Dimensionless robust control with application to vehicles

Brennan, Sean; Alleyne, Andrew G.

doi:10.1109/tcst.2004.841669

Cited by 21 publications

(13 citation statements)

References 14 publications

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“…Similar work has been conducted before [11,[15][16][17][18], but not on the components mentioned herein. The dimensionless variable method is applied to two specific cases: The first is the analysis of the steady-state operating conditions of alternating current induction motors and permanent magnet direct current motors.…”

Section: Introductionmentioning

confidence: 88%

Scaling of hybrid electric vehicle powertrain components for hardware-in-the-loop simulation

Petersheim

Brennan

2008

2008 IEEE International Conference on Control Applications

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Hardware in the loop (HIL) simulation enables experimental study of prototype hardware systems or control algorithms via real-time interaction between physical hardware and virtual simulations. As a result, this method is a particularly valuable tool for hybrid vehicle powertrain analysis. In the case where novel or prototype hardware is being examined, it is often necessary to scale the signals in and out of the prototype system in order to represent productionsized components. This scaling process is usually done in an adhoc manner. In this work, a formal method is presented that derives appropriate input/output signal conditioning to correctly scale electric vehicle components, namely the electric motor and battery subsystems.

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Section: Introductionmentioning

confidence: 88%

Scaling of hybrid electric vehicle powertrain components for hardware-in-the-loop simulation

Petersheim

Brennan

2008

2008 IEEE International Conference on Control Applications

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“…For a given class of systems under consideration in this work, such as ground planar vehicles, all system models would have the same parametric structure in (14). The difference among the plants would be as a result of varying values of the parameters that populate the system matrices.…”

Section: Model Representations and Dimensionless Transformationmentioning

confidence: 99%

“…Dimensional analysis techniques are used in the design of a scaled car model such that the controller developed on the test bed could be directly implemented on a full size vehicle with prior knowledge of only its wheelbase and longitudinal velocity. By using dimensionless transformations, a dimensionless model of vehicle dynamics was defined in order to design a robust controller that was able to control a wide class of passenger vehicles [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

“…Dimensional analysis provides a framework to characterize the dynamic similarity in a dimensionless framework so that a robust control approach can be used. The benefits include a well-defined nominal model capturing the average dynamics of multiple plants and a lower level of plant-to-plant uncertainty description accounting for the variation among the plants [14][15][16]. The reduced level of dimensionless uncertainty [14][15][16] allowed for a single controller to robustly stabilize a large family of vehicle plants with a higher level of robust performance than could be achieved in a dimensional setting.…”

Section: Introductionmentioning

confidence: 99%

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Dimensional analysis for robust control of planar vehicle dynamics

Hencey

Alleyne

2007

Intl J Robust & Nonlinear

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SUMMARYMost engineered systems with similar functions, which are designed under strict external constraints, share similar dynamics. Using a dimensionless model as system representation, a dimensionless robust controller can be designed and implemented for a class of dynamically similar systems that are different in physical dimension. Dimensionless transformations of timescale, inputs and outputs determine a nominal plant model and plant-to-plant uncertainties in a dimensionless form. Using parameter-dependent normalization, a normalized dimensionless model can be derived that has lower levels of plant-to-plant uncertainty than previous formulations (IEEE Trans. Contr. Syst. Technol. 2005; 13(4):624-630). The benefit of this dimensional analysis is demonstrated by the dynamic analysis of different types of planar vehicle systems. Numerical results show that, by using dimensional analysis, it is possible to obtain a controller that is robust to plant-to-plant parametric uncertainties among specific classes of systems designed with widely varying physical dimensions.

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“…In a narrower application in [11], deletion of dimensions of the original differential equations was used to simplify analysis of the algebraic equations derived from them by means of the Laplace transform. This operation is a tool for identifying a group of uniform stretches.…”

Section: Introductionmentioning

confidence: 99%

Development of a method for approximate solution of nonlinear ordinary differential equations using pendulum motion as an example

Brunetkin

Maksymov

Maksymova

et al. 2017

EEJET

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4thermophysical properties, etc. In turn, this causes variation in a wide range of the process parameters subject to control. In such a situation, application of the results obtained by analysis of linear models is very problematic and even unfeasible in most cases.The search for new approaches to analysis of nonlinear models is an important element in solution of the problem of optimal control of power equipment using non-certified fuel of a variable composition. Literature review and problem statementAn effective way to simplify the study of complex models is to make them dimensionless. Reduction of dimensionality of the modeling space makes it possible both to reduce number of experimental (full-scale and numerical) studies by IntroductionWhen studying behavior of control systems, dynamic conditions require special consideration. Apparatus of ordinary differential equations is most often used as a mathematical tool for studying such systems. General methods of solution have only their linear forms. For this reason, linear (linearized) approaches are used to construct models of object and controller. However more exact models are represented by nonlinear differential equations. This situation leads to the fact that the results obtained can only be used within the range of small variation of parameters of the controlled processes nearby the linearization point.The use of fuel of a variable composition [1,2] in power equipment instead of certified fuel with a constant composition brings about a continuous variation of the fuel calorific value, amount of combustion products, their temperature, MATHEMATICS AND CYBERNETICS -APPLIED ASPECTS DEVELOPMENT OF

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Dimensionless robust control with application to vehicles

Cited by 21 publications

References 14 publications

Scaling of hybrid electric vehicle powertrain components for hardware-in-the-loop simulation

Scaling of hybrid electric vehicle powertrain components for hardware-in-the-loop simulation

Dimensional analysis for robust control of planar vehicle dynamics

Development of a method for approximate solution of nonlinear ordinary differential equations using pendulum motion as an example

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