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2021 | OriginalPaper | Buchkapitel

5. Adaptive Dynamic Inversion for Satellite Formation Flying

verfasst von : S. Mathavaraj, Radhakant Padhi

Erschienen in: Satellite Formation Flying

Verlag: Springer Singapore

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Abstract

The benefit of satellite formation flying can truly be realized with greater mission flexibility such as higher inter-satellite separation, formation in elliptic orbits, etc. However, under the above-enhanced conditions, linear system dynamics based control design approaches fail to achieve the desired objectives. Even though the LQR philosophy inspired the SDRE approach discussed in Chapter 3 offers a limited solution, it suffers from the drawback that the success of the approach largely depends on the typical state-dependent coefficient form one adopts (which remains as ‘art’). Moreover, if the eccentricity deviates significantly from circular orbit or separation distance requirement becomes large significantly, even SDRE can fail. The Adaptive LQR offers a fairly good solution to this issue, but introduces neural network learning concepts even for the system dynamics that is fairly known which can be handled directly. This brings in additional transients at the beginning of learning as well, which should preferably be avoided. In view of these observations, this chapter presents an alternate approach that need not be optimal, but can be successful under such realistic conditions as well.

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Literatur
1.
Zurück zum Zitat Enns, D., D. Bugajski, R. Hendrick, and G. Stein. 1994. Dynamic inversion: An evolving methodology for flight control design. International Journal of control 59 (1): 71–91.CrossRef Enns, D., D. Bugajski, R. Hendrick, and G. Stein. 1994. Dynamic inversion: An evolving methodology for flight control design. International Journal of control 59 (1): 71–91.CrossRef
2.
Zurück zum Zitat Slotine, J.J., and W. Li. 1991. Applied nonlinear control. Prentice Hall. Slotine, J.J., and W. Li. 1991. Applied nonlinear control. Prentice Hall.
3.
Zurück zum Zitat Kim, B.S., and A.J. Calise. 1997. Nonlinear flight control using neural networks. AIAA Journal of Guidance, Control and Dynamics 20 (1): 26–33.CrossRef Kim, B.S., and A.J. Calise. 1997. Nonlinear flight control using neural networks. AIAA Journal of Guidance, Control and Dynamics 20 (1): 26–33.CrossRef
4.
Zurück zum Zitat Padhi, R., S.N. Balakrishnan, and N. Unnikrishnan. 2007b. Model-following neuro-adaptive control design for non-square, non-affine nonlinear systems. IET Control Theory Application 1 (6): 1650–1661.CrossRef Padhi, R., S.N. Balakrishnan, and N. Unnikrishnan. 2007b. Model-following neuro-adaptive control design for non-square, non-affine nonlinear systems. IET Control Theory Application 1 (6): 1650–1661.CrossRef
5.
Zurück zum Zitat Wang, Q., and R.F. Stengel. 2004. Robust nonlinear flight control of a high-performance aircraft. IEEE Transactions on Control Systems Technology 13 (1): 15–26.CrossRef Wang, Q., and R.F. Stengel. 2004. Robust nonlinear flight control of a high-performance aircraft. IEEE Transactions on Control Systems Technology 13 (1): 15–26.CrossRef
6.
Zurück zum Zitat Marquez, H.J. 2003. Nonlinear control systems: Analysis and design, vol. 161, John Wiley Hoboken. Marquez, H.J. 2003. Nonlinear control systems: Analysis and design, vol. 161, John Wiley Hoboken.
7.
Zurück zum Zitat Kahlil, H. 2002. Nonlinear systems. New Jersey: Prentice Hall. Kahlil, H. 2002. Nonlinear systems. New Jersey: Prentice Hall.
8.
Zurück zum Zitat Li, Y., N. Sundararajan, and P. Saratchandran. 2001. Neuro-controller design for nonlinear fighter aircraft maneuver using fully tuned RBF networks. Automatica 37 (8): 1293–1301.MathSciNetCrossRef Li, Y., N. Sundararajan, and P. Saratchandran. 2001. Neuro-controller design for nonlinear fighter aircraft maneuver using fully tuned RBF networks. Automatica 37 (8): 1293–1301.MathSciNetCrossRef
9.
Zurück zum Zitat Padhi, R., and M. Kothari. 2007. An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia. Computer Methods and Programs in Biomedicine 87 (3): 208–224.CrossRef Padhi, R., and M. Kothari. 2007. An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia. Computer Methods and Programs in Biomedicine 87 (3): 208–224.CrossRef
10.
Zurück zum Zitat Mathavaraj, S., and R. Padhi. 2019. Optimally allocated nonlinear robust control of a reusable launch vehicle during re-entry. Unmanned Systems. Mathavaraj, S., and R. Padhi. 2019. Optimally allocated nonlinear robust control of a reusable launch vehicle during re-entry. Unmanned Systems.
11.
Zurück zum Zitat Rajasekaran, J., A. Chunodkar, and R. Padhi. 2009. Structured model-following neuro-adaptive design for attitude maneuver of rigid bodies. Control Engineering Practice 17 (6): 676–689.CrossRef Rajasekaran, J., A. Chunodkar, and R. Padhi. 2009. Structured model-following neuro-adaptive design for attitude maneuver of rigid bodies. Control Engineering Practice 17 (6): 676–689.CrossRef
12.
Zurück zum Zitat Cloutier, J. 1997. State-dependent Riccati equation techniques: An overview. In American Control Conference, vol. 2, 932–936. Air Force Armament Directorate, Eglin AFB, FL. Cloutier, J. 1997. State-dependent Riccati equation techniques: An overview. In American Control Conference, vol. 2, 932–936. Air Force Armament Directorate, Eglin AFB, FL.
13.
Zurück zum Zitat Nguyen, D.H., and B. Widrow. 1990. Neural networks for self-learning control systems. IEEE Control Systems Magazine 10 (3): 18–23.CrossRef Nguyen, D.H., and B. Widrow. 1990. Neural networks for self-learning control systems. IEEE Control Systems Magazine 10 (3): 18–23.CrossRef
14.
Zurück zum Zitat Barto, A. 1984. Neuron-like adaptive elements that can solve difficult learning control-problems. Behavioural Processes 9 (1). Barto, A. 1984. Neuron-like adaptive elements that can solve difficult learning control-problems. Behavioural Processes 9 (1).
15.
Zurück zum Zitat Sanner, R.M., and J.-J.E. Slotine. 1991. Gaussian networks for direct adaptive control. In IEEE American Control Conference, 2153–2159. Sanner, R.M., and J.-J.E. Slotine. 1991. Gaussian networks for direct adaptive control. In IEEE American Control Conference, 2153–2159.
Metadaten
Titel
Adaptive Dynamic Inversion for Satellite Formation Flying
verfasst von
S. Mathavaraj
Radhakant Padhi
Copyright-Jahr
2021
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-9631-5_5

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