Probabilistic robust controller design

Djavdan, P.; Tulleken, H.J.A.F.; Voetter, M.; Verbruggen, H.B.; Olsder, Geert Jan

doi:10.1109/cdc.1989.70551

Cited by 11 publications

(4 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Extensive evidence for the effectiveness of such statistical approaches can be found in the control theory community where a great effort has been devoted to the analysis and design of robust controllers [21]- [23].…”

Section: Randomized Algorithms and The Reference Diagnosis Systemmentioning

confidence: 99%

SBT soft fault diagnosis in analog electronic circuits: a sensitivity-based approach by randomized algorithms

Alippi

Catelani

Fort

et al. 2002

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

Abstract-This paper addresses the fault diagnosis issue based on a simulation before test philosophy in analog electronic circuits. Diagnosis, obtained by comparing signatures measured at the test nodes with those contained in a fault dictionary, allows for sub-systems testing and fault isolation within the circuit. A novel method for constructing the fault dictionary under the single faulty component/unit hypothesis is proposed. The method, based on a harmonic analysis, allows for selecting the most suitable test input stimuli and nodes by means of a global sensitivity approach efficiently carried out by randomized algorithms. Applicability of the method to a wide class of circuits and its integration in diagnosis tools are granted since randomized algorithms assure that the selection problem can be effectively carried out with a poly-time algorithm independently from the fault space, structure, and complexity of the circuit.

show abstract

Section: Randomized Algorithms and The Reference Diagnosis Systemmentioning

confidence: 99%

SBT soft fault diagnosis in analog electronic circuits: a sensitivity-based approach by randomized algorithms

Alippi

Catelani

Fort

et al. 2002

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

show abstract

“…Therefore, thanks to randomization, the uncertainty set is treated as it is and no conservatism is introduced which tends to significant improvement in the performance of the closed loop system. Using probabilistic concept in robust control was first introduced by Stengel in 1980 [10] and later on it was used in [11] which deals with estimating the probability of instability using Monte-Carlo type of simulation. Randomized algorithm was further developed in [12], [13] where some explicit sample bounds have been derived based on which we can determine the probability of violation (or satisfaction) of a given cost function.…”

Section: Introductionmentioning

confidence: 99%

Design of track following controller of dual actuated HDD servo for 10 Tb/in<sup>2</sup> magnetic recording

Keikha

Chamanbaz

Mamun

et al. 2011

The 2nd International Conference on Control, Instrumentation and Automation

View full text Add to dashboard Cite

One of the obstacles to achieving high recording density in hard disk drives (HDDs) is servo performance limitation.As HDD is a mass produced commodity, the challenge is not only achieving high performance for nominal models but with all the uncertainties and variations in HDD models for thousands of HDDs in a batch of production line. This paper presents the implementation results of a novel technique based on the H∞ probabilistic robust approach for the track-following controller of HDD servo systems. The objective is to design and implement an H∞ dynamic output feedback controller that achieves robust stability in the presence of various parametric uncertainties. We consider uncertainty as a random variable with uniform probability distribution. Then a randomized algorithm based on gradient iteration is preformed to compute design parameters. The proposed controller is implemented in real-time on a commercially available drive and the results are compared with the conventional H∞ approach. The results reveal that with a very small risk of violation of the cost function, the proposed method can achieve much better performance compared to the conventional robust methods.

show abstract

“…Finally, is should also be noted that the literature is abound with other approaches to uncertain parameters with even more significant differences in starting assumptions; e.g., see [22], [25] and [38].…”

Section: Introductionmentioning

confidence: 99%

Distributionally Robust Monte Carlo Simulation: A Tutorial Survey

Lagoa

Barmish

2002

IFAC Proceedings Volumes

View full text Add to dashboard Cite

Whereas the use of traditional Monte Carlo simulation requires probability distributions for the uncertain parameters entering the system, distributionally robust Monte Carlo simulation does not. The description of this new approach to Monte Carlo simulation is the focal point of this tutorial survey. According to the new theory, instead of carrying out simulations using some rather arbitrary probability distribution such as Gaussian for the uncertain parameters, we provide a rather different prescription based on distributional robustness considerations. The new approach which we describe, does not require a probability distribution f for the uncertain parameters. Instead, motivated by manufacturing considerations, a class of distributions F is specified and the results of the simulation hold for all f ∈ F. In a sense, this new method of Monte Carlo simulation was developed with the robustician in mind. That is, the motivation for this new approach is derived from the fact that robusticians often object to classical Monte Carlo simulation on the grounds that the probability distribution for the uncertain parameters is unavailable. They typically begin only with bounds on the uncertain parameters and are unwilling to assume an a priori probability distribution. This is the same starting point for the methods provided here.

show abstract

Probabilistic robust controller design

Cited by 11 publications

References 6 publications

SBT soft fault diagnosis in analog electronic circuits: a sensitivity-based approach by randomized algorithms

SBT soft fault diagnosis in analog electronic circuits: a sensitivity-based approach by randomized algorithms

Design of track following controller of dual actuated HDD servo for 10 Tb/in<sup>2</sup> magnetic recording

Distributionally Robust Monte Carlo Simulation: A Tutorial Survey

Contact Info

Product

Resources

About