Adaptive PSO-LS-wavelet H∞ control for two-wheeled self-balancing scooter

Azizi, Askar; Nourisola, Hamid; Sadeghi-Emamgholi, Amin; Naderisafa, Fahime

doi:10.1007/s12555-016-0001-2

Cited by 8 publications

(4 citation statements)

References 16 publications

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“…Actually, the proposed method reduces noises online. Therefore, it is appropriate for BCI applications [ 69 – 79 ] based on effective classifiers (e.g., linear discriminant analysis, principle component analysis, and support vector machine) [ 80 – 87 ] and studies on cognitive functions in daily life [ 88 , 89 ]. The precisely extracted commands from measured data controls external devices if noises are perfectly removed, (i.e., robot arms, wheelchairs, and prosthetic arms) [ 90 , 91 ].…”

Section: Resultsmentioning

confidence: 99%

Adaptive filtering of physiological noises in fNIRS data

2018

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The study presents a recursive least-squares estimation method with an exponential forgetting factor for noise removal in functional near-infrared spectroscopy data and extraction of hemodynamic responses (HRs) from the measured data. The HR is modeled as a linear regression form in which the expected HR, the first and second derivatives of the expected HR, a short-separation measurement data, three physiological noises, and the baseline drift are included as components in the regression vector. The proposed method is applied to left-motor-cortex experiments on the right thumb and little finger movements in five healthy male participants. The algorithm is evaluated with respect to its performance improvement in terms of contrast-to-noise ratio in comparison with Kalman filter, low-pass filtering, and independent component method. The experimental results show that the proposed model achieves reductions of 77% and 99% in terms of the number of channels exhibiting higher contrast-to-noise ratios in oxy-hemoglobin and deoxy-hemoglobin, respectively. The approach is robust in obtaining consistent HR data. The proposed method is applied for both offline and online noise removal.

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Section: Resultsmentioning

confidence: 99%

Adaptive filtering of physiological noises in fNIRS data

2018

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“…Recently, with the rapid development of battery and control technologies, electric self-balancing scooters (ESSs) are favoured by consumers due to their affordable prices, portability and flexibility [1,2]; however, a series of safety concerns have aroused researchers' interest [3,4]. The control method, mechanical structure and driving posture of ESSs differ from those of conventional bicycles or electric two-wheelers [5]. Head injury was the most common form of injury.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation of the rider's head injury in typical single-electric self-balancing scooter accident scenarios

Fang

Huang

et al. 2022

J. R. Soc. Interface.

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As the use of electric self-balancing scooters (ESSs) increases, so does the number of related traffic accidents. Because of the special control method, mechanical structure and driving posture, ESSs are prone to various single-vehicle accidents, such as collisions with fixed obstacles and falls due to mechanical failures. In various ESS accident scenarios, the rider's head injury is the most frequent injury type. In this study, several typical single-ESS accident scenarios are reconstructed via computational methods, and the risk of riders' head/brain injury is assessed in depth using various injury criteria. Results showed that two types of ESSs (solo- and two-wheeler) do not have clear differences in head kinematics and head injury risks; the head kinematics (or falling posture) and ESS accident scenario exhibit a distinct effect on the head injury responses; half of the analysed ESS riders have a 50% probability of skull fracture, a few riders have a 50% risk of abbreviated injury scale (AIS) 4+ brain injury, and none has a diffuse axonal injury; the ESS speed plays an important role in producing the head/brain injury in ESS riders, and generally, higher ESS speed generates higher level of predicted head injury parameters. These findings will provide theoretical support for preventing head injury among ESS riders and data support for developing and legislating ESSs.

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“…In [9], adaptive robust dynamic balance and motion control were considered for mobile wheeled inverted pendulum. There are many combination methods designed to compensate the weaknesses of single method [10]- [12]. Unfortunately, the above methods are not robust with respect to the structure time-varying inverted pendulum.…”

Section: Introductionmentioning

confidence: 99%

Movements and Balance Control of a Wheel-Leg Robot Based on Uncertainty and Disturbance Estimation Method

Xin

Rong

et al. 2019

IEEE Access

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In order to control the posture, balance and movements of a wheel-leg robot(WLR) precisely, some problems have to be solved. The major problems involve the strongly coupling of movement states, the composite uncertainty with modeling errors, the time-varying internal and the external disturbances. In this paper, a force controller based on the uncertainty and disturbance estimation(UDE) method is designed. The feedforward compensation based on dynamic model allows for compliant and more precise motion control. The UDE can estimate and compensate the composite uncertainty without any priori information effectively. The posture controller is designed based on the virtual model control. The whole controller which includes the posture controller and the movements balance controller is proposed and applied for WLR that built in Webots. The simulation results of trajectory control, balance control and robust test are presented to demonstrate the effectiveness of the whole controller. INDEX TERMS Uncertainty and disturbance estimator (UDE), wheel-leg robot, virtual model control.

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Adaptive PSO-LS-wavelet H∞ control for two-wheeled self-balancing scooter

Cited by 8 publications

References 16 publications

Adaptive filtering of physiological noises in fNIRS data

Adaptive filtering of physiological noises in fNIRS data

Numerical investigation of the rider's head injury in typical single-electric self-balancing scooter accident scenarios

Movements and Balance Control of a Wheel-Leg Robot Based on Uncertainty and Disturbance Estimation Method

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