{"title":"Design and tuning of fractional-order PID controllers for time-delayed processes","authors":"E. Edet, R. Katebi","doi":"10.1109/CONTROL.2016.7737589","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737589","url":null,"abstract":"Frequency domain based design methods are investigated for the design and tuning of fractional-order PID for scalar applications. Since Ziegler-Nichol's tuning rule and other algorithms cannot be applied directly to tuning of fractional-order controllers, a new algorithm is developed to handle the tuning of these fractional-order PID controllers based on a single frequency point test just like Ziegler-Nichol's rule for integer order PID controllers. Critical parameters of the system are obtained at the ultimate point and controller parameters are calculated from these critical measurements to meet design specifications. Thereafter, fractional order controller is obtained to meet a specified robustness criteria which is the phase-invariability against gain variations around the phase cross-over frequency. Results are simulated on a second-order plus dead time plant to demonstrate both performance and robustness.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"47 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132530746","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":"Statistics local fisher discriminant analysis for industrial process fault classification","authors":"Xiaogang Deng, Xuemin Tian, Sheng Chen, C. Harris","doi":"10.1109/CONTROL.2016.7737588","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737588","url":null,"abstract":"In order to effectively identify industrial process faults, an improved Fisher discriminant analysis (FDA) method, referred to as the statistics local Fisher discriminant analysis (SLFDA), is proposed for fault classification. For mining statistics information hidden in process data, statistics pattern analysis is firstly applied to transform the original measured variables into the corresponding statistics, including second-order and higher-order ones. Furthermore, considering the local structure characteristics of fault data, local FDA (LFDA) is performed which computes the discriminant vectors by modifying the optimization objective with local weighting factor. Simulation results on the benchmark Tennessee Eastman process show that the proposed SLFDA has a better fault classification performance than the FDA and LFDA methods.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131877238","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":"Model development and energy management control for hybrid electric race vehicles","authors":"K. Reeves, A. Montazeri, C. J. Taylor","doi":"10.1109/CONTROL.2016.7737651","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737651","url":null,"abstract":"A Hybrid Electric Vehicle longitudinal dynamics model for the control of energy management is developed. The model is implemented using Simulink® and consists of a transitional vehicle speed input parameterized by, for example, the New European Driving Cycle. It is a backward looking model in that engine and motor on/off states are determined by the controller, dependent on wheel torque requirements and output targets. The objective of the simulation is to calculate tractive effort and resistance forces to determine longitudinal net vehicle force at the road. This article addresses model development and initial investigations of its dynamic behaviour in order to establish appropriate energy management strategies for the Hybrid Electric system. In particular, All Wheel Drive, Front Wheel Drive and Rear Wheel Drive drivetrain architectures are evaluated to determine minimum fuel usage and battery state of charge. The use of a logic controller allows a reduction of simulation time and ensures accurate results for charge depletion and harvesting. Simulated fuel consumption is within 1% of actual usage.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115545056","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}
Weifang Ling, Minyou Chen, Zuolin Wei, Feixiong Chen, Lei Yu, David C. Yu
{"title":"A distributed optimal control method for active distribution network","authors":"Weifang Ling, Minyou Chen, Zuolin Wei, Feixiong Chen, Lei Yu, David C. Yu","doi":"10.1109/CONTROL.2016.7737568","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737568","url":null,"abstract":"This paper presents a distributed optimal control method for stable and economical operation of active distribution network (ADN). The method incorporates a distributed constraint optimization problem (DCOP) model with distributed simulated annealing (DSAN) algorithm based on potential game. Moreover, the distributed optimal strategy is developed on the basis of multi-agent system, and the distributed power flow calculation method is utilized to perform the power flow calculation among agents. The performance verification of the distributed optimal control strategy and the comparison with the centralized method are conducted in IEEE 39-bus system with distributed generations (DGs). Finally, the simulation cases are presented and discussed to demonstrate the effectiveness and applicability of the proposed optimal method for ADN.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117167990","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}
E. O’Dwyer, L. De Tommasi, K. Kouramas, M. Cychowski, G. Lightbody
{"title":"Low-order building model identification in presence of unmeasured disturbance for predictive control strategies","authors":"E. O’Dwyer, L. De Tommasi, K. Kouramas, M. Cychowski, G. Lightbody","doi":"10.1109/CONTROL.2016.7737637","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737637","url":null,"abstract":"Predictive control strategies for building heating and cooling systems have been proposed as an energy efficient alternative to traditional strategies. The performance of such strategies is highly dependent on the underlying system models used. In an effective strategy, these models used are required to be accurate enough for informative predictions to be made yet simple enough to be used within a numerical optimization problem. Identification of such models from measured data may not be trivial in the presence of a large amount of unmeasured disturbance. In this paper, methods for deriving low-order zone models in the presence of unknown disturbances are considered. A high-order RC-network representing the complexity of a building is used to generate data for the identification process. An estimate of the disturbance affecting each zone of the network is first developed using Kalman filtering. Disturbances common to several zones are isolated by a spatial filtering process using principal component analysis. The new disturbance estimates are then included in the model identification formulation. The models and disturbance estimates are refined through several iterations of the process. Significantly improved prediction accuracy is shown to result when the disturbance estimates are incorporated.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124957093","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":"Wind optimal flight trajectories to minimise fuel consumption within a 3 dimensional flight network","authors":"C. Currie, A. Marcos, Oliver Turnbull","doi":"10.1109/CONTROL.2016.7737600","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737600","url":null,"abstract":"This paper assesses the potential fuel savings benefits that can be gained from wind optimal flight trajectories. This question is posed on a 3 dimensional fixed flight network consisting of discrete waypoints which is representative of the size of Europe. The optimisation implements Dijkstra's shortest path algorithm to compute the minimum fuel burn route through a network and compares this to the fuel burn for the shortest distance route. Particular effort is applied to testing the repeatability and robustness of the results. This is achieved through a sensitive analysis based on a number of identified model parameters relating to the setup of the flight network. The results of this study show fuel savings between 1.0%-10.3%, and suggest that the benefits of wind optimal flight trajectories are significant.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123272365","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":"Based on H2/H∞ filtering control for wireless network with multi-channel network-induced delays constraints","authors":"D. Du, Guohua Zhan, Bo Qi, M. Fei","doi":"10.1109/CONTROL.2016.7737630","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737630","url":null,"abstract":"Distributed network-induced delays of wireless networked control systems with the multi-channel may deteriorate the performance of control systems, and noise interference of system may also lead to the control quality dropping. To solve these problems, a wireless networked control strategy based on H2/H∞ filtering is proposed. Firstly, a directed graph is used to describe the communication topology of the distributed sensor nodes, and different Markov chains are employed to describe the characters of network-induced delays in each wireless channel. To improve the precision of the controlled inputs, a H2/H∞ filter is then designed to reduce noise interference of the output signals of the sensors, and a closed-feedback filtering and control system model is further proposed. Moreover, for the given maximum network-induced delays in each wireless channel, the stochastic stability of the closed-feedback filtering and control system is presented and a prescribed H2/H∞ performance is also achieved, and the relationships between the stochastic stability criteria, the network-induced delays, the filtering parameters and the controller gain are established. Finally, simulation results confirm the feasibility and effectiveness of the proposed method.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"49 14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122743886","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":"A model based design framework for safety verification of a semi-autonomous inspection drone","authors":"O. McAree, J. Aitken, S. Veres","doi":"10.1109/CONTROL.2016.7737551","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737551","url":null,"abstract":"In this paper, we present a model based design approach to the development of a semi-autonomous control system for an inspection drone. The system is tasked with maintaining a set distance from the target being inspected and a constant relative pose, allowing the operator to manoeuvre the drone around the target with ease. It is essential that the robustness of the autonomous behaviour be thoroughly verified prior to actual implementation, as this will involve the flight of a large multi-rotor drone in close proximity to a solid structure. By utilising the Robotic Operating System to communicate between the autonomous controller and the drone, the same Simulink model can be used for numerical coverage testing, high fidelity simulation, offboard execution and final executable deployment.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123973453","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}
Feriel Kochtbene, George Moraru, J. Carmona, U. Masciantonio
{"title":"Active control of a vibrating beam in milling","authors":"Feriel Kochtbene, George Moraru, J. Carmona, U. Masciantonio","doi":"10.1109/CONTROL.2016.7737567","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737567","url":null,"abstract":"The vibrations while Milling often impact the results, sometimes generating very important cost because of the lack of quality for high value parts as well as cutting tool wear due to chatter phenomenon that happens during unstable vibrations. To mitigate this phenomenon, many techniques exist like passive and semi-active methods but the active control in milling, which is not as widespread in turning or boring, remains one of the most promising ways. This article will deal briefly with these techniques before explaining our two system models: cutting process and the vibrating beam, considered as an accurate enough model of a long slender rotary tool, which will be after coupled. Then, we will study the active control of the obtained system following three control strategies: the H∞ compensator, LQG one and μ synthesis compensator.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128115144","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":"Gas phase train in upstream oil & gas fields: Part-II disturbances impact study","authors":"Y. H. Al-Naumani, J. Rossiter","doi":"10.1109/CONTROL.2016.7737591","DOIUrl":"https://doi.org/10.1109/CONTROL.2016.7737591","url":null,"abstract":"The main objectives of this paper are to assess the impact of disturbances in a natural gas processing train in the upstream oil & gas fields and to validate a representative model which can be used for developing/testing a swift and anticipatory control system. The impact of two different causes of process disturbances on a gas phase train comprising three main processes connected in series is presented. The paper provides answers about how feed disturbances, and process unit malfunctions affect series connected processes, and more specifically Gas Sweetening, Gas Dehydration, and Hydrocarbon Dew-Pointing units.","PeriodicalId":403252,"journal":{"name":"2016 UKACC 11th International Conference on Control (CONTROL)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134401951","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}