Kieran Delaney

Kalman Filter-Based Distributed Predictive Control of Large-Scale Multi-Rate Systems: Application to Power Networks

In this paper, a novel distributed Kalman filter (KF) algorithm along with a distributed model predictive control (MPC) scheme for large-scale multi-rate systems is proposed. The decomposed multi-rate system consists of smaller subsystems with linear dynamics that are coupled via states. These subsystems are multi-rate systems in the sense that either output measurements or input updates are not available at certain sampling times. Such systems can arise, e.g., when the number of sensors is smaller than the number of variables to be controlled, or when measurements of outputs cannot be completed simultaneously because of practical limitations. The multi-rate nature gives rise to lack of information, which will cause uncertainty in the systems performance. To circumvent this problem, we propose a distributed KF-based MPC scheme, in which multiple control and estimation agents each determine actions for their own parts of the system. Via communication, the agents can in a cooperative way take one anothers actions into account. The main task of the proposed distributed KF is to compensate for the information loss due to the multi-rate nature of the systems by providing optimal estimation of the missing information. A demanding two-area power network example is used to demonstrate the effectiveness of the proposed method.

Energy-Based Approach to Adaptive Pulse Shaping for Control of RF-MEMS DC-Contact Switches

This paper presents a closed-form analysis to design a pre-shaped open-loop driving actuation waveform to reduce the bouncing effect while maintaining fast switching of a microelectromechanical system contact switch. A single-degree-of-freedom model and the principle of energy conservation were utilized to design a shaped voltage waveform to close the switch with low impact speed. The method can easily adapt the voltage waveform to the variance of pull-in voltages due to imperfect manufacturing and to observed pull-in voltage drift during operation. The analytical calculation of the actuation pulse and the closure time of the switch with near zero velocity agree with simulation and are validated experimentally on the set of cantilever switches. It is shown that the analysis is also applicable for electrostatically actuated devices with more general geometries.

Modeling, simulation and validation of the dynamic performance of a single-pole single-throw RF-MEMS contact switch

This work presents a low-complexity dynamic model of a single-pole single-throw (SPST) ruthenium contact radio frequency (RF) MEMS switch. The model is based on a fabricated switch geometry and relies on dynamic Euler-Bernoulli beam theory incorporating the squeeze-film damping effect and contact mechanics interaction. Hertz theory and the JKR adhesion model are used in contact mechanics with a Gaussian probability surface asperity height distribution to model the interaction between the contact tip and drain. The simulated results for switch closing time, number and duration of bounces, contact deformation, settling time and dual-pulse control strategy are in good agreement with measured experimental results. The experimental validation proves that the proposed modeling framework can accurately simulate the dynamic behavior of the MEMS switch and serve as a design tool for dynamic optimization and development of control strategies that maximize the reliability of the MEMS switches.

Low-cost high-performance Predictive Control of drive systems with elastic coupling

Effective damping of torsional oscillations while guaranteeing desired speed response characteristics and satisfaction of safety and operational constraints remains the main challenge in control of modern industrial drive systems with elastic couplings. This paper investigates the application of an explicit approach to the design of Model Predictive Control (MPC) for the drive system with elastic coupling. The resulting explicit MPC controller achieves the same level of performance as the conventional MPC, but requires only a fraction of the real-time computational machinery, thus leading to fast and reliable implementation. The main advantage of the proposed approach is that the drive physical and safety limitations can be directly incorporated into the control problem formulation and thus enforced explicitly during the operation of the controller. The results are compared to the current state of the art demonstrating the potential for notable performance improvements.

Model-based analysis of switch degradation effects during lifetime testing

The paper reports on the transient analysis of the observed decrease in the actuation voltage of MEMS ohmic switches, under a stress condition. A finite difference model (FDM) is developed that provides insight into the contributions of various mechanical factors to the measured changes in switch performance. In particular, the proposed method allows us to investigate the effects of spring constant reduction and plastic deformation of the switch. Such an analysis cannot be done on the basis of an empirical fitting or existing analytical models. The presented method can be used in the lifetime evaluation of the switch and this application is demonstrated.

Distributed Model Predictive Control and Estimation of Large-Scale Multi-Rate Systems

Abstract In this paper, we propose a new method for control of large-scale multi-rate systems with linear dynamics that are coupled via inputs. These systems are multi-rate systems in the sense that either output measurements or input updates are not available at certain sampling times. Such systems can arise, e.g., when the number of sensors is less than the number of variables to be controlled, or when measurements of outputs cannot be completed simultaneously because of applicational limitations. The multi-rate nature gives rise to lack of information, which will cause uncertainty in the systems performance. A distributed model predictive control (MPC) approach based on Nash game theory is proposed to control multi-agent multi-rate systems in which multiple control agents each determine actions for their own parts of the system. Via communication, the agents can in a cooperative way take one anothers actions into account. To compensate for the information loss due to the multi-rate nature of the systems under study, a distributed Kalman Filter is proposed to provide the optimal estimation of the missing information. Using simulation studies on a distillation column the added value of the proposed distributed MPC and Kalman Filter method is illustrated in comparison with a centralized MPC with centralized Kalman Filter, and a distributed MPC method with a fully decentralized (i.e., no communication) Kalman Filter.

Integrated modeling of nonlinear dynamics and contact mechanics of electrostatically actuated RF-MEMS switches

In this work, a novel nonlinear dynamic model is developed to investigate the bouncing and deformation behaviors of an electrostatically actuated, ohmic-contact RF-MEMS switch. The model accounts for a real geometry, the electrostatic actuation, squeeze-film damping effect, and the nonlinear elastic-plastic contact mechanics using Hertz theory. A low-complexity formulation based on finite differential analysis is employed to solve the model equations in the time-domain. The proposed methodology is validated using a real four-contact RF-MEMS switch with complex geometry. The simulation results of the switch performance in the on-stage (closure) are in good agreement with experimental measurements demonstrating that the model is very effective in capturing the bouncing and contact deformation phenomena accurately. It is foreseen that the proposed approach will be instrumental in providing a better insight into the reliability of MEMS switches and will, ultimately, found a basis of developing and implementing control strategies to maximize their lifetime.

Distributed Adaptive Networked System for Strain Mapping

Separately, context-aware sensing and networked sensing systems have been fast progressing research domains. The emergence of wireless sensor networks (WSN) has introduced a way of implementing a distributed self-organized intelligence in myriads of sensing applications. In this work, WSN and sensing technologies are combined to monitor behavior of a target object. The paper presents design and implementation of a distributed adaptive networked system for strain mapping in a wooden table. The system is intended to provide real-time data on strain development in the target object. The strain gauge deployment layout is designed based on comparison between simulated strain results and strain interpolation on various numbers of sensors. Clustering of densely deployed strain sensors, data collection and processing is organized using tiered wireless network. Experiments on capturing the evolution of strain distribution in an object subject to various loading conditions were carried out and results are reported.

SenseCare: Using Affective Computing to Manage and Care for the Emotional Wellbeing of Older People

This paper discusses an opportunity for using affective computing modalities to support the monitoring of emotional wellbeing of older people. The ageing population is escalating and is associated with an increase in the number of persons with dementia. It is also reported that older people can suffer from social isolation and that people with dementia can experience a range of negative emotions such as anxiety and depression. We present a model to care for a person’s emotional wellbeing in the home using multiple-modalities such as video, audio, electrodermal activity and photoplethysmography.

Optimising dynamic behaviour of electrostatically actuated MEMS contact switch

The reliability of the electrostatically actuated MEMS contact switches is known to be significantly undermined by the unstable dynamic behaviour of devices. High impact forces, bouncing at the contact and oscillations upon release result in substantial mechanical damage to the contacts and the switch compromising the functionality of the switch and reducing its lifetime. Certain effects become more pronounced, such as stiction causing ‘fail-to-open’ malfunctions, resistance increases leading to degraded performance, as well as fracture. To address the issue of the dynamic instability of the switch behaviour this work employs Finite Element Analysis (FEA), linear and nonlinear system identification techniques and optimal control theory to study the dynamic performance of the switch and optimise (soften) its dynamic behaviour by establishing an actuation input voltage that substantially reduces or eliminates the instabilities.