By João M. Lemos, Rui Neves-Silva, José M. Igreja (auth.)
This booklet describes tools for adaptive regulate of distributed-collector sun fields: vegetation that acquire solar power and carry it in thermal shape. Controller layout equipment are offered which can triumph over problems present in those form of plants:
- they are distributed-parameter structures, i.e., structures with dynamics that depend upon area in addition to time;
- their dynamics is nonlinear, with a bilinear structure;
- there is an important point of uncertainty in plant knowledge.
Adaptive tools shape the point of interest of the textual content as a result measure of uncertainty within the wisdom of plant dynamics. components of the textual content are dedicated to layout tools that imagine just a very constrained wisdom in regards to the plant. different elements element tools that depend upon wisdom of the dominant plant constitution. those tools are extra plant particular, yet permit the development of performance.
Adaptive keep an eye on of solar power Collector Systems demonstrates the dynamics of sunlight fields to be wealthy adequate to provide a problem to the regulate dressmaker whereas, whilst, easy sufficient to permit analytic paintings to be performed, delivering case reviews on dynamics and nonlinear keep an eye on layout in an easy and revealing, yet nontrivial way.
The keep watch over techniques handled during this monograph could be generalized to use to different crops modelled by means of hyperbolic partial differential equations, particularly approach crops within which delivery phenomena take place, vegetation like dryers, steam super-heaters or even road traffic.
An vital instance, used many times during the textual content, is a distributed-collector sunlight box put in at Plataforma sunlight de Almeria, situated in southern Spain. The keep an eye on algorithms specified by the textual content are illustrated with experimental effects generated from this plant.
Although the first concentration of this monograph is solar power collector, the diversity of different structures that may enjoy the tools defined will make it of curiosity to regulate engineers operating in lots of industries in addition to to educational regulate researchers attracted to adaptive keep watch over and its applications.
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Extra info for Adaptive Control of Solar Energy Collector Systems
2005) and Cirre et al. (2007). The inclusion of constraints in feedback linearization in relation to distributed collector solar fields is considered in Roca et al. (2009). Also departing from the partial differential equation model of the plant, Johansen and Storaa (2002) proposes a design based on Lyapunov methods, using internal energy as Lyapunov function. Lyapunov methods, but using a quadratic function, are also the realm of Carotenuto et al. (1985, 1986). Optimal and suboptimal control laws are considered in Orbach et al.
In: Allgöwer F, Zheng A (eds) Nonlinear model predictive control. Birkhäuser Verlag, Basel, pp 181–190 Lemos JM (2006) Adaptive control of distributed collector solar fields. Int J Syst Sci 37(8):523–533 Meaburn A, Hughes FM (1993) Resonance characteristics of a distributed solar collector fields. Solar Energy 51(3):215–221 Meaburn A, Hughes FM (1994) Prescheduled adaptive control scheme for ressonance cancellation of a distributed solar collector field. Solar Energy 52(2):155–166 Miller FP, Vandome AF, McBrewster J (2010) Concentrating solar power.
In general, for computing T (z, t + αt), while z is in a grid point, z − u(t)αt is not, and hence T (z − u(t)αt) is not in the computer memory from the last iteration. One possibility to obtain T (z − u(t)αt) is then to approximate this quantity by interpolating the values of T at time t in neighboring points. Another possibility consists of using a varying time step αt such that u(t)αt is constant and equal to the spatial grid increment αz. As shown in Chap. 5, this option leads to predictive control algorithms with a variable time step that have the advantage of allowing fast setpoint changes without overshoot.