Vibration suppression in multi-body systems by means of disturbance filter design methods

This paper addresses the problem of interaction in mechanical multi-body systems and shows that subsystem interaction can be considerably minimized while increasing performance if an efficient disturbance model is used. In order to illustrate the advantage of the proposed intelligent disturbance filter, two linear model based techniques are considered: IMC and the model based predictive (MPC) approach. As an illustrative example, multivariable mass-spring-damper and quarter car systems are presented. An adaptation mechanism is introduced to account for linear parameter varying LPV conditions. In this paper we show that, even if the IMC control strategy was not designed for MIMO systems, if a proper filter is used, IMC can successfully deal with disturbance rejection in a multivariable system, and the results obtained are comparable with those obtained by a MIMO predictive control approach. The results suggest that both methods perform equally well, with similar numerical complexity and implementation effort

Controller Tuning Using System Identification

In the industries today, less attention has been put on the development of a unified tuning approach for Proportional-Integral-Derivative (PID) controller of Single Input Single Output (SISO) system and Multiple Input Multiple Output (MIMO) system. The current tuning methods are limited and specific to particular systems. This paper focuses on the development of a unified controller tuning method based on Internal Model Control (IMC) method and system identification using software Matlab Simulink. The controller tuning performance of the proposed method tested on SISO and MIMO systems are being compared with the performance shown by the existing tuning methods; Ziegler-Nichols (ZN) and Simple Internal Model Control (SIMC). The evaluation of performance measurement is done based on Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time-weighted Absolute Error (ITAE) and Total Input Variation (TV). It is observed that the proposed unified tuning method is effective for tuning on SISO and MIMO systems and gives better performance than ZN and SIMC in terms of IAE, ISE, ITAE and TV in both set point tracking and disturbance rejection

Smith Predictor with Inverted Decoupling for Square Multivariable Time Delay Systems

Versión del autorThis paper presents a new methodology to design multivariable Smith predictor for n×n processes with multiple time delays based on the centralized inverted decoupling structure. The controller elements are calculated in order to achieve good reference tracking and decoupling response. Independently of the system size, very simple general expressions for the controller elements are obtained. The realizability conditions are provided and the particular case of processes with all of its elements as first order plus time delay systems is discussed in more detail. A diagonal filter is added to the proposed control structure in order to improve the disturbance rejection without modifying the nominal set-point response and to obtain a stable output prediction in unstable plants. The effectiveness of the method is illustrated through different simulation examples in comparison with other works

A classification of techniques for the compensation of time delayed processes. Part 2: Structurally optimised controllers

Following on from Part 1, Part 2 of the paper considers the use of structurally optimised controllers to compensate time delayed processes

Rejection of mismatched disturbances for systems with input delay via a predictive extended state observer

[EN] The problem of output stabilization and disturbance rejection for input-delayed systems is tackled in this work. First, a suitable transformation is introduced to translate mismatched disturbances into an equivalent input disturbance. Then, an extended state observer is combined with a predictive observer structure to obtain a future estimation of both the state and the disturbance. A disturbance model is assumed to be known but attenuation of unmodeled components is also considered. The stabilization is proved via Lyapunov-Krasovskii functionals, leading to sufficient conditions in terms of linear matrix inequalities for the closed-loop analysis and parameter tuning. The proposed strategy is illustrated through a numerical example.PROMETEOII/2013/004; Conselleria d'Educacio; Generalitat Valenciana, Grant/Award Number: TIN2014-56158-C4-4-P-AR; Ministerio de Economia y Competitividad, Grant/Award Number: FPI-UPV 2014; Universitat Politecnica de ValenciaSanz Diaz, R.; García Gil, PJ.; Fridman, E.; Albertos Pérez, P. (2018). Rejection of mismatched disturbances for systems with input delay via a predictive extended state observer. International Journal of Robust and Nonlinear Control. 28(6):2457-2467. https://doi.org/10.1002/rnc.4027S24572467286Stability and Stabilization of Systems with Time Delay. (2011). IEEE Control Systems, 31(1), 38-65. doi:10.1109/mcs.2010.939135Fridman, E. (2014). Introduction to Time-Delay Systems. Systems & Control: Foundations & Applications. doi:10.1007/978-3-319-09393-2Watanabe, K., & Ito, M. (1981). A process-model control for linear systems with delay. IEEE Transactions on Automatic Control, 26(6), 1261-1269. doi:10.1109/tac.1981.1102802Astrom, K. J., Hang, C. C., & Lim, B. C. (1994). A new Smith predictor for controlling a process with an integrator and long dead-time. IEEE Transactions on Automatic Control, 39(2), 343-345. doi:10.1109/9.272329Matausek, M. R., & Micic, A. D. (1996). A modified Smith predictor for controlling a process with an integrator and long dead-time. IEEE Transactions on Automatic Control, 41(8), 1199-1203. doi:10.1109/9.533684García, P., & Albertos, P. (2008). A new dead-time compensator to control stable and integrating processes with long dead-time. Automatica, 44(4), 1062-1071. doi:10.1016/j.automatica.2007.08.022Normey-Rico, J. E., & Camacho, E. F. (2009). Unified approach for robust dead-time compensator design. Journal of Process Control, 19(1), 38-47. doi:10.1016/j.jprocont.2008.02.003Manitius, 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.1982.1103023Krstic, 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.2014.11.003Sanz, R., Garcia, P., & Albertos, P. (2016). Enhanced disturbance rejection for a predictor-based control of LTI systems with input delay. Automatica, 72, 205-208. doi:10.1016/j.automatica.2016.05.019Basturk, H. I., & Krstic, M. (2015). Adaptive sinusoidal disturbance cancellation for unknown LTI systems despite input delay. Automatica, 58, 131-138. doi:10.1016/j.automatica.2015.05.013Basturk, H. I. (2017). Cancellation of unmatched biased sinusoidal disturbances for unknown LTI systems in the presence of state delay. Automatica, 76, 169-176. doi:10.1016/j.automatica.2016.10.006Sanz, R., Garcia, P., Albertos, P., & Zhong, Q.-C. (2016). 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. doi:10.1002/rnc.3639Mondie, S., & Michiels, W. (2003). Finite spectrum assignment of unstable time-delay systems with a safe implementation. IEEE Transactions on Automatic Control, 48(12), 2207-2212. doi:10.1109/tac.2003.820147Zhong, Q.-C. (2004). On Distributed Delay in Linear Control Laws—Part I: Discrete-Delay Implementations. IEEE Transactions on Automatic Control, 49(11), 2074-2080. doi:10.1109/tac.2004.837531Zhou, B., Lin, Z., & Duan, G.-R. (2012). Truncated predictor feedback for linear systems with long time-varying input delays. Automatica, 48(10), 2387-2399. doi:10.1016/j.automatica.2012.06.032Zhou, B., Li, Z.-Y., & Lin, Z. (2013). On higher-order truncated predictor feedback for linear systems with input delay. International Journal of Robust and Nonlinear Control, 24(17), 2609-2627. doi:10.1002/rnc.3012Besançon G Georges D Benayache Z Asymptotic state prediction for continuous-time systems with delayed input and application to control IEEE 2007 Kos, GreeceNajafi, M., Hosseinnia, S., Sheikholeslam, F., & Karimadini, M. (2013). Closed-loop control of dead time systems via sequential sub-predictors. International Journal of Control, 86(4), 599-609. doi:10.1080/00207179.2012.751627Léchappé V Moulay E Plestan F Dynamic observation-prediction for LTI systems with a time-varying delay in the input IEEE 2016 Las Vegas, NVCacace, 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.3517Mazenc, F., & Malisoff, M. (2017). Stabilization of Nonlinear Time-Varying Systems Through a New Prediction Based Approach. IEEE Transactions on Automatic Control, 62(6), 2908-2915. doi:10.1109/tac.2016.2600500Guo, 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.978Fridman, E. (2003). Output regulation of nonlinear systems with delay. Systems & Control Letters, 50(2), 81-93. doi:10.1016/s0167-6911(03)00131-2Isidori, A., & Byrnes, C. I. (1990). Output regulation of nonlinear systems. IEEE Transactions on Automatic Control, 35(2), 131-140. doi:10.1109/9.45168Ding, Z. (2003). Global stabilization and disturbance suppression of a class of nonlinear systems with uncertain internal model. Automatica, 39(3), 471-479. doi:10.1016/s0005-1098(02)00251-0Chen, 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.2015.2478397Fridman, 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., & Orlov, Y. (2009). Exponential stability of linear distributed parameter systems with time-varying delays. Automatica, 45(1), 194-201. doi:10.1016/j.automatica.2008.06.00

Predictor-based robust control of dead-time processes

Tese (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2015.Esta tese trata do problema de controle robusto de sistemas não-lineares com atraso utilizando estruturas de compensação de atraso. Como já descrito na literatura, três são os problemas causados pela presença de atraso de transporte: (i) os efeitos das perturbações não são notados até se passar o tempo do atraso, (ii) o efeito da ação de controle demora para ser notado na variável controlada, e (iii) a ação de controle que é aplicada no instante atual tenta corrigir uma situação que se originou tempos atrás. Uma das mais utilizadas soluções para evitar (ou atenuar) esses efeitos é o uso do Preditor de Smith (SP - Smith Predictor). Preditores são estruturas que permitem o controle de processos com atraso a partir de um modelo sem atraso, o que simplifica o ajuste do controlador. Uma importante propriedade do Preditor de Smith vem do fato de que a robustez do sistema de malha fechada resultante não depende do valor nominal do atraso. Esta propriedade, no entanto, não é válida para qualquer preditor. Por exemplo, algoritmos de controle preditivo (MPC - Model Based Predictive Controllers) definem implicitamente estruturas preditoras, mas, como já foi mostrado na literatura, no caso específico do GPC (Generalized Predictive Control), o preditor ótimo definido implicitamente faz com que a robustez do sistema dependa do valor nominal do atraso. Também já havia sido mostrado que, substituindo este preditor implícito por um Preditor de Smith Filtrado (FSP - Filtered Smith Predictor), resulta em um controlador mais robusto que herda as características do SP. Assim, os objetivos desta tese são: (i) Estudo do algoritmo preditivo Dynamic Matrix Control (DMC), através de uma estrutura FSP, e propor modificações que permitam melhorar a rejeição de perturbações e/ou aumentar a robustez do sistema; (ii) análise e implementação de uma estrutura baseada no FSP para sistemas não-lineares. Os algoritmos de controle preditivo, ou MPC, emergiram durante as últimas três décadas como uma poderosa solução de controle, e obtiveram um impacto significativo na indústria, como já mostrado em diversos trabalhos. No entanto, apesar de grandes avanços teóricos e do fato de que os processos industriais são, em geral, não lineares, a maioria das técnicas de controle aplicadas na indústria são baseadas em modelos lineares. Algoritmos MPC simples baseados em modelos de resposta ao degrau (ou impulsiva) sem garantia de estabilidade são os mais comuns na indústria, principalmente em refinarias e plantas petroquímicas. Algumas razões para isso são: (i) os processos possuem comportamento estável em malha aberta e ajustando adequadamente os parâmetros do controlador é possível obter a estabilidade do sistema em malha fechada, e (ii) modelos lineares são suficientes quando o processo está operando próximo de um ponto de operação. Desta forma, a análise das propriedades de malha fechada desses controladores, como velocidade de rejeição de perturbação e robustez, é muito importante para a indústria de processos, já que é possível obter modificações simples e úteis que melhoram o desempenho de aplicações reais. Assim, neste trabalho, o algoritmo preditivo DMC será interpretado através da estrutura FSP de forma que os efeitos do atraso no sistema de malha fechada possam ser entendidos. Esta abordagem foi escolhida por permitir que várias técnicas de sintonia já desenvolvidas para o FSP possam ser aplicadas ao DMC. Será mostrado que o algoritmo DMC precisa apenas de pequenas modificações para adquirir as vantagens fornecidas pela estrutura FSP. O segundo tópico deste trabalho trata de estruturas preditoras para sistemas não-lineares. Seguindo as ideias propostas para o caso linear, neste trabalho será proposto o Preditor de Smith Filtrado para Sistemas Não-Lineares (NLFSP - Nonlinear Filtered Smith Predictor), que permitirá melhorar as características de robustez e rejeição de perturbação de sistemas não lineares. Já há trabalhos evidenciando algumas vantagens do FSP para sistemas não-lineares, no entanto não há provas nem uma análise formal de suas propriedades. O FSP linear possui as seguintes características: (i) a resposta nominal para mudanças de referência não é afetada pela inserção do filtro de predição; (ii) a robustez pode ser melhorada ajustando o filtro adequadamente; (iii) o filtro de predição pode ser ajustado para acelerar a rejeição de perturbações. Vários exemplos de simulação são apresentados no documento para ilustrar os resultados teóricos apresentados. Em particular, se aplicam os resultados a processos da indústria do petróleo e petroquímica onde os controladores preditivos têm um grande impacto.Abstract : This thesis deals with the analysis and design of predictor-based robust controllers for processes with dead time. The main objectives are: (i) to analyze the effect of the predictor structure in the closed-loop behavior and robustness of linear and nonlinear controllers; (ii) to propose better predictor structures to improve robustness and performance of control loops; (iii) to apply the results in simulated and real industrial processes, mainly for the petroleum industry. The results of this thesis are: an improvement on the well-known Dynamic Matrix Control (DMC) algorithm, from the Model Predictive Control (MPC) family, and a predictor for nonlinear systems with time delay based on the Smith Predictor. Concerning the MPC, in this work, an improved industrial MPC controller based on the widely used DMC approach is presented. A MIMO filter is included in the prediction model of the controller in order to achieve two important advantages when compared to traditional industrial DMC: (i) disturbance rejection response can be speeded up and (ii) robustness can be improved, mainly when errors in the estimation of the delays are considered. The filter properties are demonstrated by means of an equivalent analysis of the unconstrained DMC using a dead time compensation (DTC) approach, namely the Filtered Smith Predictor. Moreover, implementation and tuning of the filter is simple and intuitive. Simulation results using a water-methanol distillation column are presented to illustrate the advantages of the proposed approach. For the case of nonlinear processes with time delay, a Nonlinear Filtered Smith Predictor (NLFSP) structure is proposed for nonlinear systems. It will be shown that the NLFSP maintains the characteristics of the linear Smith Predictor and that, with appropriate tuning, it can increase the robustness of the closed-loop system. The NLFSP is applied to various examples and case studies to demonstrate these characteristics

Robust control strategies for unstable systems with input/output delays

Los sistemas con retardo temporal aparecen con frecuencia en el ámbito de la ingeniería, por ejemplo en transmisiones hidráulicas o mecánicas, procesos metalúrgicos o sistemas de control en red. Los retardos temporales han despertado el interés de los investigadores en el ámbito del control desde finales de los años 50. Se ha desarrollado una amplia gama de herramientas para el análisis de su estabilidad y prestaciones, especialmente durante las dos últimas décadas. Esta tesis se centra en la estabilización de sistemas afectados por retardos temporales en la actuación y/o la medida. Concretamente, las contribuciones que aquí se incluyen tienen por objetivo mejorar las prestaciones de los controladores existentes en presencia de perturbaciones. Los retardos temporales degradan, inevitablemente, el desempeño de un bucle de control. No es de extrañar que el rechazo de perturbaciones haya sido motivo de estudio desde que emergieron los primeros controladores predictivos para sistemas con retardo. Las estrategias presentadas en esta tesis se basan en la combinación de controladores predictivos y observadores de perturbaciones. Estos últimos han sido aplicados con éxito para mejorar el rechazo de perturbaciones de controladores convencionales. Sin embargo, la aplicación de esta metodología a sistemas con retardo es poco frecuente en la literatura, la cual se investiga exhaustivamente en esta tesis. Otro inconveniente de los controladores predictivos está relacionado con su implementación, que puede llevar a la inestabilidad si no se realiza cuidadosamente. Este fenómeno está relacionado con el hecho de que las leyes de control predictivas se expresan mediante una ecuación integral. En esta tesis se presenta una estructura de control alternativa que evita este problema, la cual utiliza un observador de dimensión infinita, gobernado por una ecuación en derivadas parciales de tipo hiperbólico.Time-delay systems are ubiquitous in many engineering applications, such as mechanical or fluid transmissions, metallurgical processes or networked control systems. Time-delay systems have attracted the interest of control researchers since the late 50's. A wide variety of tools for stability and performance analysis has been developed, specially over the past two decades. This thesis is focused on the problem of stabilizing systems that are affected by delays on the actuator and/or sensing paths. More specifically, the contributions herein reported aim at improving the performance of existing controllers in the presence of external disturbances. Time delays unavoidably degrade the control loop performance. Disturbance rejection has been a matter of concern since the first predictive controllers for time-delay systems emerged. The key idea of the strategies presented in this thesis is the combination of predictive controllers and disturbance observers. The latter have been successfully applied to improve the disturbance rejection capabilities of conventional controllers. However, the application of this methodology to time-delay systems is rarely found in the literature. This combination is extensively investigated in this thesis. Another handicap of predictive controllers has to do with their implementation, which can induce instability if not done carefully. This issue is related to the fact that predictive control laws take the form of integral equations. An alternative control structure that avoids this problem is also reported in this thesis, which employs an infinite-dimensional observer, governed by a hyperbolic partial differential equation.Sanz Díaz, R. (2018). Robust control strategies for unstable systems with input/output delays [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/111830TESI

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). 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Dynamic Mathematical Modelling and Advanced Control Strategies for Complex Hydrogenation Process

Over the last past decades, the number of control system applications in the chemical and petrochemical domains has increased considerably. However, due to the diversity and particularity of chemical processes, there are still many challenges that have to be addressed like: system identification, performance enhancement, monitoring, diagnosis and more importantly closed-loop stability, robustness. Taking into account that most chemical processes are complex, nonlinear MIMO (multi-input multi-output) systems, the challenge is even greater. This book chapter is directed towards the development and the implementation of modern control algorithms for complex and high-risk petro-chemical processes, the considered case study being the production of 2 ethyl-hexanol through the 2 ethyl-hexenal hydrogenation process. 2 ethyl-hexanol is mainly used in the production of plasticizers for polyvinyl chloride (PVC) manufacture. In the second part, is described the mathematical modelling of the 2 ethyl-hexenal hydrogenation process including also the simulation and validation of the developed mathematical models. The third part will focus on the design and implementation of conventional control strategy. Section four is dedicated to the design and implementation of several advanced control strategies like Internal Model Control and robust control. The conclusions section represents the last part of the chapter