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ADAPTIVE CONTROL OF A SOLAR ENERGY PLANT: EXPLOITING ACCESSIBLE DISTURBANCES

This paper deals with temperature control in an industrial-scale distributed collector solar field. The need for adaptive control arises from the highly time-varying behaviour of both the plant dynamics and the solar radiation effects in the collector field due to atmospheric changes. The control problem consists of keeping constant the field outlet oil temperature by acting on the oil flow. The manipulated variable is chosen so as to minimize a receding horizon quadratic cost. The underlying control law is of model-based predictive control type, adaptively implemented by a MUSMAR algorithm, modified so as to exploit the information conveyed by the accessible disturbances. Experimental results are reported showing the significance on the achievable performance of the feedforward term depending on the accessible disturbances.

Cascade control of a distributed collector solar field

Abstract This paper reports experimental results on the cascade control of a distributed collector solar field. The control problem consists of keeping constant the field outlet oil temperature by acting on the circulating oil flow used for heat transfer. In the inner loop an adaptive model based predictive controller exploiting the information conveyed by accessible disturbances (radiation changes and inlet oil temperature) is used, while in the outer loop a PID is employed. The need for adaptive control arises from the time varying behaviour of the plant. Due to the generality of the methods employed, the experience reported is relevant to a wide class of industrial processes.

Discrete-time differential systems

In this paper we formulate a coherent discrete-time signals and systems theory taking derivative concepts as basis. Two derivatives - nabla (forward) and delta (backward) - are defined and generalized to fractional orders, obtaining two formulations that are discrete versions of the well-known Grunwald-Letnikov derivatives. The eigenfunctions of such derivatives are the so-called nabla and delta exponentials. With these exponentials two generalized discrete-time Laplace transforms are deduced and their properties studied. These transforms are back compatible with the current Laplace and Z transforms. They are used to study the discrete-time linear systems defined by differential equations. These equations although discrete mimic the usual continuous-time equations that are uniformly approximated when the sampling interval becomes small. Impulse response and transfer function notions are introduced and obtained. The Fourier transform and the frequency response are also considered. This implies a unified mathematical framework that allows us to approximate the classic continuous-time case when the sampling rate is high or obtain the current discrete-time case based on difference equation. HighlightsPresents a coherent approach to the nabla and delta derivatives of an order.Finds the nabla and delta exponentials and their properties.Introduces nabla and delta Laplace transforms.Uses the nabla Laplace transform to study the fractional linear systems.

SMCRVI - a Labview/Matlab based tool for remote monitoring and control

Modeling and dynamic simulation are now basic tools for understanding and verifying theoretical subjects. However, the experimentation with a plant cannot be replaced by simulation. Laboratory experiments play and will certainly play an important role in control-engineering education. The high number of students and the limitations of economic resources require an efficient use of laboratory experiments. This paper presents SMCRVI - a tool that combines the use of Matlab and Labview to allow students to gain remote access to laboratory experiments. By means of a client/server architecture students are able to share online experiment data and to perform practical tests, without leaving their Matlab environment

System initial conditions vs derivative initial conditions

The alternative system initial conditions versus the derivative initial conditions is focused in this paper. It is shown that Riemann-Liouville and Caputo initial conditions result from the corresponding derivative and not necessarily from the system at hand. To setup the correct system initialization, a formulation generalizing the integer order approach is presented. This is based on a generalization to the fractional environment of the well known jump formula. The obtained scheme is very general and does not depend on any transform. Besides, it can also be used in the time variant case. The Riemann-Liouville and Caputo initial conditions are interpreted in terms of this general framework and deduced equations where they are correct.

Architecture for remote laboratories based on REST web services

In this paper, a new architecture for remote laboratories based on REST (Representational State Transfer) web services is proposed. The proposed platform use languages such as HTML, AJAX (asynchronous Javascript and XML) and Labview. A web browser is the client interface and on the server side runs an application based on Labview 8.6 with REST web resources. The main contributions are: a) the proposed architecture; b) a “thin client“ based on a browser requiring a low bandwidth. Experimental tests, using an analog process simulator, were done and the obtained results show a good performance.

A new look into the discrete-time fractional calculus: derivatives and exponentials

Abstract A derivative based discrete-time signal processing is presented. Both nabla (forward) and delta (backward) derivatives are studied and generalised including the fractional case. The corresponding exponentials are introduced as eigenfunctions of such derivatives.

Process control based on PCA models

In this paper an approach to design controllers based on principal components analysis (PCA) models is presented. Closed-loop control can be formulated and implemented within the reduced space defined by a PCA model. This PCA controller, results in an integral controller, which can be used as an inferential controller when a measurement of a primary variable is not available. The main contributions of the paper are: a) the incorporation of an adjustable gain on the classical PCA controller; b) the proposal of a set of tuning rules; c) the performance evaluation of this new controller, in nominal operation conditions and in faulty situations. Some experimental results, obtained with the three tank benchmark (European COSY project), are presented.

A remote laboratory environment for blended learning

In this paper, a remote laboratory environment for blended learning is described. The main contributions are: a) the architecture proposed that facilitates the student-centered learning; b) an environment that improves the students learning process; c) the set of experiments available that can be easily incorporated in an e-learning platform. The Labview® platform was used on the server, a data acquisition board (NI-USB-6009) interfaces with the real setups, and the clients access remotely using a web-browser. The practice showed that the proposed remote laboratory can be used, not only for local experiments in a laboratory, but also for e-teaching and e-learning activities using a remote laboratory.

Diagnosis of Parametric Faults Based on Identification and Statistical Methods

This paper proposes a fault diagnosis approach for detection and diagnosis of parametric faults in linear dynamical systems. It is assumed that the system is modeled by an auto-regressive (ARX) model, and a recursive least-squares (RLS) algorithm with variable forgetting factor is used for online parameter identification. The fault detection task is done using a statistical principal component analysis (PCA) method applied to ARX parameters. The fault isolation is done using an influence matrix method. The proposed methodology is applied to a simulation model of a DC motor under closed-loop control, and the performance is discussed.