{"title":"Nonlinear Design and Optimisation of a Vibration Energy Harvester","authors":"U. Diala, R. Gunawardena, Yunpeng Zhu, Z. Lang","doi":"10.1109/CONTROL.2018.8516821","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516821","url":null,"abstract":"Nonlinear behavior has been exploited over the last decade towards improving the efficiency of most engineering systems. The effect of nonlinearities on a vibration energy harvester (VEH) has been widely studied. It has been reported in literature that a cubic damping nonlinearity extends the dynamic range (power/energy level) of a VEH system. It has also been widely shown that the operational bandwidth of a VEH system can be increased using a nonlinear hardening spring. As most energy harvesters have a maximum throw limited by the physical enclosure of the device, it is imperative to improve the operational conditions of the harvester within this limitation. This paper investigates the effects of a nonlinear hardening spring with cubic damping on a VEH system while assuming no limitation to the maximum throw (Practical VEH systems are constrained to a maximum throw and this is considered in a subsequent study). A frequency-based approach known as Output Frequency Response Function (OFRF) determined using the Associated Linear Equations (ALEs) of the nonlinear system model is employed. The OFRF polynomial is a representation of the actual system model hence used for the nonlinear VEH analysis and design. Based on the OFRF, optimal parameter values are designed to achieve any desired level of energy for the VEH.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128871314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ICLOCS2: Try this Optimal Control Problem Solver Before you Try the Rest","authors":"Yuanbo Nie, Omar J. Faqir, E. Kerrigan","doi":"10.1109/CONTROL.2018.8516795","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516795","url":null,"abstract":"We present a comprehensive toolbox for solving nonlinear optimal control problems (OCPs) in Matlab and Simulink. The software provides a wide selection of underlying solution methods, as well as automated tools to assist in the design and implementation process. The aim is to provide a first port of call to solve OCPs of different natures, with minimum requirements on the experience of the user. Other OCP solvers might be faster on some problems, but ICLOCS2 might work where others fail.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128770629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Swarm Robotics for Object Transportation","authors":"J. Farrugia, S. Fabri","doi":"10.1109/CONTROL.2018.8516829","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516829","url":null,"abstract":"In this paper a system is proposed whereby a group of small and inexpensive LEGO robots cooperate autonomously to transport a relatively much larger object to a specific location. In achieving this objective, the robots were able to generate a formation, recognise and locate neighbouring robot positions, control their motion and coordinate as a team in order to move the object to a set target location. Cooperative transportation algorithms were implemented, tested and evaluated on a physical setup, including pushing, caging and grasping. Results demonstrate that any desired formation shape can be generated and maintained without distance or orientation constraints. Caging and grasping algorithms yielded an accurate delivery performance, exhibiting reliability across different scenarios.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134024852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal Sensor Placement for Large Scale Systems Using Boosted Clustering","authors":"Satheesh K. Perepu","doi":"10.1109/CONTROL.2018.8516865","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516865","url":null,"abstract":"Applications such as smart cities, smart weather monitoring etc. involve installing a large number of sensors. Installing these sensors and maintaining them is a cumbersome exercise and quite often involves huge cost. As a solution, one can install lesser number of sensors and monitor the entire area by interpolating the missing values (locations which are not measured). The approximation error obtained depends on two things (i) number of sensors installed (ii) placement of these limited number of sensors. The proposed work focuses on the second aspect i.e. optimal placing of sensors assuming the number of sensors available to be placed are fixed. Traditional methods like [1, 2, 3] estimate the optimal locations by posing them as an optimization problem solved using mathematical or heuristic approach. However, for large-scale systems, which deal with thousands of sensors, solution strategies are inefficient owing to their computational complexity.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123973156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Angesh Anupam, D. Wilton, S. Anderson, V. Kadirkamanathan
{"title":"A Data-Driven Framework for Identifying Tropical Wetland Model","authors":"Angesh Anupam, D. Wilton, S. Anderson, V. Kadirkamanathan","doi":"10.1109/CONTROL.2018.8516826","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516826","url":null,"abstract":"A wetland is a land area that is saturated with water. Most of the wetlands exhibit seasonal variations because of soil characteristics, climate variables and orography of a site. This study applies the orthogonal least square (OLS) algorithm under the system identification methodology for the identification of a nonlinear dynamic model structure of the tropical wetlands, using a remotely sensed dataset. Despite the availability of data from the multiple tropical sites, a single dynamic-model structure is able to explain the underlying processes, governing the wetland extents of the tropics. The model is validated against a fresh data set, derived using the similar remote sensing technique. Overall, this study is a novel application of the systems identification for obtaining a single model structure of a category of wetlands, enabling some understanding about their dynamics. The model can also be employed for the assessment of future wetlands in the advent of climate change.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127744576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Decentralized Robust Model Predictive Control for Multi-Input Linear Systems","authors":"Saeed Adelipour, M. Haeri, G. Pannocchia","doi":"10.1109/CONTROL.2018.8516722","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516722","url":null,"abstract":"In this paper, a decentralized model predictive control approach is proposed for discrete linear systems with a high number of inputs and states. The system is decomposed into several interacting subsystems. The interaction among subsystems is modeled as external disturbances. Then, using the concept of robust positively invariant ellipsoids, a robust model predictive control law is obtained for each subsystem solving several linear matrix inequalities. Maintaining the recursive feasibility while considering the attenuation of mutual coupling at each time step and the stability of the overall system are investigated. Moreover, an illustrative simulation example is provided to demonstrate the effectiveness of the method.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129236721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ivana Tomić, Laksh Bhatia, Michael J. Breza, J. Mccann
{"title":"The Limits of LoRaWAN in Event-Triggered Wireless Networked Control Systems","authors":"Ivana Tomić, Laksh Bhatia, Michael J. Breza, J. Mccann","doi":"10.1109/CONTROL.2018.8516774","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516774","url":null,"abstract":"Wireless sensors and actuators offer benefits to large industrial control systems. The absence of wires for communication reduces the deployment cost, maintenance effort, and provides greater flexibility for sensor and actuator location and system architecture. These benefits come at a cost of a high probability of communication delay or message loss due to the unreliability of radio-based communication. This unreliability poses a challenge to contemporary control systems that are designed with the assumption of instantaneous and reliable communication. Wireless sensors and actuators create a paradigm shift in engineering energy-efficient control schemes coupled with robust communication schemes that can maintain system stability in the face of unreliable communication. This paper investigates the feasibility of using the low-power wide-area communication protocol LoRaWAN with an event-triggered control scheme through modelling in Matlab. We show that LoRaWAN is capable of meeting the maximum delay and message loss requirements of an event-triggered controller for certain classes of applications. We also expose the limitation in the use of LoRaWAN when message size or communication range requirements increase or the underlying physical system is exposed to significant external disturbances.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116687976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Auber, M. Pouliquen, E. Pigeon, P. Chapon, S. Moussay
{"title":"Activity Recognition from Binary Data","authors":"R. Auber, M. Pouliquen, E. Pigeon, P. Chapon, S. Moussay","doi":"10.1109/CONTROL.2018.8516844","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516844","url":null,"abstract":"In this paper, an algorithm for the activity recognition from binarized accelerometric data is presented. The particularity of the proposed algorithm is the use of binary data, this constraint on data is justified by the fact that using binary data allows to save battery and memory on the connected device. The objective of the present study is to show that it is possible to perform activity recognition from these binary data. The proposed algorithm uses Auto Regressive (AR) modeling and classification using Support Vector Machine (SVM). Some results on a real-data experiment is presented for the recognition of three activity.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115795440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Callum Moseley, T. Shenton, B. Neaves, P. Paoletti, P. Fulcher
{"title":"Nonlinearity Detection in Dynamical Systems","authors":"Callum Moseley, T. Shenton, B. Neaves, P. Paoletti, P. Fulcher","doi":"10.1109/CONTROL.2018.8516892","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516892","url":null,"abstract":"A method to detect the presence of nonlinearity in dynamical systems is proposed. The method quantifies nonlinearity as a statistical variance from a system's response when linearised. For a given input signal, bounds are defined by an F-score statistical significance test. If the variance of the system's output compared to an ideal linear response exceeds those bounds, linearity is very unlikely and cannot be assumed for the system. The proposed method has use in selecting model structures for system identification and for controller design. The effectiveness of the proposed technique is demonstrated on three single-input single-output (SISO) benchmark systems: a linear spring-damper system, a nonlinear pendulum and nonlinear Duffing oscillator. Each model is driven with inputs of varying amplitude, showing how the effect of nonlinearity in the system dynamics increases as the input amplitude increases. This also demonstrates that, for the same input signals, some of the systems' responses behave more nonlinearly than others. The method is also applied to a published multiple-input-multiple-output (MIMO) nonlinear diesel engine air-path model to show relevance for real applications.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128064751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cooperative Distributed LQR Control for Longitudinal Flight of a Formation of Non-Identical Low-Speed Experimental UAV's","authors":"E. Vlahakis, E. Milonidis, G. Halikias","doi":"10.1109/CONTROL.2018.8516853","DOIUrl":"https://doi.org/10.1109/CONTROL.2018.8516853","url":null,"abstract":"In this paper, an established distributed LQR control methodology applied to identical linear systems is extended to control arbitrary formations of non-identical UAV's. The nonlinear model of a low-speed experimental UAV known as X-RAE1 is utilized for simulation purposes. The formation is composed of four dynamically decoupled X-RAE1 which differ in their masses and their products of inertia about the xz plane. In order to design linear controllers the nonlinear models are linearized for horizontal flight conditions at constant velocity. State-feedback, input and similarity transformations are applied to solve model-matching type problems and compensate for the mismatch in the linearized models due to mass and symmetry discrepancies among the X-RAE1 models. It is shown that the method is based on the controllability indices of the linearized models. Distributed LQR control employed in networks of identical linear systems is appropriately adjusted and applied to the formation of the nonidentical UAV's. The applicability of the approach is illustrated via numerous simulation results.","PeriodicalId":266112,"journal":{"name":"2018 UKACC 12th International Conference on Control (CONTROL)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125996013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}