Control reconfiguration

About: Control reconfiguration is a research topic. Over the lifetime, 22423 publications have been published within this topic receiving 334217 citations.

Efficient Spare Allocation for Reconfigurable Arrays

Abstract: Yield degradation from physical failures in large memories and processor arrays is of significant concern to semiconductor manufacturers. One method of increasing the yield for iterated arrays of memory cells or processing elements is to incorporate spare rows and columns in the die or wafer. These spare rows and columns can then be programmed into the array. The authors discuss the use of CAD approaches to reconfigure such arrays. The complexity of optimal reconfiguration is shown to be NP-complete. The authors present two algorithms for spare allocation that are based on graph-theoretic analysis. The first uses a branch-and-bound approach with early screening based on bipartite graph matching. The second is an efficient polynomial time-approximation algorithm. In contrast to existing greedy and exhaustive search algorithms, these algorithms provide highly efficient and flexible reconfiguration analysis.

Self-organising software architectures for distributed systems

Abstract: A self-organising software architecture is one in which components automatically configure their interaction in a way that is compatible with an overall architectural specification. The objective is to minimise the degree of explicit management necessary for construction and subsequent evolution whilst preserving the architectural properties implied by its specification. This paper examines the feasibility of using architectural constraints as the basis for the specification, design and implementation of self-organising architectures for distributed systems. Although we focus on organising the structure of systems, we show how component state can influence reconfiguration via interface attributes.

Concepts and methods in fault-tolerant control

Abstract: Faults in automated processes will often cause undesired reactions and shut-down of a controlled plant, and the consequences could be damage to technical parts of the plant, to personnel or the environment. Fault-tolerant control combines diagnosis with control methods to handle faults in an intelligent way. The aim is to prevent that simple faults develop into serious failure and hence increase plant availability and reduce the risk of safety hazards. Fault-tolerant control merges several disciplines into a common framework to achieve these goals. The desired features are obtained through online fault diagnosis, automatic condition assessment and calculation of appropriate remedial actions to avoid certain consequences of a fault. The envelope of the possible remedial actions is very wide. Sometimes, simple re-tuning can suffice. In other cases, accommodation of the fault could be achieved by replacing a measurement from a faulty sensor by an estimate. In yet other situations, complex reconfiguration or online controller redesign is required. This paper gives an overview of recent tools to analyze and explore structure and other fundamental properties of an automated system such that any inherent redundancy in the controlled process can be fully utilized to maintain availability, even though faults may occur.

Optimal Photovoltaic Array Reconfiguration to Reduce Partial Shading Losses

Abstract: Partial shading of a photovoltaic array is the condition under which different modules in the array experience different irradiance levels due to shading. This difference causes mismatch between the modules, leading to undesirable effects such as reduction in generated power and hot spots. The severity of these effects can be considerably reduced by photovoltaic array reconfiguration. This paper proposes a novel mathematical formulation for the optimal reconfiguration of photovoltaic arrays to minimize partial shading losses. The paper formulates the reconfiguration problem as a mixed integer quadratic programming problem and finds the optimal solution using a branch and bound algorithm. The proposed formulation can be used for an equal or nonequal number of modules per row. Moreover, it can be used for fully reconfigurable or partially reconfigurable arrays. The improvement resulting from the reconfiguration with respect to the existing photovoltaic interconnections is demonstrated by extensive simulation results.

Artificial neural-network based feeder reconfiguration for loss reduction in distribution systems

Abstract: Strategies are proposed to reconfigure the feeder in distribution systems by using artificial neural networks (ANNs) with mapping ability. ANNs determine the appropriate system topology that reduces the power loss according to the variation of load pattern. The control strategy can be easily obtained on the basis of the system topology which is provided by ANNs. ANNs are designed in two groups. The first group estimates the proper load level from the load data of each zone. The second determines the appropriate system topology from the input load level. Several programs with the training set builder are developed for the design, the training, and the accuracy test of artificial neural networks. The performance of neural networks designed is evaluated on the test distribution system. Neural networks are implemented in FORTRAN language and trained on a 386 PC. >