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Vibration Analysis and Control New Trends and Developments Part 7 docx

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One then obtains thatcan be shown that the proposed observer design methodology is quite robust with respect toparameter uncertainty and unmodeled dynamics, by considering the parameter

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derivatives of the flat output required for implementation of the controller (20):

approximated by a family of Taylor polynomials of fourth degree Therefore, the characteristicpolynomial for the dynamics of output observation error (24) is given by

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One then obtains that

can be shown that the proposed observer design methodology is quite robust with respect toparameter uncertainty and unmodeled dynamics, by considering the parameter variations

presented through some experimental results that the polynomial disturbance signal-basedGPI control scheme, implemented as a classical compensation network, is robust enough withrespect to parameter uncertainty and unmodeled dynamics in the context of an off-line andpre-specified reference trajectory tracking tasks

It is important to emphasize that, the proposed results are now possible thanks to the existence

of commercial embedded system for automatic control tasks based on high speed FPGA/DSPboards with high computational performance operating at high sampling rates The proposedobserver could be implemented via embedded software applications without many problems

5 Simulation results

Some numerical simulations were performed on a nonlinear quarter-vehicle suspensionsystem characterized by the following set of realistic parameters (Tahboub, 2005) to verifythe effectiveness of the proposed disturbance observer-control design methodology (see Table1):

Table 1 Parameters of the vehicle suspension system

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Fig 2 shows some schematic diagram for the implementation of the proposed active vibrationcontrollers based on on-line disturbance estimation using a flatness-based controller and GPIobservers.

Fig 2 Schematic diagram of the instrumentation for active vehicle suspension controlimplementation

The following trajectory was utilized to simulate the unknown exogenous disturbanceexcitations due to irregular road surfaces (Chen & Huang, 2005):

Figs 3-9 describe the robust performance of the controller (7) using the observer (14) It can

be seen the high vibration attenuation level of the active vehicle suspension system comparedwith the passive counterpart

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Moreover, one can observe a robust and fast on-line estimation of the disturbanceξ(t)as well

as the corresponding time derivatives of the flat output up to third order Similar results onthe implementation of the controller (20) with disturbance observer (23) for estimation of the

can be locally approximated by a family of Taylor polynomials of fourth degree

The characteristic polynomials for the ninth order observation error dynamics were all set to

be of the following form:

p o(s) = (s+p o)s2+2ζ o ω o s+ω24

The characteristic polynomials associated with the closed-loop dynamics were all set to be of

t [s]

Active Passive Road profile

Fig 3 Sprung mass displacement response using controller (7) and observer (14)

t [s]

2 ]

Active Passive

Fig 4 Sprung mass acceleration response using controller (7) and observer (14)

In general, the proposed active vehicle suspension using a flatness-based controller and GPIobservers for the estimation of unknown perturbations yields good attenuation properties and

an overall robust performance

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0 5 10 15

−0.15

−0.1

−0.05 0 0.05 0.1 0.15

t [s]

Active Passive

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Estimate Actual value

Estimate Actual value

Estimate Actual value

Fig 8 Estimation of time derivatives of the flat output using the observer (14)

t [s]

Active Passive Road profile

Fig 10 Sprung mass displacement response using controller (20) and observer (23).)

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t [s]

2 ]

Active Passive

Fig 11 Sprung mass acceleration response using controller (20) and observer (23)

−0.15

−0.1

−0.05 0 0.05 0.1 0.15

t [s]

Active Passive

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Estimate Actual value

Estimate Actual value

Estimate Actual value

Fig 15 Estimation of time derivatives of the flat output using the observer (23)

t [s]

Fig 16 Control force using the observer (23)

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6 Conclusions

In this chapter a robust active vibration control scheme, based on real-time estimationand rejection of perturbation signals, of nonlinear vehicle suspension systems is described.The proposed approach exploits the structural property of differential flatness exhibited

by the suspension system fot the synthesis of a flatness based controller and a robustobserver Therefore, a perturbed input-output differential equation describing the dynamics

of the flat output is obtained for design purposes of the control scheme The exogenousdisturbances due to irregular road surfaces, nonlinear effects, parameter variations andunmodeled dynamics are lumped into an unknown bounded time-varying perturbationinput signal affecting the differentially flat linear simplified dynamic mathematical model

of the suspension system A family of Taylor polynomials of (r-1)th degree is used tolocally approximate this perturbation signal Hence the perturbation signal is described by

a rth-order mathematical model Then, the perturbed suspension system model is expressed

as a (r+4)th-order extended mathematical model

The design of high-gain Luenberger observers, based on this kind of extended models, isproposed to estimate the perturbation signal and some time derivatives of the flat outputrequired for implementation of differential flatness-based disturbance feedforward andfeedback controllers for attenuation of vibrations in electromagnetic and hydraulic activevehicle suspension systems

Two high-gain disturbance observer-based controllers have been proposed to attenuate thevibrations induced by unknown exogenous disturbance excitations due to irregular roadsurfaces, which could be employed for nonlinear quarter-vehicle active suspension models byusing hydraulic or electromagnetic actuators Computer simulations were included to showthe effectiveness of the proposed controllers, as well as of the disturbance observers based onTaylor polynomials of fourth degree

The results show a high vibration attenuation level of the active vehicle suspension systemcompared with the passive counterpart and, in addition, a robust and fast real-time estimation

of the disturbance and time derivatives of the flat output

7 References

Ahmadian, M Active control of vehicle suspensions In: Encyclopedia of Vibration, Edited by

Braun, S.G., Ewins, D.J & Rao, S.S (2001), Vols 1-3, Academic Press, San Diego, CA.Basterretxea, K., Del Campo, I & Echanobe, J (2010) A semi-active suspension embedded

controller in a FPGA, 2010 IEEE International Symposium on Industrial Embedded

Systems, pp 69-78, Trento, July 7-9.

Beltran-Carbajal, F., Silva-Navarro, G., Blanco-Ortega, A & Chavez-Conde, E (2010a)

Active Vibration Control for a Nonlinear Mechanical System using On-line Algebraic

Identification, In: Vibration Control, M Lallart, (Ed.), 201-214, Sciyo, Rijeka, Croatia.

Beltran-Carbajal, F., Silva-Navarro, G., Sira-Ramirez, H & Blanco-Ortega, A (2010b)

Application of on-line algebraic identification in active vibration control, Computación

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Cao, J., Liu, H., Li, P & Brown, D (2008) State of the Art in Vehicle Active Suspension

Adaptive Control Systems Based on Intelligent Methodologies, IEEE Transaction on

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Choi, S.B., Lee, H.K & Chang, E.G (2001) Field test results of a semi-active ER suspension

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Chavez-Conde, E., Beltran-Carbajal, F., Garcia-Rodriguez, C & Blanco-Ortega, A (2009a)

Sliding Mode Based Differential Flatness Control and State Estimation of Vehicle

Active Suspensions System, IEEE International Conference on Electrical Engineering,

Computing Science and Automatic Control, pp 544-549, Toluca, Mexico, November

10-13

Chavez-Conde, E., Beltran-Carbajal, F., Blanco-Ortega, A & Mendez-Azua, H (2009b)

Sliding Mode and Generalized PI Control of Vehicle Active Suspensions, 18th

IEEE International Conference on Control Applications, pp 1726-1731, Saint Petersburg,

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Chen, P & Huang, A (2005) Adaptive sliding control of non-autonomous active suspension

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1119-1135

Proportionnels-Integraux Généralisés, ESAIM Control, Optimisation and Calculus

of Variations, Vol 7, pp 23-41.

Fliess, M., Marquez, R & Delaleau, E (2001) State feedbacks without asymptotic observers

and generalized PID regulators, Nonlinear Control in the Year 2000, Lecture Notes in

Control and Information Sciences, Vol 258, pp 367-384, Springer, London.

Fliess, M., Lévine, J., Martin, Ph & Rouchon, P (1993) Flatness and defect of nonlinear

systems: introductory theory and examples, International Journal of Control, Vol 61,

No 6, pp 1327-1361

Gysen, B.L.J., Paulides, J.J.H., Janssen, J.L.G & Lomonova, E A (2008) Active

Electromagnetic Suspension System for Improved Vehicle Dynamics, IEEE Vehicle

Power and Propulsion Conference (VPPC), Harbin, China, September 3-5.

Isermann, R & Munchhpf, M (2011) Identification of Dynamic Systems, Springer-Verlag, Berlin.

Martins, I., Esteves, J., Marques, D.G & Da Silva, F P (2006) Permanent-Magnets Linear

Actuators Applicability in Automobile Active Suspensions, IEEE Trans on Vehicular

Technology, Vol 55, No 1, pp 86-94.

Sira-Ramirez, H., Beltran-Carbajal, F & Blanco-Ortega, A (2008a) A Generalized Proportional

Integral Output Feedback Controller for the Robust Perturbation Rejection in a

Mechanical System, e-STA Sciences et Technologies de l’Automatique, Vol 5, No 4, pp.

24-32

Sira-Ramirez, H., Feliu-Batlle, V., Beltran-Carbajal, F & Blanco-Ortega, A (2008b)

Sigma-Delta modulation sliding mode observers for linear systems subject to locally

unstable inputs, 16th Mediterranean Conference on Control and Automation, pp 344-349,

Ajaccio, France, June 25-27

Sira-Ramirez, H., Barrios-Cruz, E & Marquez-Contreras, R.J (2009) Fast adaptive trajectory

tracking control for a completely uncertain DC motor via output feedback,

Computación y Sistemas, Vol 12, No 4, pp 397-408.

Sira-Ramirez, H., Silva-Navarro, G & Beltran-Carbajal, F (2007) On the GPI balancing control

of an uncertain Jeffcot rotor model, 2007 4th International Conference on Electrical and

Electronics Engineering (ICEEE), pp 306-309, Mexico City, Mexico, September 5-7.

Sira-Ramirez, H & Agrawal, S.K (2004) Differentially Flat Systems, Marcel Dekker, New York.

Trang 12

Shoukry, Y., El-Kharashi, M W & Hammad, S (2010) MPC-On-Chip: An Embedded GPC

Coprocessor for Automotive Active Suspension Systems, IEEE Embedded Systems

Letters, Vol 2, No 2, pp 31-34.

Tahboub, K A (2005) Active Nonlinear Vehicle-Suspension Variable-Gain Control, 13th

Mediterranean Conference on Control and Automation, pp 569-574, Limassol, Cyprus,

June 27-29

London

Ventura, P.J.C., Ferreira, C.D.H., Neves, C F C S., Morais, R.M.P., Valente, A.L.G & Reis,

M.J.C.S (2008) An embedded system to assess the automotive shock absorber

condition under vehicle operation, IEEE Sensor 2008 Conference, pp 1210-1213, Lecce,

October 26-29

Yao, G.Z., Yap, F.F., Chen, G., Li, W.H & Yeo, S.H (2002) MR damper and its application for

semi-active control of vehicle suspension system, Mechatronics, Vol 12, pp 963-973.

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R R

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( ) ( )( )

=

( )( )

( ) = ( ( ) ( )) + ( )( ( ) ( ))

( ( ) ( ))

( )( ( ) ( ))( )

Trang 19

Trang 25

Pon (Nominal structure):

Pon (Optimized structure):

SA (Nominal structure):

SA (Optimized structure):

Energy-based SA (Optimized structure):

( )( )

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