Jie You, Yufei Zhang, Mingchen Li, Kun Su, Fumin Zhang, Wencen Wu
{"title":"Cooperative parameter identification of advection-diffusion processes using a mobile sensor network","authors":"Jie You, Yufei Zhang, Mingchen Li, Kun Su, Fumin Zhang, Wencen Wu","doi":"10.23919/ACC.2017.7963445","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963445","url":null,"abstract":"Online parameter identification of advection-diffusion processes is performed using a mobile sensor network. A constrained cooperative Kalman filter is developed to provide estimates of the field values and gradients along the trajectories of the mobile sensor network so that the temporal variations of the field values can be estimated. Utilizing the state estimates from the constrained cooperative Kalman filter, a recursive least square (RLS) algorithm is designed to estimate the unknown parameters of the advection-diffusion process. We provide bias analysis of the RLS in the paper. In addition to validating the proposed algorithm in simulated advection-diffusion fields, we build a controllable CO2 advection-diffusion field in a lab and design a sensor grid that collects the field concentration over time to allow the validation of the proposed algorithm in the CO2 field. Experimental results demonstrate robustness of the algorithm under realistic uncertainties and disturbances.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133247886","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 control of a distributed solar collector field","authors":"Xiaodong Xu, Yuan Yuan, S. Dubljevic","doi":"10.23919/ACC.2017.7963217","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963217","url":null,"abstract":"The dynamics of a distributed solar collector field can be modelled by a nonlinear hyperbolic partial differential equation (PDE) based on the energy balance. The model-based optimal control of the outlet temperature is studied. One of few ways to influence the outlet temperature is by adjusting the oil pump volumetric flow rate. In this work, an optimal algorithm is developed to minimize the mismatch between the outlet temperature and a desired temperature. The method is based on the adjoint approach for constrained optimization problems with a nonlinear hyperbolic PDE applied as an optimization constraint. In particular, the algorithm simplifies a problem by decomposing it into a two-level optimization problem. Unlike the traditional tracking control such as motion planing, the reference tracking equations in this work do not need state trajectory generation. Finally, the proposed approach is verified to perform well via a computer simulation.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115106899","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}
Michael Quann, L. Ojeda, William Smith, Denise M. Rizzo, M. Castanier, K. Barton
{"title":"An energy-efficient method for multi-robot reconnaissance in an unknown environment","authors":"Michael Quann, L. Ojeda, William Smith, Denise M. Rizzo, M. Castanier, K. Barton","doi":"10.23919/ACC.2017.7963292","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963292","url":null,"abstract":"Autonomous robots have significant potential for reconnaissance and environmental monitoring applications. Ground robots, in particular, are performing reconnaissance missions in places that are too hazardous for humans. However, these robots are constrained by energy limitations that are impacted by uncertain environments and harsh terrains. The purpose of this work is to develop methods for improving the efficiency of reconnaissance missions through energy awareness. To address such limitations, robot energy usage is spatially modeled with a Gaussian Process (GP) through measurements collected during the mission. The resulting energy predictions are incorporated into a centralized waypoint-based optimization with the goal of minimizing the uncertainty of a spatio-temporal field, subject to ensuring the robots' return to their respective starting locations for refueling. Simulation results for a 3-robot system demonstrate the effectiveness of incorporating energy predictions into reconnaissance missions.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132143752","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":"Subspace identification and predictive control of batch particulate processes","authors":"Abhinav Garg, P. Mhaskar","doi":"10.23919/ACC.2017.7963003","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963003","url":null,"abstract":"This paper addresses the problem of subspace identification based modeling and predictive control of batch particulate process with an application to crystal size distribution (CSD) control in a batch crystallizer. To this end, a subspace identification technique is first adapted to identify a linear time invariant model for batch particulate processes. The estimated model is then deployed in a linear model predictive control (MPC) formulation to achieve a particle size distribution with desired characteristics subject to both manipulated input and product quality constraints. The proposed approach is implemented on a seeded batch crystallizer process and compared with an open loop policy as well as a PI controller based trajectory tracking policy. The proposed MPC is shown to achieve 27% and 30% improvements, respectively.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134111878","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":"Characteristic Moore-Greitzer model parameter identification for a one stage axial compressor system","authors":"Chris K. Bitikofer, M. Schoen, Ji-chao Li, F. Lin","doi":"10.23919/ACC.2017.7962948","DOIUrl":"https://doi.org/10.23919/ACC.2017.7962948","url":null,"abstract":"Axial compressor systems are predisposed to instability near their optimum operating point. Instabilities include surge or stall, leading to severe consequences to the operational health and integrity of compressor system. The Moore-Greitzer (MG) model has been commonly recognized as a standard when characterizing the dynamics within an axial compressor and is advantageous for the development of a controller. Such a controller promises to increase the efficiency of compressor systems; yet, controller design has been barred by an inability to extract the MG parameters defining the behavior of real-life compressors. Hence, control has not been based on the MG model. Determining these system parameters experimentally is impractical due the limited range of operation compressors can withstand without sustaining damage. In this paper a proof-of-concept gray-box identification method is proposed to extract the characteristic parameters of a MG model from experimental data. This technique utilizes a genetic algorithm based optimization. In this study, simulated data from a MG model and measured data from a one stage compressor system is utilized to extract key parameters of the MG model. Establishing an indirect method to determine the parameters for the MG model extends its relevance from theoretical use to concrete application and opens the door for the direct control of axial compressors.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132943017","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":"Nonlinear adaptive control of EPB shield tunneling machine","authors":"Xiaodong Xu, W. Mao","doi":"10.23919/ACC.2017.7963209","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963209","url":null,"abstract":"This paper solves the issue of earth pressure balance (EPB) control in shield tunneling. Keeping earth pressure balanced on cutting head is the key to ground deformation avoidance. However, only a few control methods based on mechanism model are put forward and all the model applied before seldom involved nonlinearity and uncertainty. Thus, a nonlinear model of EPB control in shield tunneling is first established with consideration of particular parametric and multi-unmodeled uncertainties in order to match the actual system more precisely, and a nonlinear adaptive control method is proposed for a class of uncertain nonlinear systems in this paper. The resulting controller guarantees the shield machine system to be globally uniformly ultimately bounded with a satisfactory transient performance and a small steady tracking error as expected to some extent.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123623882","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":"Further discussions on a distributed algorithm for solving linear algebra equations","authors":"Xuan Wang, S. Mou, Dengfeng Sun","doi":"10.23919/ACC.2017.7963612","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963612","url":null,"abstract":"In [2], a distributed algorithm has recently been developed for solving linear algebraic equations via multi-agent networks. To adopt the algorithm, each agent only has to know part of the linear equation as well as its nearby neighbors' estimates to the solution. In this paper, we would like to further discuss this algorithm from the following two perspectives. The first one is to improve the numerical stability of the algorithm and meanwhile eliminate initialization step that is necessary in [2]. The second one is to achieve a specific solution with minimum l2 norm when the linear equation has more than one solutions.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123756526","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":"On the globally exponentially convergent immersion and invariance speed observer for mechanical systems","authors":"M. H. Arbo, E. Grøtli, J. Gravdahl","doi":"10.23919/ACC.2017.7963455","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963455","url":null,"abstract":"In this article we present a reformulation of the invariance and immersion speed observer of Astolfi et al. as applied to mechanical systems with bounded inertia matrices. This is done to explore the possibility of its practical implementation e.g. for 6 degrees-of-freedom industrial robots. The reformulation allows us find an explicit expression for one of the bounds used in the observer, and a constructive method for the second. We show that the observer requires either analytically or numerically solving at most 2n2 integrals, where n is the number of generalized coordinates in the mechanical system.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122358637","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}
S. M. Moosavi, S. Fakoorian, V. Azimi, H. Richter, D. Simon
{"title":"Derivative-free Kalman filtering-based control of prosthetic legs","authors":"S. M. Moosavi, S. Fakoorian, V. Azimi, H. Richter, D. Simon","doi":"10.23919/ACC.2017.7963763","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963763","url":null,"abstract":"A derivative-free method for state estimation-based control of a robot/prosthesis system is presented. The system is the combination of a test robot that emulates human hip and thigh motion, and a powered transfemoral prosthetic leg. The robot/prosthesis combination is modeled as a three degree-of-freedom (DOF) robot: vertical hip displacement, thigh angle, and knee angle. We develop a derivative-free Kalman filter (DKF) for state estimation-based control for an n-DOF robotic system. We then propose a method to make the DKF robust when the robot dynamics include disturbances. In the robust DKF, we use two different methods for disturbance rejection: PD and PI. These disturbance compensators are used for supervisory control to make the DKF robust in the presence of disturbances. The simulation results show the advantages of the DKF and the robust DKF for the three-DOF robot/prosthesis system for state estimation-based control.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124972460","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}
Changliu Liu, Chung-Yen Lin, Yizhou Wang, M. Tomizuka
{"title":"Convex feasible set algorithm for constrained trajectory smoothing","authors":"Changliu Liu, Chung-Yen Lin, Yizhou Wang, M. Tomizuka","doi":"10.23919/ACC.2017.7963597","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963597","url":null,"abstract":"Trajectory smoothing is an important step in robot motion planning, where optimization methods are usually employed. However, the optimization problem for trajectory smoothing in a clustered environment is highly non-convex, and is hard to solve in real time using conventional non-convex optimization solvers. This paper discusses a fast online optimization algorithm for trajectory smoothing, which transforms the original non-convex problem to a convex problem so that it can be solved efficiently online. The performance of the algorithm is illustrated in various cases, and is compared to that of conventional sequential quadratic programming (SQP). It is shown that the computation time is greatly reduced using the proposed algorithm.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125872147","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}