Modified active disturbance rejection control for time-delay systems

Industrial processes are typically nonlinear, time-varying and uncertain, to which active disturbance rejection control (ADRC) has been shown to be an effective solution. The control design becomes even more challenging in the presence of time delay. In this paper, a novel modification of ADRC is proposed so that good disturbance rejection is achieved while maintaining system stability. The proposed design is shown to be more effective than the standard ADRC design for time-delay systems and is also a unified solution for stable, critical stable and unstable systems with time delay. Simulation and test results show the effectiveness and practicality of the proposed design. Linear matrix inequality (LMI) based stability analysis is provided as well

Modified active disturbance rejection control for time-delay systems

Industrial processes are typically nonlinear, time-varying and uncertain, to which active disturbance rejection control (ADRC) has been shown to be an effective solution. The control design becomes even more challenging in the presence of time delay. In this paper, a novel modification of ADRC is proposed so that good disturbance rejection is achieved while maintaining system stability. The proposed design is shown to be more effective than the standard ADRC design for time-delay systems and is also a unified solution for stable, critical stable and unstable systems with time delay. Simulation and test results show the effectiveness and practicality of the proposed design. Linear matrix inequality (LMI) based stability analysis is provided as well

Active disturbance rejection control: a guide for design and application

[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. Control Engineering Practice 84, 218-229. https://doi.org/10.1016/j.conengprac.2018.11.021Marlin, T., 2000. Process Control: Designing Processes and Control Systems for Dynamic Performance. McGraw-Hill.Martínez, B. V., Jul 2020. Active Disturbance Rejection Control-implementation examples. Version 1.0.0. url: https://www.mathworks.com/matlabcentral/fileexchange/78459.Maxim, A., Copot, D., Copot, C., Ionescu, C. M., 2019. The 5w's for control as part of industry 4.0: Why, what, where, who, and when-a PID and MPC control perspective. Inventions 4 (1), 10. https://doi.org/10.3390/inventions4010010Nowicki, M., Madonski, R., Kozlowski, K., 2015. First look at conditions on applicability of ADRC. In: 2015 10th International Workshop on Robot Motion and Control (RoMoCo). IEEE. https://doi.org/10.1109/romoco.2015.7219750Parvathy, R., Daniel, A. E., 2013. A survey on active disturbance rejection control. 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. Information Technology And Control 43 (2). https://doi.org/10.5755/j01.itc.43.2.4059Wu, X., Chen, Z., Zhao, Y., Sun, L., Sun, M., 2018. A comprehensive decoupling control strategy for a gas flow facility based on active disturbance rejection generalized predictive control. The Canadian Journal of Chemical Engineering 97 (3), 762-776. https://doi.org/10.1002/cjce.23215Xue,W., Huang, Y., 2015. Performance analysis of active disturbance rejection tracking control for a class of uncertain LTI systems. ISA Transactions 58, 133-154. https://doi.org/10.1016/j.isatra.2015.05.001Xue, W., Huang, Y., Gao, Z., 2016. On ADRC for non-minimum phase systems: canonical form selection and stability conditions. Control Theory and Technology 14 (3), 199-208. https://doi.org/10.1007/s11768-016-6041-6Zhang, B., Tan, W., Li, J., 2019. Tuning of linear active disturbance rejection controller with robustness specification. ISA Transactions 85, 237-246. https://doi.org/10.1016/j.isatra.2018.10.018Zhao, C., Li, D., 2014. Control design for the SISO system with the unknown order and the unknown relative degree. ISA Transactions 53 (4), 858-872. https://doi.org/10.1016/j.isatra.2013.10.001Zhao, C., Li, D., Cui, J., Tian, L., 2018. Decentralized low-order ADRC design for MIMO system with unknown order and relative degree. Personal and Ubiquitous Computing 22 (5-6), 987-1004. https://doi.org/10.1007/s00779-018-1158-xZhao, S., Gao, Z., 2010. Active disturbance rejection control for non-minimum phase systems. In: Proceedings of the 29th Chinese Control Conference. pp. 6066-6070.Zhao, S., Gao, Z., 2014. Modified active disturbance rejection control for time delay systems. ISA Transactions 53 (4), 882-888. https://doi.org/10.1016/j.isatra.2013.09.013Zhao, S., Xue, W., Gao, Z., 2013. Achieving minimum settling time subject to undershoot constraint in systems with one or two real right half plane zeros. Journal of Dynamic Systems, Measurement, and Control 135 (3). https://doi.org/10.1115/1.4023211Zheng, Q., Chen, Z., Gao, Z., 2009. A practical approach to disturbance decoupling control. Control Engineering Practice 17 (9), 1016-1025. https://doi.org/10.1016/j.conengprac.2009.03.005Zheng, Q., Gao, L. Q., Gao, Z., 2012. On validation of extended state observer through analysis and experimentation. Journal of Dynamic Systems, Measurement, and Control 134 (2). https://doi.org/10.1115/1.4005364Zheng, Q., Gao, Z., 2010. On practical applications of active disturbance rejection control. In: Proceedings of the 29th Chinese Control Conference. pp. 6095-6100.Zheng, Q., Gao, Z., 2016. Active disturbance rejection control: between the formulation in time and the understanding in frequency. Control Theory and echnology 14 (3), 250-259. https://doi.org/10.1007/s11768-016-6059-9Zheng, Q., Gao, Z., 2018. Active disturbance rejection control: some recent experimental and industrial case studies. Control Theory and Technology 16 (4), 301-313. https://doi.org/10.1007/s11768-018-8142-xZheng, Q., Gaol, L. Q., Gao, Z., 2007. On stability analysis of active disturbance rejection control for nonlinear time-varying plants with unknown dynamics. In: 2007 46th IEEE Conference on Decision and Control. IEEE. https://doi.org/10.1109/cdc.2007.4434676Zhou, R., Tan,W., 2019. Analysis and tuning of general linear active disturbance rejection controllers. IEEE Transactions on Industrial Electronics 66 (7), 5497-5507. https://doi.org/10.1109/tie.2018.286934

Design and practical implementation of a fractional order proportional integral controller (FOPI) for a poorly damped fractional order process with time delay

One of the most popular tuning procedures for the development of fractional order controllers is by imposing frequency domain constraints such as gain crossover frequency, phase margin and iso-damping properties. The present study extends the frequency domain tuning methodology to a generalized range of fractional order processes based on second order plus time delay (SOPDT) models. A fractional order PI controller is tuned for a real process that exhibits poorly damped dynamics characterized in terms of a fractional order transfer function with time delay. The obtained controller is validated on the experimental platform by analyzing staircase reference tracking, input disturbance rejection and robustness to process uncertainties. The paper focuses around the tuning methodology as well as the fractional order modeling of the process' dynamics

Robust controller design for input-delayed systems using predictive feedback and an uncertainty estimator

[EN] This paper deals with the problem of stabilizing a class of input-delayed systems with (possibly) nonlinear uncertainties by using explicit delay compensation. It is well known that plain predictive schemes lack robustness with respect to uncertain model parameters. In this work, an uncertainty estimator is derived for input-delay systems and combined with a modified state predictor, which uses current available information of the estimated uncertainties. Furthermore, based on Lyapunov-Krasovskii functionals, a computable criterion to check robust stability of the closed-loop is developed and cast into a minimization problem constrained to an LMI. Additionally, for a given input delay, an iterative-LMI algorithm is proposed to design stabilizing tuning parameters. The main results are illustrated and validated using a numerical example with a second-order dynamic system.This work was partially supported by projects PROMETEOII/2013/004, Conselleria d Educació, Generalitat Valenciana, and TIN2014-56158-C4-4-P-AR, Ministerio de Economía y Competitividad, Spain.Sanz Diaz, R.; García Gil, PJ.; Albertos Pérez, P.; Zhong, Q. (2017). Robust controller design for input-delayed systems using predictive feedback and an uncertainty estimator. International Journal of Robust and Nonlinear Control. 27(10):1826-1840. https://doi.org/10.1002/rnc.3639S182618402710Stability and Stabilization of Systems with Time Delay. (2011). IEEE Control Systems, 31(1), 38-65. doi:10.1109/mcs.2010.939135Normey-Rico, J. E., Bordons, C., & Camacho, E. F. (1997). Improving the robustness of dead-time compensating PI controllers. Control Engineering Practice, 5(6), 801-810. doi:10.1016/s0967-0661(97)00064-6Michiels, W., & Niculescu, S.-I. (2003). On the delay sensitivity of Smith Predictors. International Journal of Systems Science, 34(8-9), 543-551. doi:10.1080/00207720310001609057Normey-Rico, J. E., & Camacho, E. F. (2008). Dead-time compensators: A survey. Control Engineering Practice, 16(4), 407-428. doi:10.1016/j.conengprac.2007.05.006Guzmán, J. L., García, P., Hägglund, T., Dormido, S., Albertos, P., & Berenguel, M. (2008). Interactive tool for analysis of time-delay systems with dead-time compensators. Control Engineering Practice, 16(7), 824-835. doi:10.1016/j.conengprac.2007.09.002Manitius, A., & Olbrot, A. (1979). Finite spectrum assignment problem for systems with delays. IEEE Transactions on Automatic Control, 24(4), 541-552. doi:10.1109/tac.1979.1102124Artstein, Z. (1982). Linear systems with delayed controls: A reduction. IEEE Transactions on Automatic Control, 27(4), 869-879. doi:10.1109/tac.1982.1103023Moon, Y. S., Park, P., & Kwon, W. H. (2001). Robust stabilization of uncertain input-delayed systems using reduction method. Automatica, 37(2), 307-312. doi:10.1016/s0005-1098(00)00145-xYue, D. (2004). Robust stabilization of uncertain systems with unknown input delay. Automatica, 40(2), 331-336. doi:10.1016/j.automatica.2003.10.005Yue, D., & Han, Q.-L. (2005). Delayed feedback control of uncertain systems with time-varying input delay. Automatica, 41(2), 233-240. doi:10.1016/j.automatica.2004.09.006Lozano, R., Castillo, P., Garcia, P., & Dzul, A. (2004). Robust prediction-based control for unstable delay systems: Application to the yaw control of a mini-helicopter. Automatica, 40(4), 603-612. doi:10.1016/j.automatica.2003.10.007Gonzalez, A., Garcia, P., Albertos, P., Castillo, P., & Lozano, R. (2012). Robustness of a discrete-time predictor-based controller for time-varying measurement delay. Control Engineering Practice, 20(2), 102-110. doi:10.1016/j.conengprac.2011.09.001Karafyllis, I., & Krstic, M. (2013). Robust predictor feedback for discrete-time systems with input delays. International Journal of Control, 86(9), 1652-1663. doi:10.1080/00207179.2013.792005Krstic, M. (2010). Input Delay Compensation for Forward Complete and Strict-Feedforward Nonlinear Systems. IEEE Transactions on Automatic Control, 55(2), 287-303. doi:10.1109/tac.2009.2034923Bekiaris-Liberis, N., & Krstic, M. (2011). Compensation of Time-Varying Input and State Delays for Nonlinear Systems. Journal of Dynamic Systems, Measurement, and Control, 134(1). doi:10.1115/1.4005278Karafyllis, I., Malisoff, M., Mazenc, F., & Pepe, P. (Eds.). (2016). Recent Results on Nonlinear Delay Control Systems. Advances in Delays and Dynamics. doi:10.1007/978-3-319-18072-4Cacace, F., Conte, F., Germani, A., & Pepe, P. (2016). Stabilization of strict-feedback nonlinear systems with input delay using closed-loop predictors. International Journal of Robust and Nonlinear Control, 26(16), 3524-3540. doi:10.1002/rnc.3517Fridman, E., & Shaked, U. (2002). An improved stabilization method for linear time-delay systems. IEEE Transactions on Automatic Control, 47(11), 1931-1937. doi:10.1109/tac.2002.804462Fridman, E., & Shaked, U. (2002). A descriptor system approach to H/sub ∞/ control of linear time-delay systems. IEEE Transactions on Automatic Control, 47(2), 253-270. doi:10.1109/9.983353Chen, W.-H., & Zheng, W. X. (2006). On improved robust stabilization of uncertain systems with unknown input delay. Automatica, 42(6), 1067-1072. doi:10.1016/j.automatica.2006.02.015Krstic, M. (2008). Lyapunov tools for predictor feedbacks for delay systems: Inverse optimality and robustness to delay mismatch. Automatica, 44(11), 2930-2935. doi:10.1016/j.automatica.2008.04.010Léchappé, V., Moulay, E., Plestan, F., Glumineau, A., & Chriette, A. (2015). New predictive scheme for the control of LTI systems with input delay and unknown disturbances. Automatica, 52, 179-184. doi:10.1016/j.automatica.2014.11.003Roh, Y.-H., & Oh, J.-H. (1999). Robust stabilization of uncertain input-delay systems by sliding mode control with delay compensation. Automatica, 35(11), 1861-1865. doi:10.1016/s0005-1098(99)00106-5Bresch-Pietri, D., & Krstic, M. (2009). Adaptive trajectory tracking despite unknown input delay and plant parameters. Automatica, 45(9), 2074-2081. doi:10.1016/j.automatica.2009.04.027Kamalapurkar, R., Fischer, N., Obuz, S., & Dixon, W. E. (2016). Time-Varying Input and State Delay Compensation for Uncertain Nonlinear Systems. IEEE Transactions on Automatic Control, 61(3), 834-839. doi:10.1109/tac.2015.2451472Chen, W.-H., Ohnishi, K., & Guo, L. (2015). Advances in Disturbance/Uncertainty Estimation and Attenuation [Guest editors’ introduction]. IEEE Transactions on Industrial Electronics, 62(9), 5758-5762. doi:10.1109/tie.2015.2453347Chen, 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. doi:10.1109/tie.2015.2478397Sariyildiz E Ohnishi K Design constraints of disturbance observer in the presence of time delay 2013 IEEE International Conference on Mechatronics (ICM) Vicenza, Italy 2013 69 74Wang, Q.-G., Hang, C. C., & Yang, X.-P. (2001). Single-loop controller design via IMC principles. Automatica, 37(12), 2041-2048. doi:10.1016/s0005-1098(01)00170-4Zheng, Q., & Gao, Z. (2014). Predictive active disturbance rejection control for processes with time delay. ISA Transactions, 53(4), 873-881. doi:10.1016/j.isatra.2013.09.021Chen, M., & Chen, W.-H. (2010). Disturbance-observer-based robust control for time delay uncertain systems. International Journal of Control, Automation and Systems, 8(2), 445-453. doi:10.1007/s12555-010-0233-5Guo, L., & Chen, W.-H. (2005). Disturbance attenuation and rejection for systems with nonlinearity via DOBC approach. International Journal of Robust and Nonlinear Control, 15(3), 109-125. doi:10.1002/rnc.978Zhong, Q.-C., & Rees, D. (2004). Control of Uncertain LTI Systems Based on an Uncertainty and Disturbance Estimator. Journal of Dynamic Systems, Measurement, and Control, 126(4), 905-910. doi:10.1115/1.1850529Yong He, Min Wu, & Jin-Hua She. (2005). Improved bounded-real-lemma representation and H/sub /spl infin// control of systems with polytopic uncertainties. IEEE Transactions on Circuits and Systems II: Express Briefs, 52(7), 380-383. doi:10.1109/tcsii.2005.850418CAO, Y.-Y., LAM, J., & SUN, Y.-X. (1998). Static Output Feedback Stabilization: An ILMI Approach. Automatica, 34(12), 1641-1645. doi:10.1016/s0005-1098(98)80021-6Marler, R. T., & Arora, J. S. (2009). The weighted sum method for multi-objective optimization: new insights. Structural and Multidisciplinary Optimization, 41(6), 853-862. doi:10.1007/s00158-009-0460-7Fridman, E. (2014). Introduction to Time-Delay Systems. Systems & Control: Foundations & Applications. doi:10.1007/978-3-319-09393-2Solomon, O., & Fridman, E. (2013). New stability conditions for systems with distributed delays. Automatica, 49(11), 3467-3475. doi:10.1016/j.automatica.2013.08.025Huaizhong Li, & Minyue Fu. (1997). A linear matrix inequality approach to robust H/sub ∞/ filtering. IEEE Transactions on Signal Processing, 45(9), 2338-2350. doi:10.1109/78.622956Šiljak, D. D., & Stipanovic, D. M. (2000). Robust stabilization of nonlinear systems: The LMI approach. Mathematical Problems in Engineering, 6(5), 461-493. doi:10.1155/s1024123x0000143

Temperature control in transport delay systems

A control architecture is proposed for temperature control in manufacturing applications based on the internal model principle. It is applied to a problem where the material exit temperature is to be controlled by changing the transportation speed to influence the amount of heat loss. The internal model is used to achieve a fast response with minimal overshoot. The controller tuning is carried out using constraints on the sensitivity function to map out the controller parameter region to achieve this performance. The robustness of the controller to parametric uncertainty is also considered. Results are shown from the application of this controller to the temperature controller for a hot strip rolling mill

The application of a new PID autotuning method for the steam/water loop in large scale ships

In large scale ships, the most used controllers for the steam/water loop are still the proportional-integral-derivative (PID) controllers. However, the tuning rules for the PID parameters are based on empirical knowledge and the performance for the loops is not satisfying. In order to improve the control performance of the steam/water loop, the application of a recently developed PID autotuning method is studied. Firstly, a 'forbidden region' on the Nyquist plane can be obtained based on user-defined performance requirements such as robustness or gain margin and phase margin. Secondly, the dynamic of the system can be obtained with a sine test around the operation point. Finally, the PID controller's parameters can be obtained by locating the frequency response of the controlled system at the edge of the 'forbidden region'. To verify the effectiveness of the new PID autotuning method, comparisons are presented with other PID autotuning methods, as well as the model predictive control. The results show the superiority of the new PID autotuning method

Robust H∞ fuzzy output-feedback control with multiple probabilistic delays and multiple missing measurements

Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the robust H∞-control problem is investigated for a class of uncertain discrete-time fuzzy systems with both multiple probabilistic delays and multiple missing measurements. A sequence of random variables, all of which are mutually independent but obey the Bernoulli distribution, is introduced to account for the probabilistic communication delays. The measurement-missing phenomenon occurs in a random way. The missing probability for each sensor satisfies a certain probabilistic distribution in the interval. Here, the attention is focused on the analysis and design of H∞ fuzzy output-feedback controllers such that the closed-loop Takagi-Sugeno (T-S) fuzzy-control system is exponentially stable in the mean square. The disturbance-rejection attenuation is constrained to a given level by means of the H∞-performance index. Intensive analysis is carried out to obtain sufficient conditions for the existence of admissible output feedback controllers, which ensures the exponential stability as well as the prescribed H∞ performance. The cone-complementarity-linearization procedure is employed to cast the controller-design problem into a sequential minimization one that is solved by the semi-definite program method. Simulation results are utilized to demonstrate the effectiveness of the proposed design technique in this paper.This work was supported in part by the Engineering and Physical Sciences Research Council, U.K., under Grant GR/S27658/01, in part by the Royal Society, U.K., in part by the National Natural Science Foundation of China under Grant 60825303, in part by the National 973 Project of China under Grant 2009CB320600, in part by the Heilongjiang Outstanding Youth Science Fund of China under Grant JC200809, in part by the Youth Science Fund of Heilongjiang Province of China under Grant QC2009C63, and in part by the Alexander von Humboldt Foundation of Germany