3,764 research outputs found
Feedback linearization control for a distributed solar collector field
This article describes the application of a feedback linearization technique for control of a distributed solar collector field using the energy from solar radiation to heat a fluid. The control target is to track an outlet temperature reference by manipulating the fluid flow rate through the solar field, while attenuating the effect of disturbances (mainly radiation and inlet temperature). The proposed control scheme is very easy to implement, as it uses a numerical approximation of the transport delay and a modification of the classical control scheme to improve startup in such a way that results compared with other control structures under similar conditions are improved while preserving short commissioning times. Experiments in the real plant are also described, demonstrating how operation can be started up efficiently.Ministerio de Ciencia y TecnologĂa DPI2004-07444-C04-04Ministerio de Ciencia y TecnologĂa DPI2005-0286
Vibration suppression in multi-body systems by means of disturbance filter design methods
This paper addresses the problem of interaction in mechanical multi-body systems and shows that subsystem interaction can be considerably minimized while increasing performance if an efficient disturbance model is used. In order to illustrate the advantage of the proposed intelligent disturbance filter, two linear model based techniques are considered: IMC and the model based predictive (MPC) approach. As an illustrative example, multivariable mass-spring-damper and quarter car systems are presented. An adaptation mechanism is introduced to account for linear parameter varying LPV conditions. In this paper we show that, even if the IMC control strategy was not designed for MIMO systems, if a proper filter is used, IMC can successfully deal with disturbance rejection in a multivariable system, and the results obtained are comparable with those obtained by a MIMO predictive control approach. The results suggest that both methods perform equally well, with similar numerical complexity and implementation effort
Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent-Magnet Synchronous Generator
Wind energy is an integral part of nowadays energy supply and one of the
fastest growing sources of electricity in the world today. Accurate models for
wind energy conversion systems (WECSs) are of key interest for the analysis and
control design of present and future energy systems. Existing control-oriented
WECSs models are subject to unstructured simplifications, which have not been
discussed in literature so far. Thus, this technical note presents are thorough
derivation of a physical state-space model for permanent magnet synchronous
generator WECSs. The physical model considers all dynamic effects that
significantly influence the system's power output, including the switching of
the power electronics. Alternatively, the model is formulated in the -
and -reference frame. Secondly, a complete control and operation
management system for the wind regimes II and III and the transition between
the regimes is presented. The control takes practical effects such as input
saturation and integral windup into account. Thirdly, by a structured model
reduction procedure, two state-space models of WECS with reduced complexity are
derived: a non-switching model and a non-switching reduced-order model. The
validity of the models is illustrated and compared through a numerical
simulation study.Comment: 23 pages, 11 figure
Design of generalized minimum variance controllers for nonlinear multivariable systems
The design and implementation of Generalized Minimum Variance control laws for nonlinear multivariable systems that can include severe nonlinearities is considered. The quadratic cost index minimised involves dynamically weighted error and nonlinear control signal costing terms. The aim here is to show the controller obtained is simple to design and implement. The features of the control law are explored. The controller obtained includes an internal model of the process and in one form is a nonlinear version of the Smith Predictor
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