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- Ferizbegovic, Mina, et al.
(författare)
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Bayes control of hammerstein systems
- 2021
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Ingår i: 19th IFAC Symposium on System Identification, SYSID 2021. - : Elsevier BV. ; , s. 755-760, s. 755-760
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Konferensbidrag (refereegranskat)abstract
- In this paper, we consider data driven control of Hammerstein systems. For such systems a common control structure is a transfer function followed by a static output nonlinearity that tries to cancel the input nonlinearity of the system, which is modeled as a polynomial or piece-wise linear function. The linear part of the controller is used to achieve desired disturbance rejection and tracking properties. To design a linear part of the controller, we propose a weighted average risk criterion with the risk being the average of the squared L2 tracking error. Here the average is with respect to the observations used in the controller and the weighting is with respect to how important it is to have good control for different impulse responses. This criterion corresponds to the average risk criterion leading to the Bayes estimator and we therefore call this approach Bayes control. By parametrizing the weighting function and estimating the corresponding hyperparameters we tune the weighting function to the information regarding the true impulse response contained in the data set available to the user for the control design. The numerical results show that the proposed methods result in stable controllers with performance comparable to the optimal controller, designed using the true input nonlinearity and true plant.
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| 2. |
- Ferizbegovic, Mina, et al.
(författare)
-
Willems' fundamental lemma based on second-order moments
- 2021
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Ingår i: 2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665436595 ; , s. 396-401
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Konferensbidrag (refereegranskat)abstract
- In this paper, we propose variations of Willems' fundamental lemma that utilize second-order moments such as correlation functions in the time domain and power spectra in the frequency domain. We believe that using a formulation with estimated correlation coefficients is suitable for data compression, and possibly can reduce noise. Also, the formulations in the frequency domain can enable modeling of a system in a frequency region of interest.
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