Asymmetric modelling and control of an electronic throttle
Corresponding Author
Gisela Pujol
CoDAlab (Control, Dynamics and Applications), Departament de Matemàtica Aplicada III, Universitat Politècnica de Catalunya, Barcelona, Spain
Correspondence to: Gisela Pujol, Applied Mathematics III, Universitat Politècnica de Catalunya, Colom 1, 08222 Terrassa Spain.,
E-mail: [email protected]
Search for more papers by this authorYolanda Vidal
CoDAlab (Control, Dynamics and Applications), Departament de Matemàtica Aplicada III, Universitat Politècnica de Catalunya, Barcelona, Spain
Search for more papers by this authorLeonardo Acho
CoDAlab (Control, Dynamics and Applications), Departament de Matemàtica Aplicada III, Universitat Politècnica de Catalunya, Barcelona, Spain
Search for more papers by this authorAlessandro N. Vargas
Universidade Tecnólogica Federal do Parana, UTFPR, Electrotechnical Department, Paraná, Brazil
Search for more papers by this authorCorresponding Author
Gisela Pujol
CoDAlab (Control, Dynamics and Applications), Departament de Matemàtica Aplicada III, Universitat Politècnica de Catalunya, Barcelona, Spain
Correspondence to: Gisela Pujol, Applied Mathematics III, Universitat Politècnica de Catalunya, Colom 1, 08222 Terrassa Spain.,
E-mail: [email protected]
Search for more papers by this authorYolanda Vidal
CoDAlab (Control, Dynamics and Applications), Departament de Matemàtica Aplicada III, Universitat Politècnica de Catalunya, Barcelona, Spain
Search for more papers by this authorLeonardo Acho
CoDAlab (Control, Dynamics and Applications), Departament de Matemàtica Aplicada III, Universitat Politècnica de Catalunya, Barcelona, Spain
Search for more papers by this authorAlessandro N. Vargas
Universidade Tecnólogica Federal do Parana, UTFPR, Electrotechnical Department, Paraná, Brazil
Search for more papers by this authorSummary
This paper presents an improved model for an automotive electronic throttle inspired on the behaviour observed in real-time experiments. Due to a number of issues, particularly the return-spring, the performance of the throttle valve depends on whether it is opening or closing. This asymmetric behaviour was taken into account to design a mathematical model of the throttle body and to derive a nonlinear asymmetric Proportional Integral controller. The experimental demonstration suggests that considering an asymmetric term dramatically improves the performance of the controller. Copyright © 2015 John Wiley & Sons, Ltd.
References
- 1Song J, Byun K. Throttle actuator control system for vehicle traction control. Mechatron 1999; 9(5): 477–495.
- 2Rossi C, Tilli A, Tonielli A. Robust control of a throttle body for drive by wire operation of automotive engines. IEEE Trans Control Syst Technol 2000; 8: 993–1002.
- 3Pavkovic D, Deura J, Janszb M, Peric N. Adaptive control of automotive electronic throttle. Control Eng Pract 2006; 14: 121–136.
- 4Favela Contreras A, Perez Quiroz I, Canudas de Wit C. Further Results on modelling and identification of an electronic throttle body. 10th Mediterranean Conference on Control and Automation - MED2002, Lisbon, Portugal, 2002.
- 5Canudas de Witty C, Kolmanovsky I, Sun J. Adaptive pulse control of electronic throttle. American Control Conference, Arlington, VA, 2001.
- 6Canudas de Wit C, Olsson H, Amstrom KJ, Lischinsky P. A new model for control of systems with friction. IEEE Trans Autom Control 1995; 40(3): 419–425.
- 7Grepl R. Adaptive composite control of electronic throttle using local learning method. IEEE International Symposium on Industrial Electronics (ISIE), Bari, Italy, 2010; 58–61.
- 8Yuan X, Wang Y, Wu L, Zhang X, Sun W. Neural network based self-learning control strategy for electronic throttle valve. IEEE Trans Veh Technol 2010; 59(8): 3757–3765.
- 9Yuan X, Wang Y. A novel electronic throttle valve controller based on approximate model method. IEEE Trans Ind Electron 2009; 56(3): 883–890.
- 10Yuan X, Wang Y, Wei S, Lianghong W. RBF networks based adaptive inverse model control system for electronic throttle. IEEE Trans Control Syst Technol 2010; 18(3): 750–756.
- 11Loh RNK, Thanom W, Pyko JS, Lee A. Electronic throttle control system: modeling, identification and model-based control designs. Eng 2013; 5: 587–600.
10.4236/eng.2013.57071 Google Scholar
- 12Kitahara A, Sato A, Hoshino M, Kurihara N, Shin S. QG based electronic throttle control with a two degree of freedom structure. 35th Conference on Decision and Control, Kobe, Japan, 1996.
- 13Yokoyama M, Shimizu K, Okamoto N. Decision and Control. Proceedings of the 37th IEEE Conference on, Vol. 2, Hyatt Regency Westshore Tampa, Florida, 1998; 1541–1545.
- 14AL-Samarraie A, Abbas M. Design of electronic throttle valve position control system using nonlinear PID controller. Int J Comput Appl 2012; 59(15): 27–34.
- 15Nakano K, Sawut U, Higuchi K, Okijama Y. Modelling and observer-based sliding mode control of electronic throttle systems. ECTI trans on Elec Eng Electron, and Commun 2006; 4(1): 22–28.
- 16Vidal Y, Acho L, Pozo F. Robust control of an electronic throttle system via switched chattering control: benchmark experiments. IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling, Paris, France, 2009.
- 17Pozo F, Acho L, Vidal Y. Nonlinear Adaptive Tracking Control of an Electronic Throttle System: Benchmark Experiments, Paris, France, 2009.
- 18Stotsky A, Egardt B, Eriksson S. Variable structure control of engine idle speed with estimation of un-measurable disturbances. J of Dyn Syst, Meas and Control 2000; 122: 599–603.
- 19Garrido R, Miranda R. DC servomechanism parameter identification: a closed loop input error approach. ISA Trans 2012; 51: 42–29.
- 20Fuh CC, Tsai HH. Adaptive parameter identification of servo control systems with noise and high-frequency uncertainties. Mech Syst Sig Process 2007; 21: 1437–1451.
- 21Vasak M, Baoti M, Morari M, Petrovi I, Peri N. Constrained optimal control of an electronic throttle. Int J Control 2006; 79(5): 465–478.
- 22Slotine JJE, Li W. Applied Nonlinear Control. Prentice Hall, Englewood Cliffs, NJ, 1991.
- 23Volyanskyy KY, Haddad WM, Calise AJ. A new neuro-adaptive control architecture for nonlinear uncertain dynamical systems: beyond-and-modifications. IEEE Trans on Neural Netw 2010; 20(11): 1707–1723.
- 24Yucelen T, Haddad W. Low-frequency learning and fast adapt-ation in model reference adaptive control. IEEE Trans Autom Control 2013; 58(4): 1080–1085.
- 25Bennett S. A History of Control Engineering. 1930-1955, IET. 1993. p.p. 48. ISBN 978-0-86341-299-8.
- 26Toscano R. A simple robust PI/PID controller design via numerical optimization approach. J of Process Control 2005; 15: 81–88.
- 27Leena G, Datta KB, Ray G. A class of stabilizing PID controllers for position control of single-link manipulator. Int Contr Autom 2011; 4(3): 127–142.
- 28Wang YG, Shao HH. Optimal tuning for PI controller. Autom 2000; 36: 147–152.
- 29Yuan X, Wang Y. Neural networks based self-learning PID control of electronic throttle. Nonlinear Dyn 2009; 55(4): 385–393.
- 30Filippov AF. Differential Equations with Discontinuous Right-hand Sides, Kluwer Academic, Boston, 1988.
10.1007/978-94-015-7793-9 Google Scholar
- 31Skafidas E, Evans RJ, Savkin AV, Petersen IR. Stability results for switched controller systems. Autom 1999; 35: 553–564.