scispace - formally typeset
Search or ask a question
Author

Ruth Bars

Bio: Ruth Bars is an academic researcher from Budapest University of Technology and Economics. The author has contributed to research in topics: Model predictive control & Control system. The author has an hindex of 9, co-authored 78 publications receiving 376 citations.


Papers
More filters
Book
17 Oct 2011
TL;DR: This practical book discusses topics such as the handling of on-off control, nonlinearities and numerical problems, and gives guidelines and methods for reducing the computational demand for real-time applications.
Abstract: Describing the principles and applications of single input, single output and multivariable predictive control in a simple and lively manner, this practical book discusses topics such as the handling of on-off control, nonlinearities and numerical problems. It gives guidelines and methods for reducing the computational demand for real-time applications. With its many examples and several case studies (incl. injection molding machine and waste water treatment) and industrial applications (stripping column, distillation column, furnace) this is invaluable reading for students and engineers who would wish to understand and apply predictive control in a wide variety of process engineering application areas.

62 citations

Journal ArticleDOI
TL;DR: The status report gives an overview of the current key problems in control theory and design, evaluates the recent major accomplishments and forecasts some new areas.

43 citations

Journal ArticleDOI
TL;DR: Three predictive control algorithms based on a Volterra model are considered and applied and compared in simulation to control a Wiener model, and are used for real-time control of a chemical pilot plant.
Abstract: There is a large demand to apply nonlinear algorithms to control nonlinear systems. With algorithms considering the process nonlinearities, better control performance is expected in the whole operating range than with linear control algorithms. Three predictive control algorithms based on a Volterra model are considered. The iterative predictive control algorithm to solve the complete nonlinear problem uses the non-autoregressive Volterra model calculated from the identified autoregressive Volterra model. Two algorithms for a reduced nonlinear optimization problem are considered for the unconstrained case, where an analytic control expression can be given. The performance of the three algorithms is analyzed and compared for reference signal tracking and disturbance rejection. The algorithms are applied and compared in simulation to control a Wiener model, and are used for real-time control of a chemical pilot plant. Copyright © 2009 John Wiley & Sons, Ltd.

19 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: The time has arrived for virtual and remote labs to make use of the facilities that the World Wide Web provides and the replacement of traditional laboratories with virtual or remote laboratories is presented.

381 citations

Journal ArticleDOI
TL;DR: The problem formulation for solving the multiple constant multiplication (MCM) problem is introduced where first the minimum number of shifts that are needed is computed, and then the number of additions is minimized using common subexpression elimination.
Abstract: Many applications in DSP, telecommunications, graphics, and control have computations that either involve a large number of multiplications of one variable with several constants, or can easily be transformed to that form. A proper optimization of this part of the computation, which we call the multiple constant multiplication (MCM) problem, often results in a significant improvement in several key design metrics, such as throughput, area, and power. However, until now little attention has been paid to the MCM problem. After defining the MCM problem, we introduce an effective problem formulation for solving it where first the minimum number of shifts that are needed is computed, and then the number of additions is minimized using common subexpression elimination. The algorithm for common subexpression elimination is based on an iterative pairwise matching heuristic. The power of the MCM approach is augmented by preprocessing the computation structure with a new scaling transformation that reduces the number of shifts and additions. An efficient branch and bound algorithm for applying the scaling transformation has also been developed. The flexibility of the MCM problem formulation enables the application of the iterative pairwise matching algorithm to several other important and common high level synthesis tasks, such as the minimization of the number of operations in constant matrix-vector multiplications, linear transforms, and single and multiple polynomial evaluations. All applications are illustrated by a number of benchmarks.

362 citations

Journal ArticleDOI
TL;DR: In this article, the development of MPC theory and industrial applications are briefly reviewed and the limitations of current model predictive control theory and technology are analyzed, and the necessity to strengthen the MPC research with respect to enhancing its effectiveness, scientificness, and usability is pointed out.

254 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present various optimization criteria used by researchers for optimal placement of piezoelectric sensors and actuators on a smart structure, including modal forces/moments applied by actuators, maximizing deflection of the host structure, minimizing control effort/maximizing energy dissipated, maximizing degree of controllability, and minimizing degree of observability.
Abstract: This article presents in a unified way, the various optimization criteria used by researchers for optimal placement of piezoelectric sensors and actuators on a smart structure. The article discusses optimal placement of piezoelectric sensors and actuators based upon six criteria: (i) maximizing modal forces/moments applied by piezoelectric actuators, (ii) maximizing deflection of the host structure, (iii) minimizing control effort/maximizing energy dissipated, (iv) maximizing degree of controllability, (v) maximizing degree of observability, and (vi) minimizing spill-over effects. Optimal piezoelectric sensor and actuator locations on beam and plate structures for each criterion and modes of interest are presented in a tabular form. This technical review has two objectives: (i) practicing engineers can pick the most suitable philosophy for their end application and (ii) researchers can come to know about potential gaps in this area.

246 citations

Journal ArticleDOI
TL;DR: In this paper, a survey of underactuated mechanical systems (UMS) is presented, from its history to the state-of-the-art research on modelling, classification, control, and to some extent, provides some unique insights for bottleneck issues and future research directions.
Abstract: An underactuated mechanical system (UMS) is a system which has fewer independent control actuators than degrees of freedom to be controlled. Control of UMS is considered as one of the most active fields of research because of its diverse engineering applications. This survey reviews UMS from its history to the state-of-the-art research on modelling, classification, control, and to some extent, provides some unique insights for bottleneck issues and future research directions.

238 citations