Optimal control of a solar collector loop using a distributed-lumped model

This paper considers the optimal control of a solar collector loop described by a bilinear distributed parameter model for the collector fluid temperature and a bilinear lumped parameter model for the storage fluid temperature. The objective is to control the collector fluid velocity so as to maximize the net energy collected over a fixed time period. Necessary conditions for optimality, given by a set of equations whose solution yields the optimal control, are derived. It is shown that the optimal control is an open-loop, bang-bang control which depends on two terms: a measurable quantity which depends on the state of the collector fluid, and a quantity which depends on a future knowledge of the weather data. It is also shown that for the case in which only two switches occur during the period of operation, the optimal control depends only on the temperature difference across the collector. Thus, one can construct a feedback on/off controller for the system provided that it is known a priori that only two switches will occur during the time interval under consideration.     

Cascade control of a distributed collector solar field

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.     

Deformation-based interactive texture design using energy optimization

In this paper, we present a novel interactive texture design scheme based on deformation and energy optimization. Given a small sample texture, the design process starts with applying a set of deformation operations to the sample texture to obtain a set of deformed textures. Then local changes to those deformed textures are further made by replacing their local regions with the texture elements interactively selected from other textures. Such a deform–select–replace process is iterated many times until the desired deformed textures are obtained. Finally the deformed textures are composed to form a large texture with graph-cut optimization. By combining the graph-cut algorithm with an energy optimization process, interactive selections of local texture elements are done simply through indicating the positions of texture elements very roughly with a brush tool. Our experimental results demonstrate that the proposed technique can be used for designing a large variety of versatile textures from a single small sample texture, increasing or decreasing the density of texture elements, as well as for synthesizing textures from multiple sources.     

Energy-based control of a distributed solar collector field

Model-based control of the outlet temperature of a distributed solar collector field is studied. An energy-based controller is derived using internal energy as a controlled variable. The controller relies on a distributed parameter nonlinear plant model and includes feedforward from the solar irradiation and inlet temperature. Convergence of the closed loop is proved, and the method is experimentally verified to perform well on a pilot-scale solar power plant.     

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.     

Optimal and suboptimal control policies for a solar collector system

An optimal control problem to maximize the net energy gathered by a flat-plate solar collector system by controlling the collector fluid flow rate is investigated. The problem is formulated in terms of a distributed parameter system and solved using the method of characteristics. It is shown that if the pump of the collector loop is such that its pumping power is greater than a linear function of the fluid velocity, then the optimal control policy is one in which the fluid flow is instantly switched between zero and maximum rates. Necessary conditions that determine the optimal switching times are derived. Because the resultant switching function of the optimal policy is shown to be decomposable into two parts, one that depends on the state of the system and another that requires a priori knowledge of the solar intensity over the entire period of operation, a suboptimal control policy that can be implemented by an on/off feedback controller with hysteresis is proposed. When this suboptimal policy is compared with the optimal policy, it is shown that on a clear day with sufficient solar insolation to dictate a two-switch optimal policy, the two policies are identical. Under other weather conditions, the feedback suboptimal controller will keep the pump off for a slightly shorter period of time than the time dictated by the optimal control.     

A switching control strategy applied to a solar collector field

This work presents a new switching control procedure that has been chosen to deal with the changes in plant dynamics. Several control systems composed of IMC-based PID controllers and feedforward compensators are designed for each operation region and a continuous switching mechanism for the overall control system is defined. Experimental tests which have been performed in a distributed collector field of a solar air cooling system, are presented showing promising results for the proposed strategy.     

Reduced complexity adaptive nonlinear control of a distributed collector solar field

An approach to the control of a distributed collector solar field relying on feedback linearization, Lyapunov based adaptation and a simplified plant model is presented. The control objective consists of manipulating the oil flow so that the outlet oil temperature is regulated around a given setpoint. For dealing with plant nonlinearities and external disturbances, a nonlinear transformation is performed on the accessible variables such that the transformed system behaves as an integrator, to which linear control techniques are then applied. Since the transformation depends on an unknown parameter, an adaptation law is designed so as to minimize a Lyapunov function for the whole system's state. For the sake of control synthesis a simplified plant model which retains the bilinear nonlinearity is employed. The resulting control law has the same control structure of the one yielding exact input-output linearization but assumes a different placement of a temperature sensor. In order to justify this procedure, plant internal dynamics is studied. Experimental results obtained in the actual field are presented.     

Direct off-line robot programming via a common CAD package

This paper focuses on intuitive and direct off-line robot programming from a CAD drawing running on a common 3-D CAD package. It explores the most suitable way to represent robot motion in a CAD drawing, how to automatically extract such motion data from the drawing, make the mapping of data from the virtual (CAD model) to the real environment and the process of automatic generation of robot paths/programs. In summary, this study aims to present a novel CAD-based robot programming system accessible to anyone with basic knowledge of CAD and robotics. Experiments on different manipulation tasks show the effectiveness and versatility of the proposed approach.     

Stampede: a cluster programming middleware for interactive stream-oriented applications

Emerging application domains such as interactive vision, animation, and multimedia collaboration display dynamic scalable parallelism and high-computational requirements, making them good candidates for executing on parallel architectures such as SMPs and clusters of SMPs. Stampede is a programming system that has many of the needed functionalities such as high-level data sharing, dynamic cluster-wide threads and their synchronization, support for task and data parallelism, handling of time-sequenced data items, and automatic buffer management. We present an overview of Stampede, the primary data abstractions, the algorithmic basis of garbage collection, and the issues in implementing these abstractions on a cluster of SMPs. We also present a set of micromeasurements along with two multimedia applications implemented on top of Stampede, through which we demonstrate the low overhead of this runtime and that it is suitable for the streaming multimedia applications.     

Robot programming using augmented reality: An interactive method for planning collision-free paths

Current robot programming approaches lack the intuitiveness required for quick and simple applications. As new robotic applications are being identified, there is a greater need to be able to programme robots safely and quickly. This paper discusses the use of an augmented reality (AR) environment for facilitating intuitive robot programming, and presents a novel methodology for planning collision-free paths for an n-d.o.f. (degree-of-freedom) manipulator in a 3D AR environment. The methodology is interactive because the human is involved in defining the free space or collision-free volume (CFV), and selecting the start and goal configurations. The methodology uses a heuristic beam search algorithm to generate the paths. A number of possible scenarios are discussed.     

Multi-response non-parametric profiling using Taguchi's qualimetric engineering and neurocomputing methods: Screening a foaming process in a solar collector assembly

Taguchi's data programming techniques in synergy with data analysis tactics based on artificial neural networks have been fruitful in illuminating intricate manufacturing phenomena. We present a non-parametric approach to treat multi-response multi-factorial datasets created with Taguchi's orthogonal-array samplers. Replicated response datasets are compressed utilizing the signal to noise ratio and then they are homogenized by simple rank-ordering. The multiple response layout is reduced to the more tractable uni-response arrangement by using the super-ranking concept to enact the fusing of the individual responses. The ‘ranked-and-fused’ dataset is subjected to conversion by linear and three-layer perceptrons. The performance of a group of examined effects is assessed according to the perceptrons’ sensitivity analysis output. Using Wilcoxon's one-sample test, statistical significance is assigned to the accumulated ranking scores obtainable from a series of independent perceptron runs. We discuss the efficiency status for each of the two engaged perceptron options on affecting prediction accuracy as well as the influence of data fusion on the SNR-compressed datasets. Our robust neurocomputing solver is elucidated in a concurrent screening of three foam characteristics which are encountered in popular solar-collector assembly operations. Seven controlling factors were profiled and it was found that the temperature of the polyol additive is the sole statistically predominant effect. Finally, through our industrial paradigm, we illustrate the superiority of the fusing principle for downsizing stochastically multiple characteristics and thus gaining faster and more accurate perceptron predictions. We show that the proposed method outperforms the outcomes obtained by the desirability analysis. We identify the points of superiority to the crisper resolution in locating effect dominance accompanied with recovered stochastic significance.     

Visual interactive simulation using a microcomputer

The paper describes an approach to discrete event simulation in which the status of a model is dynamically displayed on a graphics screen. The end user may watch and interact with the model in order to try alternative strategies. The paper reports that the visual interactive technique, if used on a time sharing computer suffers due to variable response times and that the implementation using a microcomputer gives a feasible alternative.     

Experimental investigation on a parabolic trough solar collector for thermal power generation

Developing solar thermal power technology in an effective manner is a great challenge in China.In this paper an experiment platform of a parabolic trough solar collector system(PTCS) was developed for thermal power generation,and the performance of the PTCS was experimentally investigated with synthetic oil as the circulate heat transfer fluid(HTF).The solar collector's efficiency with the variation of the solar flux and the flow rate of the HTF was identified.The collector efficiency of the PTCS can be in ...     

函数式语言方法在网络交互程序中的应用

网络应用程序中为了保持程序的交互性,服务器端的控制程序如CGI(command gateway interface)程序需要在不同的脚本程序之问切换,这样不可避免的会造成控制信息的丢失.为了避免这些问题,介绍了将函数式程序设计语言的一些方法,如Continuation、CPS(eontinuationpassing style)等,并将它们应用到网络程序设计中,不仅简化了设计过程,也提高了程序的安全性,并可以在更一般的语言中实现.     

Robust constrained predictive feedback linearization controller in a solar desalination plant collector field

This paper proposes a feedback linearization strategy for a solar collector field, which is a constrained non-linear processes. The benefits of input–output feedback linearization are improved by a filtered Smith predictor-based model predictive control algorithm with embedded variable constraint mapping to take advantage of: (i) linear control without losing the intrinsic non-linearities typical of thermal power plants; (ii) including input amplitude constraint handling capabilities due to control signal saturations induced, for example, by strong irradiance disturbances or plant start-up; and (iii) avoiding unstable or highly oscillatory responses caused by plant-model mismatch. Simulation studies are first presented to analyze robustness and constraint-mapping features, and real experimental tests of this technique in the AQUASOL desalination plant solar field have been included to demonstrate the advantages of its implementation, especially for reference tracking despite disturbances.     

Adaptive time-warped control of molten salt distributed collector solar fields

This paper concerns the temperature control of a new class of distributed collectors solar fields, which employ molten salt as heat transfer fluid (HTF). Distinctive characteristics of these plants are the high operating temperatures, close to the thermal limits of receiver pipes, and the high solidification temperature of HTF. By means of a novel hybrid adaptive control scheme, based on the Unscented Kalman Filter and on a time-warped predictive controller, the HTF temperature can be effectively controlled within prescribed constraints also in presence of uncertainty in model parameters and faults on collectors.