Topic
Control variable
About: Control variable is a research topic. Over the lifetime, 4378 publications have been published within this topic receiving 59753 citations. The topic is also known as: experimental constant & constant.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this paper, a new method of digital process control is described, which relies on three principles: 1) the multivariable plant is represented by its impulse responses which will be used on line by the control computer for long range prediction; 2) the behavior of the closed-loop system is prescribed by means of reference trajectories initiated on the actual outputs; 3) the control variables are computed in a heuristic way with the same procedure used in identification, which appears as a dual of the control under this formulation.
1,835 citations
TL;DR: A practical method is given for solving the power flow problem with control variables such as real and reactive power and transformer ratios automatically adjusted to minimize instantaneous costs or losses by Newton's method, a gradient adjustment algorithm for obtaining the minimum and penalty functions to account for dependent constraints.
Abstract: A practical method is given for solving the power flow problem with control variables such as real and reactive power and transformer ratios automatically adjusted to minimize instantaneous costs or losses. The solution is feasible with respect to constraints on control variables and dependent variables such as load voltages, reactive sources, and tie line power angles. The method is based on power flow solution by Newton's method, a gradient adjustment algorithm for obtaining the minimum and penalty functions to account for dependent constraints. A test program solves problems of 500 nodes. Only a small extension of the power flow program is required to implement the method.
1,575 citations
TL;DR: In this paper, the problem of controlling a system with constant but unknown parameters is considered and an algorithm obtained by combining a least squares estimator with a minimum variance regulator computed from the estimated model is analyzed.
1,404 citations
TL;DR: This paper conducted an in-depth review and content analysis of what variables, and why such variables are controlled for, in 10 of the most popular research domains (task performance, organizational citizenship behaviors, turnover, job satisfaction, organizational commitment, employee burnout, personality, leader member exchange, organizational justice, and affect) in organizational behavior/human resource management (OB/HRM) and applied psychology.
Abstract: The use of control variables plays a central role in organizational research due to practical difficulties associated with the implementation of experimental and quasi-experimental designs. As such, we conducted an in-depth review and content analysis of what variables, and why such variables are controlled for, in 10 of the most popular research domains (task performance, organizational citizenship behaviors, turnover, job satisfaction, organizational commitment, employee burnout, personality, leader‒member exchange, organizational justice, and affect) in organizational behavior/human resource management (OB/HRM) and applied psychology. Specifically, we examined 580 articles published from 2003 to 2012 in AMJ, ASQ, JAP, JOM, and PPsych. Results indicate that, across research domains with clearly distinct theoretical bases, the overwhelming majority of the more than 3,500 controls identified in our review converge around the same simple demographic factors (i.e., gender, age, tenure), very little effort is made to explain why and how controls relate to focal variables of interest, and control variable practices have not changed much over the past decade. To address these results, we offer best-practice recommendations in the form of a sequence of questions and subsequent steps that can be followed to make decisions on the appropriateness of including a specific control variable within a particular theoretical framework, research domain, and empirical study. Our recommendations can be used by authors as well as journal editors and reviewers to improve the transparency and appropriateness of practices regarding control variable usage.
855 citations
TL;DR: The maximum principle for nonlinear stochastic optimal control problems in the general case was proved in this article, where the control domain need not be convex, and the diffusion coefficient can contain a control variable.
Abstract: The maximum principle for nonlinear stochastic optimal control problems in the general case is proved. The control domain need not be convex, and the diffusion coefficient can contain a control variable.
725 citations