Adaptive Washout Algorithm Based Fuzzy Tuning for Improving Human Perception

Asadi, Houshyar; Mohammadi, Arash; Mohamed, Shady; Zadeh, Delpak Rahim; Nahavandi, Saeid

doi:10.1007/978-3-319-12643-2_59

Cited by 27 publications

(14 citation statements)

References 4 publications

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“…A total of 200 individuals were considered as being sufficient for the production of reasonably accurate genetic maps. [14] In addition, the optimal solution of the algorithm can depend on the chromosomes which are in the initial search space. The initial values ensure us that even in the worst case of solution, exploring new parameters will be very close to the previous ones.…”

Section: Resultsmentioning

confidence: 99%

“…where d is the number of the chromosomes in the population and the chromosome components 14 represent ω h , ω l , ζ h , ζ l , ω hθ , ω b , c 1 , c 2 , c 3 , c 4 , c 5 , c 6 , k exp , k tanh parameters, respectively. Figure 5 shows the flow chart for GA used in our method.…”

Section: Ga-based Tuningmentioning

confidence: 99%

“…Scaling factors k e,f and k e , ω used in Equation (14) allow us to determine the influence of each error on the fitness function.…”

Section: Ga-based Tuningmentioning

confidence: 99%

“…Therefore, the classical algorithm is better adapted and more appropriate for similar manoeuvres, compared with other algorithms. Also, the classical washout filter is the easiest to adjust and tune, [13,14] however it generates significant false cues because of the linear form of its filters.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Asadi

Mohamed

Zadeh³

et al. 2015

Vehicle System Dynamics

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Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching the motion limitations.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Ga-based Tuningmentioning

confidence: 99%

“…Scaling factors k e,f and k e , ω used in Equation (14) allow us to determine the influence of each error on the fitness function.…”

Section: Ga-based Tuningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Asadi

Mohamed

Zadeh³

et al. 2015

Vehicle System Dynamics

Self Cite

View full text Add to dashboard Cite

show abstract

“…The main disadvantage of classical washout filters comes from the fact that the filter parameters are fixed during its application [19], [20]. This causes inflexibility of the structure and makes the resulting simulator insufficient to suit all circumstances.…”

Section: Introductionmentioning

confidence: 99%

Incorporating Human Perception With the Motion Washout Filter Using Fuzzy Logic Control

Asadi

Mohamed

Nahavandi

2015

IEEE/ASME Trans. Mechatron.

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Nowadays, classical washout filters are extensively used in commercial motion simulators. Even though there are several advantages for classical washout filters, such as short processing time, simplicity and ease of adjustment, they have several shortcomings. The main disadvantage is the fixed scheme and parameters of the classical washout filter cause inflexibility of the structure and thus the resulting simulator fails to suit all circumstances. Moreover, it is a conservative approach and the platform cannot be fully exploited. The aim of this research is to present a fuzzy logic approach and take the human perception error into account in the classical motion cueing algorithm, in order to improve both the physical limits of restitution and realistic human sensations. The fuzzy compensator signal is applied to adjust the filtered signals on the longitudinal and rotational channels online, as well as the tilt coordination to minimize the vestibular sensation error below the human perception threshold. The results indicate that the proposed fuzzy logic controllers significantly minimize the drawbacks of having fixed parameters and conservativeness in the classical washout filter. In addition, the performance of motion cueing algorithm and human perception for most occasions is improved.

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An Improved Washout Algorithm for UPRT Scenario

Tang

Wang

2021

Engineering Psychology and Cognitive Ergonomics

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Adaptive Washout Algorithm Based Fuzzy Tuning for Improving Human Perception

Cited by 27 publications

References 4 publications

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Incorporating Human Perception With the Motion Washout Filter Using Fuzzy Logic Control

An Improved Washout Algorithm for UPRT Scenario

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