Control reconfiguration

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

Deployment and dynamic reconfiguration planning for distributed software systems

Abstract: The quality of software systems are determined in part by their optimal configurations. Optimal configurations are desired when the software is being deployed and during its lifetime. However, initial deployment and subsequent dynamic reconfiguration of a software system is difficult because of the interplay of many interdependent factors, including cost, time, application state, and system resources. As the size and complexity of software systems increases, procedures (manual or automated) that assume a static software architecture and environment are becoming untenable. We have developed a novel technique for carrying out the deployment and reconfiguration planning processes that leverages recent advances in the field of temporal planning. We describe a tool called Planit, which manages the deployment and reconfiguration of a software system utilizing a temporal planner. Given a model of the structure of a software system, the network upon which the system should be hosted, and a goal configuration, Planit will use the temporal planner to devise possible deployments of the system. Given information about changes in the state of the system, network and a revised goal, Planit will use the temporal planner to devise possible reconfigurations of the system. We present the results of a case study in which Planit is applied to a system consisting of various components that communicate across an application-level overlay network.

Deadlock-free dynamic reconfiguration schemes for increased network dependability

Abstract: Network-based parallel computing systems often require the ability to reconfigure the routing algorithm to reflect changes in network topology if and when voluntary or involuntary changes occur. The process of reconfiguring a network's routing capabilities may be very inefficient and/or deadlock-prone if not handled properly. We propose efficient and deadlock-free dynamic reconfiguration schemes that are applicable to routing algorithms and networks which use wormhole, virtual cut-through, or store-and-forward switching, combined with hard link-level flow control. One requirement is that the network architecture use virtual channels or duplicate physical channels for deadlock-handling as well as performance purposes. The proposed schemes do not impede the injection, transmission, or delivery of user packets during the reconfiguration process. Instead, they provide uninterrupted service, increased availability/reliability, and improved overall quality-of-service support as compared to traditional techniques based on static reconfiguration.

Robust and adaptive actuator failure compensation designs for a rocket fairing structural-acoustic model

Abstract: The actuator failure compensation problem is formulated for active vibration control of a rocket fairing structural-acoustic model with unknown actuator failures. Performance of a nominal optimal control scheme in the presence of actuator failures is studied to show the need of effective failure compensation. A robust control scheme and two adaptive control schemes are developed, which are able to ensure the closed-loop system signal boundedness in the presence of actuator failures whose failure pattern and values are unknown. The adaptive scheme for parameterizable failures ensures asymptotic stability despite failure uncertainties. Simulation results verified their failure compensation effectiveness.

Model Predictive Control for Tactical Decision-Making in Semiconductor Manufacturing Supply Chain Management

Abstract: Supply chain management (SCM) in semiconductor manufacturing poses significant challenges that arise from the presence of long throughput times, unique constraints, and stochasticity in throughput time, yield, and customer demand. To address these concerns, a model predictive control (MPC) algorithm is developed which relies on a control-oriented formulation to generate daily decisions on starts of factories. A multiple-degree-of-freedom observer formulated for ease of tuning is implemented to achieve robustness and performance in the presence of nonlinearity and stochasticity in both supply and demand. The control algorithm is configured to meet the requirements of meeting customer demand (both forecasted and unforecasted), and track inventory and starts targets provided by higher level decision policies. Unique features of semiconductor manufacturing, such as capacity limits, packaging, and product reconfiguration, are formally addressed by imposing different constraints related to starts and inventories. This functionality contrasts that of standard approaches to MPC and makes this controller suitable as a tactical decision tool for semiconductor manufacturing and similar forms of high-volume discrete-parts manufacturing problems. Two representative case studies are examined under diverse realistic conditions with this flexible formulation of MPC. It is demonstrated that system robustness, performance, and high levels of customer service are achieved with proper tuning of the filter gains and weights, as well as the presence of adequate capacity in the supply chain.