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Parameter estimation for non-linear systems: an application to vehicle dynamics

By C Pedchote

Abstract

This work presents an investigation into the parameter estimation of suspension components and the vertical motions of wheeled vehicles from experimental data. The estimation problems considered were for suspension dampers, a single wheel station and a full vehicle. Using conventional methods (gradient-based (GB), Downhill Simplex (DS)) and stochastic methods (Genetic Algorithm (GA) and Differential Evolution (DE)), three major problems were encountered. These were concerned with the ability and consistency of finding the global optimum solution, time consumption in the estimation process, and the difficulties in setting the algorithm's control parameters. To overcome these problems, a new technique named the discrete variable Hybrid Differential Evolution (dvHDE) method is presented. The new dvHDE method employs an integer-encoding technique and treats all parameters involved in the same unified way as discrete variables, and embeds two mechanisms that can be used to deal with convergence difficulties and reduce the time consumed in the optimisation process. The dvHDE algorithm has been validated against the conventional GB, DS and DE techniques and was shown to be more efficient and effective in all but the simplest cases. Its robustness was demonstrated by its application to a number of vehicle related problems of increasing complexity. These include case studies involving parameter estimation using experimental data from tests on automotive dampers, a single wheel station and a full vehicle. The investigation has shown that the proposed dvHDE method, when compared to the other methods, was the best for finding the global optimum solutions in a short time. It is recommended for nonlinear vehicle suspension models and other similar systems

Topics: Motor vehicles - Dynamics, Motor vehicles - Dynamics - Computer simulation, Automobiles - Dynamics, Nonlinear systems, Mathematical models, Systems and control, Linear control systems, Automatic control
Publisher: Engineering Systems Department
Year: 2009
OAI identifier: oai:dspace.lib.cranfield.ac.uk:1826/3896
Provided by: Cranfield CERES

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Citations

  1. (1998). A hybrid method of differential evolution with application to optimal control problems of a bio-process system. The doi
  2. (1992). A low cost transfer function identification technique for automotive suspensions, doi
  3. A mixed integer-discretecontinuous programming method and its application to engineering design optimisation. doi
  4. (1997). A nonlinear Dynamic Model of a Monotube Shock Absorber, doi
  5. A nonlinear Parametric Model of an Automotive Shock Absorbers,
  6. (1900). A parallel optimization scheme for parameter estimation in motor vehicle dynamics, doi
  7. (1999). A randomized integral error criterion for parametric identification of dynamic models of mechanical systems, doi
  8. (1998). A regularization approach to robust variable structure observer design applied to vehicle parameter and state estimation, doi
  9. (1991). A sequential linearisation approach for solving mixed-discrete nonlinear design optimisation problems. doi
  10. (1965). A simplex method for function minimisation, doi
  11. (1977). A Study of the Characteristics of Automotive Hydraulic Dampers at High Stroking Frequencies, doi
  12. (1993). Achievability and value of passive suspension design for minimum pitch response.
  13. (1986). Adaptive Filter Theory, Prentice-Hall,
  14. (1984). Adaptive Filtering, Prediction and Control, Printice-Hall,
  15. (1992). An improved nonlinear model for an automotive shock absorber,
  16. (1986). An Introduction to Identification, doi
  17. (1994). An Optimal Self-Tuning Controller for an Active Suspension', The active Control of Vibration, doi
  18. (1999). Analytical Dynamics, The McGraw-Hill Companies,
  19. (1998). Applied Dynamics: with applications to Multibody and Mechatronic Systems, doi
  20. (1974). Applied Optimal Estimation,
  21. (1985). Bayesian Estimation of Transit Rail Vehicle Parameters, doi
  22. Characterization of automotive shock absorbers using random excitation, doi
  23. Characterizing an automotive shock absorber and the dependency on the temperature,
  24. (1991). Computational implementation and tests of a sequential linearisation algorithm for mixed-discrete nonlinear design optimisation. doi
  25. (1996). Control system parameter identification using the population based incremental learning, doi
  26. Crolla Road Vehicle Suspension System Design -a review, doi
  27. (1979). Dahlberg Optimization Criteria for Vehicles Travelling on a randomly Profile Road -a survey, Vehicle Systems Dynamics, doi
  28. Damper models for heavy vehicle ride dynamics, doi
  29. (1990). Data processing and experiment design for the restoring force surface method, Part 1: Integration and differentiation of measured data, doi
  30. (1983). Determination of mass, damping and stiffness matrices using structural and parametric identification of linear vehicle frame models, American Control Conference, doi
  31. Differential evolution based identification of automotive hydraulic engine mount model parameters. doi
  32. (1997). Differential Evolution-A simple evolution strategy for fast optimization.
  33. (1977). Dynamic System Identification: Experiment Design and Data Analysis, doi
  34. (1990). Dynamics of Nonlinear Automotive Shock Absorbers, doi
  35. (1999). Effect of the Suspension structure on equivalent suspension parameters, doi
  36. (1996). Engineering Optimization: Theory and Practice, Wiley Inter-Science,
  37. (1997). EP 0 808 733 A2, European Patent Application,
  38. (1997). Estimation of suspension parameters, doi
  39. (1999). Estimation of the Non-linear Suspension Tyre Cornering Forces from Experimental Road Test Data, Vehicle System Dynamics, doi
  40. (1997). Estimation of vehicle dynamic and static parameters from megnetometer data,
  41. (1987). Experimental design and identifiability for non-linear systems, doi
  42. Fast multilevel implementation of recursive spectral bisection for partitioning unstructured problems, Concurrency: Practice and experience, doi
  43. (1992). Fundamentals of Vehicle Dynamics, doi
  44. (1994). Grey Box identification of vehicle 280 dynamics, IFAC System Identification,
  45. Identification of hysteretic systems using the Differential Evolution algorithm. doi
  46. (1991). Identification of linear systems: A practical guideline to accurate modelling.
  47. (1997). Identification of Parametric Models from Experimental Data,
  48. (1990). Identification of physical parameters of ground vehicle using block-pulse function method, doi
  49. (1991). Identification of System Physical Parameters for Vehicle Systems with Nonlinear Components, Vehicle System Dynamics, doi
  50. (1987). Identification of the hysteresis parameters of a nonlinear vehicle suspension under random excitation, doi
  51. (1986). Instrumental variable identification in vehicle dynamics, doi
  52. (1988). Lectures on Adaptive Parameter Estimation, Prentice-Hall,
  53. (1977). Mathematical Modeling and Digital Simulation for Engineering and Scientists, doi
  54. (1980). Maximum Likelihood and Prediction Error Methods, doi
  55. Mean Square Error of prediction as a criterion for selecting variables, doi
  56. Mechanical design optimisation by mixed-variable evolutionary programming.
  57. (1999). Mechanical Engineering Design Optimization by Differential Evolution. In: doi
  58. (1999). Mixed integer-discrete-continuous optimisation by Differential Evolution, Part 1: the optimisation method.
  59. (1993). Mixed-discrete nonlinear optimisation with simulated annealing. doi
  60. (1993). Model updating in structural dynamics: A survey, doi
  61. (1996). Model-based identification of a vehicle suspension suing parameter estimation and neural networks, IFAC 13`h Triennial World Congress,
  62. (1961). New results in Linear Filtering and Prediction, doi
  63. (1997). Non-parametric Methods of System Identification, doi
  64. (1990). Nonlinear integer and discrete programming in mechanical design optimisation. doi
  65. (1965). Numerical Identification of Linear Dynamic 278 Systems for Normal Operating Records, doi
  66. (1995). Observer-based identification of nonlinear system parameters, Journal of Dynamic Systems, Measurement, and Control, doi
  67. (1971). On mixed-discrete nonlinear optimisation problems: A comparative study.
  68. (1982). On the coherence among the multitude of system identification methods, IFAC Identification and system parameter estimation,
  69. (1996). On the nonlinear characteristics of automotive shock absorbers, Proceedings, of IMechE,
  70. (1996). ON the practical implementation and convergence of the extended Kalman filter and other approximate non-linear estimation methods,
  71. Optimal design of machine elements using genetic algorithms.
  72. (1982). Optimal engineering design: principles and applications. Mechanical engineering series/ 14.
  73. (1986). Optimal Estimation with Introduction to Stochastic Control Theory, doi
  74. (1994). Optimization Tool Box, for use with Matlab. The MathWorks Inc.,
  75. (2002). Parallel parameter estimation in full motor vehicle dynamics,
  76. (1995). Parameter Estimation in Analytical Models of Automotive Vehicles and Fault Diagnosis, doi
  77. Parameter estimation of a bio-reaction model by hybrid differential evolution. doi
  78. (2000). Parameter Estimation of vehicle suspension, doi
  79. Parameters non-linear identification for vehicle's model, doi
  80. Parametric and Non-parametric identification of automotive shock absorber, doi
  81. (1990). Partitioning spares matrices with eigenvectors of graphs, doi
  82. Performance of a telescopic dual-tube automotive damper and the implications for vehicle ride prediction, doi
  83. (1980). Practical aspects of process identification, doi
  84. (1988). Principles of Dynamics,
  85. (1992). Realization of adaptive shock absorbers by estimating physical process coefficients of a vehicle suspension system.,
  86. (1999). Reduced-order modeling and parameter estimation for a quarter-car suspension system, doi
  87. (1974). System Identification - Parameter and State Estimation, doi
  88. (1988). System Identification, doi
  89. (1999). System Identification: Theory for the user. doi
  90. (1982). The choice and use of different model sets for system identification, IFAC Identification and system parameter estimation,
  91. Theoretical and experimental investigation into an adjustable automotive damper, doi
  92. (1987). Theory and Design Adaptive Filters, doi
  93. (1987). Theory and Practice of Recursive Identification, doi

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