34 research outputs found

    Robust and Decentralized Control of Web Winding Systems

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    This research addresses the velocity and tension regulation problems in web handling, including those found in the single element of an accumulator and those in the large-scale system settings. A continuous web winding system is a complex large-scale interconnected dynamics system with numerous tension zones to transport the web while processing it. A major challenge in controlling such systems is the unexpected disturbances that propagate through the system and affect both tension and velocity loops along the way. To solve this problem, a unique active disturbance rejection control (ADRC) strategy is proposed. Simulation results show remarkable disturbance rejection capability of the proposed control scheme in coping with large dynamic variations commonly seen in web winding systems. Another complication in web winding system stems from its large-scale and interconnected dynamics which makes control design difficult. This motivates the research in formulating a novel robust decentralized control strategy. The key idea in the proposed approach is that nonlinearities and interactions between adjunct subsystems are regarded as perturbations, to be estimated by an augmented state observer and rejected in the control loop, therefore making the local control design extremely simple. The proposed decentralized control strategy was implemented on a 3-tension-zone web winding processing line. Simulation results show that the proposed control method leads to much better tension and velocity regulation quality than the existing controller common in industry. Finally, this research tackles the challenging problem of stability analysis. Although ADRC has demonstrated the validity and advantage in many applications, the rigorous stability study has not been fully addressed previously. To this end, stability characterization of ADRC is carried out in this work. The closed-loop system is first reformulated, resulting in a form that allows the application of the well established singular perturbation method. Based on the decom

    Robust and Decentralized Control of Web Winding Systems

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    This research addresses the velocity and tension regulation problems in web handling, including those found in the single element of an accumulator and those in the large-scale system settings. A continuous web winding system is a complex large-scale interconnected dynamics system with numerous tension zones to transport the web while processing it. A major challenge in controlling such systems is the unexpected disturbances that propagate through the system and affect both tension and velocity loops along the way. To solve this problem, a unique active disturbance rejection control (ADRC) strategy is proposed. Simulation results show remarkable disturbance rejection capability of the proposed control scheme in coping with large dynamic variations commonly seen in web winding systems. Another complication in web winding system stems from its large-scale and interconnected dynamics which makes control design difficult. This motivates the research in formulating a novel robust decentralized control strategy. The key idea in the proposed approach is that nonlinearities and interactions between adjunct subsystems are regarded as perturbations, to be estimated by an augmented state observer and rejected in the control loop, therefore making the local control design extremely simple. The proposed decentralized control strategy was implemented on a 3-tension-zone web winding processing line. Simulation results show that the proposed control method leads to much better tension and velocity regulation quality than the existing controller common in industry. Finally, this research tackles the challenging problem of stability analysis. Although ADRC has demonstrated the validity and advantage in many applications, the rigorous stability study has not been fully addressed previously. To this end, stability characterization of ADRC is carried out in this work. The closed-loop system is first reformulated, resulting in a form that allows the application of the well established singular perturbation method. Based on the decom

    Active Disturbance Rejection Control (ADRC) Toolbox for MATLAB/Simulink

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    In this study, an active disturbance rejection control (ADRC) toolbox for MATLAB/Simulink is introduced. Although ADRC has already been established as a powerful robust control framework with successful industrial implementations and strong theoretical foundations, a comprehensive tool for computer-aided design of ADRC has not been developed until now. The proposed open-source ADRC Toolbox is a response to the growing need in the scientific community and the control industry for a straightforward software application of the ADRC methodology. Its main purpose is to fill the gap between the current theories and applications of ADRC and to provide an easy-to-use solution for users in various control fields who want to employ the ADRC scheme in their applications. The ADRC Toolbox contains a single, general-purpose, drag-and-drop function block that allows the synthesis of a predefined ADRC-based strategy with minimal design effort. Additionally, its open structure allows creation of custom control solutions. The efficacy of the ADRC Toolbox is validated through both simulations and hardware experiments, which were conducted using a variety of problems known in the motion, process, and power control areas.Comment: 43 pages, 16 figures, 3 table

    Inferential active disturbance rejection control of distillation columns

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    PhD ThesisThe distillation column is an important processing unit in the chemical and oil refining industry. Distillation is the most widely employed separation method in the world’s oil plants, chemical and petrochemical industrial facilities. The main drawback of the technique is high energy consumption, which leads to high production costs. Therefore, distillation columns are required to be controlled close to the desired steady state conditions because of economic incentives. Most industrial distillation columns are currently controlled by conventional multi-loop controllers such as proportional-integral-derivative (PID) controllers, which have several shortcomings such as difficulty coping with sudden set-point jumps, complications due to the integral term (I), and performance degradation due to the effect of noise on the derivative term (D). The control of ill-conditioned and strongly non-linear plants such as high purity distillation needs advanced control schemes for high control performance. This thesis investigates the use of active disturbance rejection control (ADRC) for product composition control in distillation columns. To the author’s knowledge, there are few reported applications of ADRC in the chemical industry. Most ADRC applications are in electrical, robotics and others. Therefore, this research will be the first to apply the ADRC scheme in a common chemical processing unit, and can be considered as a first contribution of this research. Initially, both PI and ADRC schemes are developed and implemented on the Wood–Berry distillation column transfer function model, on a simulated binary distillation column based on a detailed mechanistic model, and on a simulated heat integrated distillation column (HIDiC) based on a detailed mechanistic model. Process reaction curve method and system identification tools are used to obtain the 2×2 multi-input multi-output (MIMO) transfer function of both binary and HIDiC for the purpose of PI tuning where the biggest log-modulus tuning (BLT) method is used. Then, the control performance of ADRC is compared to that of the traditional PI control in terms of set-point tracking and disturbance rejection. The simulation result clearly indicates that the ADRC gives better control performance than PI control in all three case studies. The long time delay associated with product composition analysers in distillation columns such as gas chromatography deteriorates the overall control performance of the ADRC scheme. v To overcome this issue an inferential ADRC scheme is proposed and can be considered as a second contribution of this research. The tray temperatures of distillation columns are used to estimate both the top and bottom product compositions that are difficult to measure on-line without a time delay. Due to the strong correlation that exists in the tray temperature data, principal component regression (PCR) and partial least square (PLS) are used to build the soft sensors, which are then integrated into the ADRC. In order to overcome control offsets caused by the discrepancy between soft sensor estimation and actual compositions measurement, an intermittent mean updating technique is used to correct both the PCR and PLS model predictions. Furthermore, no significant differences were observed from the simulation results in the prediction errors reported by both PCR and PLS. The proposed inferential ADRC scheme shows effective and promising results in dealing with non-linear systems with a large measurement delay, where the ADRC has the ability to accommodate both internal uncertainties and external disturbances by treating the impact from both factors as total disturbances that will then be estimated using the extended state observer (ESO) and cancelled out by the control law. The inferential ADRC control scheme provides tighter product composition control that will lead to reduced energy consumption and hence increase the distillation profitability. A binary distillation column for separating a methanol–water mixture and an HIDiC for separating a benzene–toluene mixture are used to verify the developed inferential ADRC control scheme.Petroleum Development of Oman (PDO) for their generous support and scholarshi

    Disturbance Observer-based Robust Control and Its Applications: 35th Anniversary Overview

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    Disturbance Observer has been one of the most widely used robust control tools since it was proposed in 1983. This paper introduces the origins of Disturbance Observer and presents a survey of the major results on Disturbance Observer-based robust control in the last thirty-five years. Furthermore, it explains the analysis and synthesis techniques of Disturbance Observer-based robust control for linear and nonlinear systems by using a unified framework. In the last section, this paper presents concluding remarks on Disturbance Observer-based robust control and its engineering applications.Comment: 12 pages, 4 figure

    Multimodal series elastic actuator for human-machine interaction with applications in robot-aided rehabilitation

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    Series elastic actuators (SEAs) are becoming an elemental building block in collaborative robotic systems. They introduce an elastic element between the mechanical drive and the end-effector, making otherwise rigid structures compliant when in contact with humans. Topologically, SEAs are more amenable to accurate force control than classical actuation techniques, as the elastic element may be used to provide a direct force estimate. The compliant nature of SEAs provides the potential to be applied in robot-aided rehabilitation. This thesis proposes the design of a novel SEA to be used in robot-aided musculoskeletal rehabilitation. An active disturbance rejection controller is derived and experimentally validated and multiobjective optimization is executed to tune the controller for best performance in human-machine interaction. This thesis also evaluates the constrained workspaces for individuals experiencing upper-limb musculoskeletal disorders. This evaluation can be used as a tool to determine the kinematic structure of devices centred around the novel SEA

    Active disturbance rejection control: a guide for design and application

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    [EN] This tutorial addresses the design of controllers by active disturbance rejection control (ADRC). First, the main blocks in the ADRC loop are described. Next, the formulation of the control problem under the disturbance rejection framework is discussed, as well as the tuning of the gains set which are part of the main loop and a guide on designing of the active disturbance rejection controller is presented. This tutorial aims to offer an introduction to readers about the ADRC and a review of the most significant publications that have contributed to development and advance in the research related to the area. To illustrate the design procedure, two examples are included: thermal control and the multivariable control of a chemical process.[ES] Este tutorial aborda el diseño de controladores lineales por rechazo activo de perturbaciones (ADRC). Se inicia con la descripción de los bloques que componen el lazo ADRC. Seguidamente, se discute la formulación del problema de control en el marco del rechazo de perturbaciones, la sintonización del conjunto de ganancias que hacen parte del lazo y se presenta una guía general para el diseño del controlador lineal por rechazo activo de perturbaciones. Con este tutorial se pretende ofrecer una introducción a los lectores sobre el ADRC y una reseña de los trabajos que indican las tendencias de investigación en el área. Para ilustrar el procedimiento de diseño, se incluyen dos ejemplos: el control de un proceso térmico y el control multivariable de un proceso químico.Martínez, B.; Sanchis, J.; García-Nieto, S.; Martínez, M. (2021). Control por rechazo activo de perturbaciones: guía de diseño y aplicación. Revista Iberoamericana de Automática e Informática industrial. 18(3):201-217. https://doi.org/10.4995/riai.2020.14058OJS201217183Ahi, B., Haeri, M., 2018. Linear active disturbance rejection control from the practical aspects. IEEE/ASME Transactions on Mechatronics 23 (6), 2909-2919. https://doi.org/10.1109/tmech.2018.2871880Ahmad, S., Ali, A., 2019. Active disturbance rejection control of DC-DC boost converter: a review with modifications for improved performance. IET Power Electronics 12 (8), 2095-2107. https://doi.org/10.1049/iet-pel.2018.5767Albertos, P., Garcia, P., Gao, Z., Liu, T., 2014. Disturbance rejection in process control. In: Proceeding of the 11th World Congress on Intelligent Control and Automation. IEEE. https://doi.org/10.1109/wcica.2014.7053408Baquero-Suarez, M., Cortes-Romero, J., Arcos-Legarda, J., Coral-Enriquez, H., 2018. Estabilización automática de una bicicleta sin conductor mediante el enfoque de control por rechazo activo de perturbaciones. Revista Iberoamericana de Automática e Informática industrial 15 (1), 86-100. https://doi.org/10.4995/riai.2017.8832Castillo, A., García, P., Sanz, R., Albertos, P., 2018. Enhanced extended state observer-based control for systems with mismatched uncertainties and disturbances. ISA Transactions 73, 1-10. https://doi.org/10.1016/j.isatra.2017.12.005Chen, W.-H., Yang, J., Guo, L., Li, S., 2016. Disturbance-observer-based control and related methods-an overview. IEEE Transactions on Industrial Electronics 63 (2), 1083-1095. https://doi.org/10.1109/tie.2015.2478397Cheng, Y., Chen, Z., Sun, M., Sun, Q., Aug. 2019. Active disturbance rejection generalized predictive control for a high purity distillation column process with time delay. The Canadian Journal of Chemical Engineering 97 (11), 2941-2951. https://doi.org/10.1002/cjce.23513Chu, Z.,Wu, C., Sepehri, N., 2019. Active disturbance rejection control applied to high-order systems with parametric uncertainties. International Journal of Control, Automation and Systems 17 (6), 1483-1493. https://doi.org/10.1007/s12555-018-0509-8Feng, H., Guo, B.-Z., 2017. Active disturbance rejection control: Old and new results. Annual Reviews in Control 44, 238-248. https://doi.org/10.1016/j.arcontrol.2017.05.003Fu, C., Tan, W., 2016. Tuning of linear ADRC with known plant information. ISA Transactions 65, 384-393. https://doi.org/10.1016/j.isatra.2016.06.016Gao, Z., 2003. Scaling and bandwidth-parameterization based controller tuning. In: Proceedings of the 2003 American Control Conference, 2003. IEEE. https://doi.org/10.1109/acc.2003.1242516Gao, Z., 2014. On the centrality of disturbance rejection in automatic control. ISA Transactions 53 (4), 850-857. https://doi.org/10.1016/j.isatra.2013.09.012Guerrero-Ramírez, E. O., Martínez-Barbosa, A., Ramírez, E.-G., Linares-Flores, J., Sira-Ramírez, H., 2018. Control del convertidor CD/CD reductor-paralelo implementado en FPGA. Revista Iberoamericana de Automática e Informática industrial 15 (3), 309-316. https://doi.org/10.4995/riai.2018.8925Guo, B.-Z., Zhao, Z.-L., 2016. Active Disturbance Rejection Control for Nonlinear Systems. John Wiley & Sons Singapore Pte. Ltd. https://doi.org/10.1002/9781119239932Han, J., 2009. From PID to active disturbance rejection control. IEEE Transactions on Industrial Electronics 56 (3), 900-906. https://doi.org/10.1109/tie.2008.2011621He, T., Wu, Z., Li, D., Wang, J., 2020. A tuning method of active disturbance rejection control for a class of high-order processes. IEEE Transactions on Industrial Electronics 67 (4), 3191-3201. https://doi.org/10.1109/tie.2019.2908592Herbst, G., 2013. A simulative study on active disturbance rejection control (ADRC) as a control tool for practitioners. Electronics 2 (4), 246-279. https://doi.org/10.3390/electronics2030246Herbst, G., 2016. Practical active disturbance rejection control: Bumpless transfer, rate limitation, and incremental algorithm. IEEE Transactions on Industrial Electronics 63 (3), 1754-1762. https://doi.org/10.1109/tie.2015.2499168Huang, C., Du, B., 2016. Dierentially flatness active disturbance rejection control approach via algebraic parameter identification to double tank problem. In: 2016 35th Chinese Control Conference (CCC). IEEE. https://doi.org/10.1109/chicc.2016.7553678Huang, Y., Xue, W., 2014. Active disturbance rejection control: Methodology and theoretical analysis. ISA Transactions 53 (4), 963-976. https://doi.org/10.1016/j.isatra.2014.03.003Huilcapi, V., Herrero, J. M., Blasco, X., Martínez-Iranzo, M., 2017. Non-linear identification of a peltier cell model using evolutionary multi-objective optimization. IFAC-PapersOnLine 50 (1), 4448-4453. https://doi.org/10.1016/j.ifacol.2017.08.372Inoue, S., Ishida, Y., 2016. Design of a model-following controller using a decoupling active disturbance rejection control method. Journal of Electrical & Electronic Systems 05 (01). https://doi.org/10.4172/2332-0796.1000174Li, D., Chen, X., Zhang, J., Jin, Q., 2020. On parameter stability region of LADRC for time-delay analysis with a coupled tank application. Processes 8 (2), 223. https://doi.org/10.3390/pr8020223Li, J., Qi, X. H., Wan, H., Xia, Y. Q., 2017a. Active disturbance rejection control: theoretical results summary and future researches. Kongzhi Lilun Yu Yingyong/Control Theory and Applications 34, 281-295. https://doi.org/10.7641/CTA.2017.60363Li, J., Xia, Y., Qi, X., Gao, Z., 2017b. On the necessity, scheme, and basis of the linear-nonlinear switching in active disturbance rejection control. IEEE Transactions on Industrial Electronics 64 (2), 1425-1435. https://doi.org/10.1109/tie.2016.2611573Li, S., Yang, J., Chen,W.-H., Chen, X., 2012. Generalized extended state observer based control for systems with mismatched uncertainties. IEEE Transactions on Industrial Electronics 59 (12), 4792-4802. https://doi.org/10.1109/tie.2011.2182011Liang, Q., Wang, C. B., Pan, J. W., Wei, Y. H., Wang, Y., 2015. Parameter identification of b0 and parameter tuning law in linear active disturbance rejection control. Kongzhi yu Juece/Control and Decision 30, 1691-1695. https://doi.org/10.13195/j.kzyjc.2014.0943Luyben, W. L., 1990. Process Modeling, Simulation, and Control for Chemical Engineers. McGraw-Hill.Madonski, R., Gao, Z., Lakomy, K., 2015. Towards a turnkey solution of industrial control under the active disturbance rejection paradigm. In: 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). IEEE. https://doi.org/10.1109/sice.2015.7285478Madonski, R., Piosik, A., Herman, P., 2013. High-gain disturbance observer tuning seen as a multicriteria optimization problem. In: 21st Mediterranean Conference on Control and Automation. IEEE. https://doi.org/10.1109/med.2013.6608905Madonski, R., Shao, S., Zhang, H., Gao, Z., Yang, J., Li, S., 2019. General error-based active disturbance rejection control for swift industrial implementations. 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In: 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s). IEEE. https://doi.org/10.1109/imac4s.2013.6526432Pérez-Polo, M., Albertos, P., 2007. Nonisothermal stirred-tank reactor with irreversible exothermic reaction a ! b: 2. nonlinear phenomena. In: Selected Topics in Dynamics and Control of Chemical and Biological Processes. Springer Berlin Heidelberg, pp. 243-279. https://doi.org/10.1007/978-3-540-73187_8Reynoso, G., Blasco, X., Sanchis, J., Herrero, J. M., 2017. Controller Tuning with Evolutionary Multiobjective Optimization. Springer International Publishing. https://doi.org/10.1007/978-3-319-41301-3Sanz, R., Garcia, P., Albertos, P., 2015. Active disturbance rejection by state feedback: Experimental validation in a 3-dof quadrotor platform. In: 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE). pp. 794-799. https://doi.org/10.1109/SICE.2015.7285349Sira-Ramírez, H., 2018. From flatness, GPI observers, GPI control and flat filters to observer-based ADRC. Control Theory and Technology 16 (4), 249-260. https://doi.org/10.1007/s11768-018-8134-xSun, L., Li, D., Gao, Z., Yang, Z., Zhao, S., 2016. Combined feedforward and model-assisted active disturbance rejection control for non-minimum phase system. ISA Transactions 64, 24-33. https://doi.org/10.1016/j.isatra.2016.04.020Sun, L., Zhang, Y., Li, D., Lee, K. Y., 2019. Tuning of active disturbance rejection control with application to power plant furnace regulation. Control Engineering Practice 92, 104122. https://doi.org/10.1016/j.conengprac.2019.104122Tan,W., Fu, C., 2016. Linear active disturbance-rejection control: Analysis and tuning via imc. IEEE Transactions on Industrial Electronics 63 (4), 2350-2359.Teppa-Garran, P., Garcia, G., 2014. ADRC tuning employing the LQR approach for decoupling uncertain MIMO systems. 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    Nonlinear adaptive speed control of a permanent magnet synchronous motor: A perturbation estimation approach

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    This paper presents a nonlinear adaptive control (NAC) scheme for the speed regulation of a permanent magnet synchronous motor (PMSM) based on perturbation estimation and feedback linearizing control. All PMSM system’s unknown nonlinearities, parameter uncertainties, and external disturbances including unknown time-varying load torque disturbance, are defined as lumped perturbation terms, which are estimated by designing perturbation observers. The estimates are used to adaptively compensate the real perturbations and achieve adaptive feedback linearizing control of the original nonlinear system. The proposed control scheme does not require accurate system model and full state feedback. Stability of the close-loop system with proposed NAC is investigated via Lyapunov theory, and the effectiveness of proposed NAC scheme is verified through both simulation and experimental studies. Both simulation and experimental results show that the proposed NAC scheme can provide less regulation error in speed tracking, better dynamic performance and robustness against parameter uncertainties and load torque disturbance, compared with conventional vector control and load torque estimated based control

    Design of robust MPPT controller for grid-connected PMSG-Based wind turbine via perturbation observation based nonlinear adaptive control

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    This paper presents a robust maximum power point tracking (MPPT) control scheme for a grid-connected permanent magnet synchronous generator based wind turbine (PMSG-WT) using perturbation observation based nonlinear adaptive control. In the proposed control scheme, system nonlinearities, parameter uncertainties, and external disturbances of the PMSG-WT are represented as a lumped perturbation term, which is estimated by a high-gain perturbation observer. The estimate of the lumped perturbation is employed to compensate the actual perturbation and further achieve adaptive feedback linearizing control of the original nonlinear system, without requiring the detailed system model and full state measurements. The effectiveness of the proposed control scheme is verified through both simulation studies and experimental tests. The results show that, compared with the conventional vector controller and the standard feedback linearizing controller, the proposed control strategy provides higher power conversion efficiency and has better dynamic performances and robustness against parameter uncertainties and external disturbances
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