupancy, the controlling variable is the amount of resources necessary to satisfy the operational requirements of the switching system, and the set point is the average expected load based on a Poisson arrival rate. Current processor occupancy is compared, on an instantaneous basis against the set point to detenmine if it exceeds the average expected load. If so, the controlling variable is adjusted to allocate additional resources to process the offered traffic load. The process continues until the traffic burst expires. Additional resources may be obtained by eliminating or deferring non-essential work, and by allocating additional call registers, effectively accepting work in larger increments or batches. By instantly and proactively responding to traffic bursts, this traffic control system aids the switching system in weathering brief periods of high traffic, without actually reaching an overload condition and invoking overload controls. As a result, switching system capacity is increased, and other performance characteristics are improved.

Identification and Control of NOx Emissions Using Neural Networks.

Abstract: We investigate the application of two classes of artificial neural networks for the identification and control of discrete-time nonlinear dynamical systems. A fully connected recurrent network is used for process identification, and a multilayer feedforward network is used for process control. The two neural networks are arranged in series for closed-loop control of oxides of nitrogen (NOx) emissions of a simplified representation of a dynamical system. Plant data from one of Commonwealth Edison's coal-fired power plants are used for testing the approach, with initial results indicating that the method is feasible. However, further work is required to determine whether the method remains feasible as the number of state variables and control variables are increased.

An intelligent predictive control approach to path tracking problem of autonomous mobile robot

Abstract: An intelligent predictive control approach to the path tracking problem of an autonomous mobile robot is presented based on the analysis of the characteristics of the vehicle model and the traditional predictive control algorithm. A neural network model of the vehicle is used to predict future vehicle posture according to the current posture and control variables. The future tracking error between this predictive posture and the planned ideal path created by the local path planning module can be calculated. The optimal control variables in the next control instant are computed by the online optimization algorithm. The above process is updated and solved repeatedly. The intelligent predictive controller is composed of four principal components: a reference path, a predictive model, a set of online optimization algorithms and a feedback tuning model, which are discussed in detail in the paper. The characteristic of this method is analyzed and the result is provided.

Canal Control Algorithm Formulations

Abstract: Over the past two decades, numerous automatic control systems have been proposed for irrigation canal operation. Types of automatic control systems range from empirically based, for a one-canal pool, to multivariable multipool procedures, based on the minimization of quadratic performance criteria. Most control algorithms can be expressed in standard control theory terminology, from which properties and characteristics can be determined. The determination of the control action or control variable required to obtain some desired canal operation as a function of the design technique used is presented. The control laws associated with the different design techniques are shown in an RST polynomial form, where R(q−1), S(q−1), and T(q−1) are polynomial matrices in the backward shift operator, q−1, associated with the control variables, controlled variables, and reference profiles, respectively. These expressions clarify the differences between the algorithms and their limitations when they are used in the opera...

Fuzzy inference system to assist the operator in reactive power control in distribution systems

Abstract: The paper proposes a fuzzy inference system to assist the operator for voltage control and power loss minimisation. The reactive power control problem is decoupled from the voltage regulator problem. A fuzzy expert system provides rules for both the problems. The fuzzy inference system acts as the front-end to determine the control variables for the two decoupled problems. An existing 30-bus distribution system is used to demonstrate the effectiveness of the above approach. Simplicity of approach and speed make it a viable option for online Var control.

Discrete-time inventory models with deteriorating items

Abstract: The discrete-time inventory control problem for deteriorating items with deterministic or stochastic demand is considered. The control problem is stated as an optimization problem with constrained control variables. The linear quadratic (LQ) criterion is used to derive the optimal control policy for both deterministic and stochastic demand cases. In the presence of bounded uncertainties, a guaranteed cost control law is also proposed. A numerical example is provided to show the usefulness of the theoretical results.

Method and device for controlling optimum operation of power plant

Abstract: PROBLEM TO BE SOLVED: To carry out the optimalizing control of each power-generation element by multivariable-model prediction control, by estimating a parameter incapable of being directly measured on the basis of the physical models of the power-generation elements and the quantity of state of an input process, and determining optimum-load distribution minimizing the cost of the whole power-plant. SOLUTION: In an optimalizing arithmetic section 114 in an optimalizing system 110, optimalizing arithmetic operation for minimizing the running cost of the whole power-plant is conducted on the basis of the quantity of the state of the power-plant, a parameter estimated by a parameter estimation arithmetic section 112 and the physical model 113 of the power-plant by a mathematical programming method. In a multivariable control system 120, on the other hand, the optimum load of a boiler and the load of a turbine taken in by an optimalizing arithmetic-result input section 122 are taken in by a multivariable control operation section 123, and set as the set values of control operation. In a multivariable control operation section 123, the quantities of states of processes are taken in as a control variable, a disturbance variable and an operation variable, and multivariable control is conducted while using optimalizing arithmetic results as set values.

On the control of manufacturing lines modelled by controlled continuous Petri nets

Abstract: We present a new methodology to study the control of a class of discrete event dynamic systems, opened manufacturing lines and closed manufacturing lines. Our contribution is based on the controlled variable speed continuous Petri net model. The computation of the control variables is made using a classic constrained optimization method. The resulting control solution is used to guide the real system behaviour. Some properties linked to the accessibility problem of the reference input are given. Through illustrative examples, the practical application of this approach issue will be made prominent

Hydraulic control system

Abstract: PROBLEM TO BE SOLVED: To provide a hydraulic control system which can smoothly and timely carry out transition from speed control to position control SOLUTION: The hydraulic control system comprises an actuator 10, a pump 20, an electric motor 30, a servo controller 70, a position sensor 11, a pressure sensor 21, and an encoder 31 for detecting a flow rate The servo controller 70 calculates a controlled variable of a position Ds by performing the calculation of feedback control so as to make a detected position Df follow a position command Dc, a controlled variable of pressure Ps by performing the calculation of the feedback control so as to make a detected pressure Pf follow a pressure command Pc, and a controlled variable of flow rate Qs by performing the calculation of the feedback control so as to make a detected flow rate Qf follow a flow rate command Qc; and carries out the rotation control of the electric motor 30 by selecting a controlled variable having the smallest absolute value among these controlled variables as the controlled variable S By this method, the effect of the variation of a reaction force, etc on transition timing from the speed control to the position control is suppressed because the force control is carried out during transition from the speed control to the position control, and the transition of the control is smoothly carried out COPYRIGHT: (C)2005,JPO&NCIPI

Extrusion process control: modeling, identification, and optimization

Abstract: Our work has been focused on developing a methodology for process control of bulk deformation-specifically, extrusion. A process model is required for control. We state the difficulties which exist with currently available models. An appropriate decomposition and associated assumptions are introduced which permit a real-time process model to be constructed via spectral approximation to solve the axi-symmetric two-dimensional (2D) transient heat conduction equation with heat generation and loss. This solution, simulation results, and model execution times are provided. We use this model development plus output relationships from previous model development work to develop parameter identification and open-loop control methodologies. These methodologies are motivated by the structure and properties of the developed model. We demonstrate that the parameters and control variables enter into the model equations so that the identification and open-loop optimization problems are tractable. An example with plant trial data is provided.

Modelling and robust control of a dam-river system

Abstract: The paper deals with the modelling and the automatic control of a dam-river system, where the action variable is the upstream flow rate and the controlled variable the downstream flow rate. The system is modeled with a linear model (second order transfer function with delay). Two control methods (pole placement and Smith predictor) are compared in terms of performance and robustness. The pole placement is done on the sampled model, whereas the Smith predictor is based on the continuous model. Robustness is estimated with the use of margins, and also with the use of a bound on multiplicative uncertainty for variable reference discharges. Simulations are carried out on a nonlinear model of the river, and performance of both controllers are compared to the one of a continuous-time PID controller.

Variable structure estimation and control of nonlinear distributed parameter bioreactors

Abstract: Estimation and control design issues for distributed parameter bioreactors are discussed in relation to a model consisting of a nonlinear partial differential system. The regulation problem consists of maintaining the substrate concentration at the outlet of the reactor at a desired value. The model describes microbial growth and substrate consumption in a fixed-bed reactor. The behaviour of living organisms is hardly known since biological parameters are time varying over a long period. Moreover, online biomass concentration sensors are not available. Variable structure control systems are known to be robust. A joint estimator of states and parameters and a controller is designed by using the variable structure system approach. The control variable concerned is very smooth and chattering does not exist. The robustness of the different algorithms is shown by means of numerical simulations.

Multivariable process control system

Abstract: PROBLEM TO BE SOLVED: To derive a manipulated variable updated value meeting operation restriction conditions of a control variable by determining the manipulated variable updated value from a predicted value of a controlled variable so that the operation restriction conditions are met. SOLUTION: A control database 11 stores model data including a mathematical expression model representing response characteristics of a process 2 to be controlled and control data including adjustment parameters of model prediction control. A predicted value calculation part 12 predicts a future response of the process 2 to be controlled according to the process data of the process 2 to be controlled and the model data. An evaluation function setting part 13 derives an evaluation function of model prediction control regarding the manipulated variable updated value according to the prediction result of the process. A restriction condition selection setting part 14 compares the prediction result of the process with the operation restriction conditions to derive a search range of the manipulated variable updated value. A manipulated variable calculation part 15 calculates the manipulated variable updated value by numeral optimization from the evaluation function and the search range of the manipulated variable updated value.

Network control system, process management method in this system, and recording medium on which a process management program is recorded

Abstract: In a controlled object, a process variable of a controlled object process is detected by a sensor and its detection time is measured by a timer. A process signal transmitting device transmits, as a process signal, the process variable and the detection time to a control apparatus. A control variable calculating device calculates a control variable based on the received process variable and a control reference value, and transmits a control signal including the control variable and the received process variable detection time to the controlled object. In the controlled object, a control signal receiving device calculates a transmission delay, that is, a difference between control signal reception time that is measured by the timer and the transmitted process variable detection time, corrects the control variable by processing it in accordance with the transmission delay, and drives an actuator by using the corrected control variable.

Transmission electric power control device and control method

Abstract: A transmission electric power control device includes: a coupler 12, detector 13, electric power amplifier 14, error detection means 15, target value generation means 16, gain variable means 17, control calculation means 18, control calculation parameter generation means 19, modulator 20, control variable addition means 21, transmission electric power control means 22, and transmission electric power designation means 23. In this case, the automatic transmission electric power control feedback loop includes: the coupler 12, detector 13, error detection means 15, control calculation means 18, control calculation parameter generation means 19, transmission electric power designation means 23, control variable addition means 21 and gain variable means 17. When the control calculation parameter in the automatic transmission electric power control feedback loop is made variable according to the transmission electric power designation information and also when the convergence offset value of the loop response characteristic is made variable, it is possible to conduct an electric power control of a high dynamic range, high linearity and high accuracy even if the electric power source control of the electric amplifier is conducted for each transmission electric power and the gate bias control is conducted.

Voltage controlled variable inductor

Abstract: A voltage controlled variable inductor provides a rapidly variable inducte for high power frequency dependent circuit applications. Continuously variable inductance values having a high Q factor are obtainable with the application of only a minimal amount of control power.

Method and arrangement for neural modeling of a paper winding device

Abstract: The invention relates to a method for modelling a paper winding device, especially a drum cutting and winding machine. Control variables and influencing variables (70, 80) are determined and stored as a function of time. Said variables are used to determine the strength of the strip (FAW(r)), according to the number of wound layers, or a correlative variable is used and considered as a target variable along with the other relevant control and influenced variables to enable a neuronal network to be trained as a model for a nip (Ni) for said winding device. New data for training the network can be continually obtained during operation of the installation, thereby improving the model. Optimum control parameters can be determined to meet various production requirements by means of an iterative process dependent upon the winding quality (100) which can also be determined from the strength of the strip.

Optical apparatus with a voltage controlled variable density element

Abstract: An optical apparatus capable of performing an image-taking operation in a plurality of image-taking modes includes a selecting part for selecting one image-taking mode from among a plurality of image-taking modes, a variable density element, and a density control part for controlling density of the variable density element, wherein the density control part is capable of controlling the density of the variable density element in a plurality of density control modes and selects one of the plurality of density control modes according to the image-taking mode selected by the selecting part.

Adjustment rule generating and control method and apparatus

Abstract: An adjustment control method and apparatus of this invention assume that a dependency relationship table representing qualitative characteristics, in which manipulated variables are classified in units of change patterns of controlled variables, and are characterized in that an adjustment rule for adjustment is generated. An adjustment control method and apparatus of this invention is characterized in that it is determined whether the current object situation exhibits an exceptional behavior (vibration/saturation), on the basis of selection of an adjusted controlled variable and a manipulated variable obtained from an automatically generated adjustment rule and a past operation in response to an occasionally output deviation. If it is determined that no exceptional behavior is observed, the instruction of the generated adjustment rule is performed, otherwise, the correction amount of the. manipulated variable which is input to the object to be adjusted is given assuming that a predetermined input operation is performed.

Process control method and electronic device manufacture using the same

Abstract: PROBLEM TO BE SOLVED: To make a controlled variable outputted from a controlled system quickly and accurately follow a target and to improve the throughput of a process by appropriately selecting and switching a manipulated variable corresponding to an arithmetic operation and the manipulated variable based on a prescribed output pattern and inputting them to the controlled system. SOLUTION: A pattern generator 18 is constituted so as to output an output pattern H2 set beforehand at the time set beforehand and the output pattern H2 is inputted to one of the input terminals of a switching device 19. To the pattern generator 18, an optimum pattern for satisfying a prescribed condition to the size change of a target value A and disturbance is respectively experimentally (or empirically) obtained and set. The switching device 19 selects one of a temporary manipulated variable H1 obtained corresponding to PID computation from an adder 17 and the output pattern H2 from the pattern generator 18 according to control output I from a changeover controller 20 and outputs it as the manipulated variable G. COPYRIGHT: (C)1999,JPO

Procedure for controlling turbocharged IC engine which has two banks of cylinders

Abstract: A procedure for controlling a turbocharged IC engine which has two banks of cylinders (2,3) has an exhaust turbocharger (4,7) assigned to each cylinder bank. There is a control unit (24) in which an adjusting signal is generated for adjusting at least one turbocharger by consideration of the state variables describing the operating state of the engine. To control the engine, a state variable is measured in the region of the compressor (6,9) of the turbocharger. From the state variable is formed a control variable according to a given set of rules which is passed as an adjusting signal to a final control element (18,19) influencing the effective turbine cross-section.

Autonomous control method and control system

Abstract: PROBLEM TO BE SOLVED: To provide autonomous control method and control system capable of judging the necessity of the reconstruction of a model relating to the effect of the tuning of a parameter and autonomously activating the construction of a control model. SOLUTION: This system is provided with a parameter tuning part 105 for adjusting the specified parameter of the control model 104 so as to dissolve the controlled variable error of the controlled variable of a controlled system 109 and a target value, a control model construction part 103 for constructing the control model 104 by using data at the time of operating the controlled system stored in a data base 110 and a control model construction activation part 101 for activating the control model construction part 103. The control model construction activation part 101 judges whether or not the tuning by the parameter turning part 105 can dissolve the controlled variable error and activates the control model construction part 103 at the time of judging that the tuning can not dissolve the controlled variable error any more.

Shortest time controller of robot

Abstract: PROBLEM TO BE SOLVED: To use torque effectively and perform the work in the shortest time by forming a command to be delivered to a servo control means using acceleration and deceleration constants. SOLUTION: A corresponding relation storage means 4 stores the results obtained by measuring actually or calculating in advance corresponding relation between a controlled variable and load weight using a value of the controlled variable at the time of no load as the reference. A load assumption calculation means 3 assumes a weight of a workpiece based on the controlled variable inside a control means 2 and the corresponding relation of the corresponding relation storage means 4. An optimum operation constant determining means 5 determines the optimum operation constant based on the weight of the workpiece assumed by the load assumption calculation means 3. A command preparation means 1 changes values of acceleration and deceleration constants which are set in advance to values of acceleration and deceleration constants determined by the optimum operation constant determining means 5 to prepare a command newly and again. A control means 2 of a servo motor 6 driving a robot arm uses proportional control of position and proportion of speed and integral control usually.

A system inversion approach to robust set-point regulation

Abstract: We present a novel methodology, based on system inversion, for the set-point regulation of a system with structured uncertainties. The approach consists in choosing a polynomial as the output function and then designing both the controller and the reference input in order to minimize the worst-case settling-time of the set-point regulation, with constraints on the absolute value of the control variable and on the maximum overshoot of the output. A comparison with a traditional methodology, based on the step-response, shows how the overall design is simplified and how the worst-case settling-time can be greatly reduced. Optimization has been performed by means of genetic algorithms.