Controls and Control Theory Commons^™

Design And Evaluation Of Processes For Fuel Fabrication: Quarterly Progress Report #7, Georg F. Mauer

Fuels Campaign (TRP)

The seventh quarter of the project covered the following:

• Mr. Richard Silva continued the development of a simulation model with a Waelischmiller hot cell robot. Rich will continue to develop detailed 3-D process simulation models as his M.Sc. thesis project.

• Mr. Richard Silva presented a paper on hot cell robotics at the ANS student conference in Berkeley, CA.

• Concepts and Methods for Vision-Based Hot Cell Supervision and control, focusing on rule-based object recognition (Ph.D. Student Jae-Kyu Lee)

• Undergraduate student Jamil Renno, developed better control algorithms, and created simulations of pick and place actions for the hot …

Design And Evaluation Of Processes For Fuel Fabrication: Quarterly Progress Report #6, Georg F. Mauer

Fuels Campaign (TRP)

The sixth quarter of the project covered the following:

• Mr. Richard Silva continued the development of a simulation model with a Waelischmiller hot cell robot. Rich will continue to develop detailed 3-D process simulation models as his M.Sc. thesis project. Rich is employed with Bechtel at the Yucca Mountain project.

• Concepts and Methods for Vision-Based Hot Cell Supervision and control (Ph.D. Student Jae-Kyu Lee )

• An undergraduate senior student in mechanical engineering, Mr. Jamil Renno, was hired to develop the simulation model for the hot cell manipulator.

Funções De Base Em Modelos Rbf: Um Estudo De Caso Na Modelagem Do Sistema De Lorenz, Gladstone B. Alves, Luis A. Aguirre

Gladstone B. Alves

No abstract provided.

Otimização Baseada Na Quimiotaxia Social De Bactérias: Introdução E Perspectivas, Gladstone B. Alves

Gladstone B. Alves

No abstract provided.

An Outline And Further Development Of Smith Predictor Based Methods For The Compensation Of Processes With Time Delay, Pauline Sourdille, Aidan O'Dwyer

Conference papers

An extensive literature review is presented and a new modified Smith predictor is subsequently presented.

Analytical Ise Calculation And Optimum Control System Design, Tony Kealy, Aidan O'Dwyer

Conference papers

In control system theory, a performance index is a quantitative measure of the performance of a system and is chosen so that emphasis is given to the important system parameters. In this paper, the authors demonstrate two methods to determine analytically the ISE performance index value for a FOPDT process model under PI control. The ability of proportional/integral (PI) and proportional/integral/derivative (PID) controllers to compensate most practical industrial processes has led to their wide acceptance in industrial applications. The most direct way to set up PI/PID controller parameters is the use of tuning rules. The second part of this paper …

System Identification Using Higher Order Spectra, Aidan O'Dwyer

Conference papers

This communication will explore the use of particular types of frequency domain concepts, labelled higher order spectra, to help determine the frequency response of a process. This will allow the identification of the parameters of a single input, single output (SISO) model for a process (which includes a time delay), in both open loop and closed loop environments.

On Stability Of Affine Blending Systems, Ruiyao Gao, Aidan O'Dwyer, Seamus Mcloone, Eugene Coyle

Conference papers

This paper presents a novel approach to stability analysis of affine blending systems. The analysis is based on Quadratic Lyapunov functions. The approach considers the nonlinear offset term in affine blending systems as non-vanishing perturbations added to the corresponding nominal linear blending systems. The affine blending systems will be bounded if the corresponding linear blending system is exponentially stable. The bound is determined by an ultimate limit, which is proportional to the maximum of the offset terms of each affine system.

New Modified Smith Predictor Designs, Pauline Sourdille, Aidan O'Dwyer

Conference papers

By combining several existing modified Smith predictor structures, presented in a literature review, a generalised form of the Smith predictor is proposed. From this structure, excellent servo and regulator responses can be obtained by specifying three controller dynamic elements. Two new modified Smith predictor structures are presented with their associated tuning rules. The results of the simulations indicate that the two new designs give better overall responses than the original Smith predictor.

Pid Compensation Of Time Delayed Processes 1998-2002: A Survey, Aidan O'Dwyer

Conference papers

A time delay may be defined as the time interval between the start of an event at one point in a system and its resulting action at another point in the system. Delays are also known as transport lags or dead times; they arise in physical, chemical, biological and economic systems, as well as in the process of measurement and computation. Methods for the compensation of time delayed processes may be broadly divided into proportional integral derivative (PID) based controllers, in which the controller parameters are adapted to the controller structure, and structurally optimised controllers, in which the controller structure …

Comparison Of Process Identification Techniques In The Time And Frequency Domains, Tony Kealy, Aidan O'Dwyer

Conference papers

This paper describes ten methods to identify a mathematical model for a real process with a time delay. The process is the Process Trainer, PT326 from Feedback Instruments Limited. Six of the methods use step response data and one of the methods uses impulse response data for identification. Two of the methods use frequency response data and the final method uses information from relay-based experiments. The best results are obtained using a combined analytical and gradient method [6] in the frequency-domain and, in the time-domain, using the two-point algorithm [1] and a method proposed by Suganda et al. [5].

A New Modified Smith Predictor Design, Pauline Sourdille, Aidan O'Dwyer

Conference papers

A new modified Smith predictor structure is presented with its associated tuning rules.

Autonomous Vehicles Research Laboratory – Phase Ii: Mobile Robots And A Walking Internet, Raúl Ordóñez

Raúl Ordóñez

PI, Funded by the University of Dayton Research Council, $8,000.

Decentralized Adaptive Coordination And Control Of Uninhabited Autonomous Vehicles Via Surrogate Optimization, Raúl Ordóñez

Raúl Ordóñez

No abstract provided.

Comparison Of Open- And Closed-Loop Process Identification Techniques In The Time-Domain, Tony Kealy, Aidan O'Dwyer

Conference papers

Abstract: This paper describes seven methods to identify a mathematical model for a real process with a time delay. The process is the Process Trainer, PT326 from Feedback Instruments Limited. Six of the methods use the step response data and one of the methods uses the impulse response data for identification.

Implementation Of Large Neural Networks Using Decomposition, Henry Selvaraj, H. Niewiadomski, P. Buciak, M. Pleban, Piotr Sapiecha, Tadeusz Luba, Venkatesan Muthukumar

Electrical & Computer Engineering Faculty Research

The article presents methods of dealing with huge data in the domain of neural networks. The decomposition of neural networks is introduced and its efficiency is proved by the authors’ experiments. The examinations of the effectiveness of argument reduction in the above filed, are presented. Authors indicate, that decomposition is capable of reducing the size and the complexity of the learned data, and thus it makes the learning process faster or, while dealing with large data, possible. According to the authors experiments, in some cases, argument reduction, makes the learning process harder.

Closed Loop Identification Of A First Order Plus Dead Time Process Model Under Pi Control, Tony Kealy, Aidan O'Dwyer

Conference papers

Abstract -- This paper discusses the estimation of the parameters of a first order plus dead-time process model using the closed-loop step response data of the process under proportional plus integral (PI) control. The proportional gain and the integral time, in the PI controller, are chosen such that the closed-loop step response exhibits an under-damped response. From this response data, five characteristic points are used to determine a second order plus dead-time model and subsequently, the frequency response of the closed-loop system. Knowing the dynamics of the closed-loop system and the dynamics of the controller, the open-loop dynamics of the …

From Linear To Nonlinear Control Means: A Practical Progression, Zhiqiang Gao

Electrical and Computer Engineering Faculty Publications

With the rapid advance of digital control hardware, it is time to take the simple but effective proportional-integral-derivative (PID) control technology to the next level of performance and robustness. For this purpose, a nonlinear PID and active disturbance rejection framework are introduced in this paper. It complements the existing theory in that (1) it actively and systematically explores the use of nonlinear control mechanisms for better performance, even for linear plants; (2) it represents a control strategy that is rather independent of mathematical models of the plants, thus achieving inherent robustness and reducing design complexity. Stability analysis, as well as …

A Stable Self-Tuning Fuzzy Logic Control System For Industrial Temperature Regulation, Zhiqiang Gao, Thomas A. Trautzsch, James G. Dawson

Electrical and Computer Engineering Faculty Publications

A closed-loop control system incorporating fuzzy logic has been developed for a class of industrial temperature control problems. A unique fuzzy logic controller (FLC) structure with an efficient realization and a small rule base that can be easily implemented in existing industrial controllers was proposed. The potential of FLC in both software simulation and hardware test in an industrial setting was demonstrated. This includes compensating for thermo mass changes in the system, dealing with unknown and variable delays, operating at very different temperature set points without retuning, etc. It is achieved by implementing, in the FLC, a classical control strategy …

Using Prior Information In The Structure Selection Of Rbf Network Models, Gladstone B. Alves, Marcelo V. Corrêa

Gladstone B. Alves

No abstract provided.

Searching For Dynamical Resemblance Between Time Series - A Method Based On Nonlinear Autoregressive Models, Gladstone B. Alves, Marcelo V. Corrêa, Viviane C. Silva

Gladstone B. Alves

No abstract provided.

Multiple Model Networks In Non-Linear System Modelling For Control – A Review, Ruiyao Gao, Aidan O'Dwyer

Conference papers

Non-linear processes, by their nature, are non-uniform and invariably require custom designed control schemes to deal with individual characteristics. No general theory deals comprehensively with the wide range of non-linear systems encountered. In an attempt to accurately model non-linear dynamical systems, a wide variety of techniques have been developed such as non-linear auto-regressive moving average with exogeneous inputs (NARMAX) models (Chen and Billings, 1989), Weiner models (Schetzen, 1981), Hammerstein models (Billings and Fakhouri, 1982) and Multiple Layer Perceptron (MLP) neural networks (Narendra and Kannan, 1990). While the accuracy of such models offers a potentially significant improvement over linear models, the …

Model Predictive Control Of Cstr Based On Local Model Networks, Ruiyao Gao, Aidan O'Dwyer, Eugene Coyle

Conference papers

A non-linear predictive controller is presented. It judiciously combines predictive controllers with a local model network utilizing a neural-network-like gating system. It avoids the time consuming quadratic optimization calculation, which is normally necessary in non-linear predictive control. A controller simulation on a Continuous Stirred Tank Reactor (CSTR) case study was shown to be satisfactory both in terms of set point tracking and regulation performance over the entire operating range. Moreover, the inherent integration action in the local predictive controller provides zero static offsets.

Discrete-Time Velocity-Based Multiple Model Networks, Ruiyao Gao, Seamus Mcloone, Eugene Coyle

Conference papers

The velocity-based local model (LM) network is a novel modelling approach that overcomes the lack of interpretability associated with the conventional LM network technique. The global dynamics of the nonlinear network are directly related to the underlying sub-model dynamics. Thus, the velocity-based network is ideally suited to the development of local controller (LC) networks. Furthermore, the local models are continuous-time, velocity-based and linear, providing continuity with established linear theory. To date, research has focused on the continuous-time version of the velocity-based network. The application of digital computer is widely popular in the field of control and, therefore, this paper develops …

A Non-Linear Pid Controller For Cstr Using Local Model Networks, Ruiyao Gao, Aidan O'Dwyer, Eugene Coyle

Conference papers

The basic PID controllers have difficulty in dealing with problems that appear in complex non-linear processes. This paper presents a practical non-linear PID controller that deals with these non-linear difficulties. It utilises a local model (LM) network, which combines a set of local models within an artificial neural network structure, to adaptively characterise the process non-linearity. Then a local controller network is formulated through a gating system deduced from the LMN to handle the non-linearity. A continuous stirred tank reaction (CSTR) case study illustrates the practicality of this method in the modelling and control of non-linear processes. PID controllers are …

Towards An Expert System Approach For Pi Controller Design Of Delayed Processes, Michael Feeney, Aidan O'Dwyer

Conference papers

This paper will discuss the compensation of first order lag plus time delay (FOLPD) processes using PI controllers whose parameters are specified using appropriate tuning rules. The gain margin and phase margin of the compensated system, as the ratio of time delay to time constant of the process varies, are calculated for each tuning rule and an expert system is used to recommend a tuning rule for user defined requirements.

Closed Loop Identification Of A First Order Plus Dead-Time Process Model Under Pi Control, Tony Kealy, Aidan O'Dwyer

Conference papers

This paper discusses the estimation of the parameters of a first order plus dead-time process model using the closed-loop step response data of the process under proportional plus integral (PI) control. The proportional gain and the integral time, in the PI controller, are chosen such that the closed-loop step response exhibits an under-damped response. From this response data, five characteristic points are used to determine a second order plus dead-time model and subsequently, the frequency response of the closed-loop system. Knowing the dynamics of the closed-loop system and the dynamics of the controller, the open-loop dynamics of the process can …

Time Delay Estimation In Signal Processing Applications: An Overview, Aidan O'Dwyer

Conference papers

An extensive though scattered literature exists on the estimation of time delays in signal processing applications. However, it is possible to identify themes that are common to many of the available techniques. The intention of this paper is to provide a framework against which the literature may be viewed. In addition, original work on gradient based time delay estimation is described.

Comparison Of Open And Closed Loop Process Identification Techniques In The Time Domain, Tony Kealy, Aidan O'Dwyer

Conference papers

This paper describes seven methods to identify a mathematical model for a real process with a time delay. The process is the Process Trainer, PT326 from Feedback Instruments Limited. Six of the methods use the step response data and one of the methods uses the impulse response data for identification.

Development Of An Autonomous Vehicles Research Laboratory, Raúl Ordóñez

Raúl Ordóñez

PI, funded by the University of Dayton Research Council, $3,800.