Reduction of computational cost in driving simulation subsystems using approximation techniques

Fouladinejad, Nariman; Jalil, Mohamad Kasim Abdul; Taib, Jamaludin Mohd

doi:10.1109/iaict.2014.6922100

Cited by 2 publications

(2 citation statements)

References 39 publications

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“…Surrogate modelling is a kind of an interpolation technique that, in contrast with the conventional approaches that focus on the linear regression term, deals with the error term by considering the correlation between the instances. It has rapidly become a popular method to solve the computation time problems related to constraint and performance evaluations [20][21][22][23][24][25][26][27][28][29][30][31]. Actually, it offers a very interesting advantage since, in many engineering applications, particularly in analogue circuit design, such evaluations/measures can be very time consuming, mainly when using an in-loop technique.…”

Section: Overview Of Surrogate Modelsmentioning

confidence: 99%

Metamodelling Techniques for the Optimal Design of Low-Noise Amplifiers

et al. 2020

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In this article we deal with the optimal sizing of low-noise amplifiers (LNAs) using newly proposed metamodeling techniques. The main objective is to construct metamodels of main performances of the LNAs (namely, the third intercept point (IIP3), the scattering parameters (Sij), and the noise figure (NF)) and use them inside an optimization kernel for maximizing the circuits’ performances. The kriging surrogate modelling technique is used for constructing these models. The particle swarm optimization (PSO) technique is considered as the optimization metaheuristic. Two CMOS amplifiers are considered: a UMTS LNA and a multistandard LNA. Obtained results show that, at the considered working frequencies, the first LNA exhibits at 2.14 GHz a noise figure of 1.30 dB, an S21 of 16.01 dB, an S11 of −12.60 dB, and an IIP3 of 8.30 dBm. At 2 GHz, the second LNA has a noise figure of 1.24 dB, an S21 of 17.16 dB, an S11 of −13.74 dB, and an IIP3 of 4.30 dBm. Comparisons between results obtained using the constructed models and those of the simulation are presented to show the perfect agreement between them.

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Section: Overview Of Surrogate Modelsmentioning

confidence: 99%

Metamodelling Techniques for the Optimal Design of Low-Noise Amplifiers

et al. 2020

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“…Thus, computational delay is the major issue to be resolved in the UTMVDM. 3,20,23 In the following section, we outline the use of approximation techniques to optimize the UTMVDM and review well-known metamodeling techniques.…”

Section: Universiti Teknologi Malaysia Driving Simulatormentioning

confidence: 99%

Development of a surrogate-based vehicle dynamic model to reduce computational delays in a driving simulator

Fouladinejad

Jalil

et al. 2016

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The development of a real-time driving simulator involves highly complex integrated and interdependent subsystems that require a large amount of computational time. When advanced hardware is unavailable for economic reasons, achieving real-time simulation is challenging, and thus delays are inevitable. Moreover, computational delays in the response of driving simulator subsystems reduce the fidelity of the simulation. In this paper, we propose a technique to decrease computational delays in a driving simulator. We used approximation techniques, sensitivity analysis, decomposition, and sampling techniques to develop a surrogate-based vehicle dynamic model (SBVDM). This global surrogate model can be used in place of the conventional vehicle dynamic model to reduce the computational burden while maintaining an acceptable accuracy. Our results showed that the surrogate model can significantly reduce computing costs compared to the computationally expensive conventional model. In addition, the response time of the SBVDM is nearly five times faster than the original simulation codes. Also, as a method to reduce hardware cost, the SBVDM was used and the results showed that most of the responses were accurate and acceptable in relation to longitudinal and lateral dynamics. Based on the results, the authors suggested that the proposed framework could be useful for developing low-cost vehicle simulation systems that require fast computational output.

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Reduction of computational cost in driving simulation subsystems using approximation techniques

Cited by 2 publications

References 39 publications

Metamodelling Techniques for the Optimal Design of Low-Noise Amplifiers

Metamodelling Techniques for the Optimal Design of Low-Noise Amplifiers

Development of a surrogate-based vehicle dynamic model to reduce computational delays in a driving simulator

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