Fuzzy-Based Parameter Optimization of Adaptive Unscented Kalman Filter: Methodology and Experimental Validation

Asl, Reza Mohammadi; Palm, Rainer; Wu, Huapeng; Handroos, Heikki

doi:10.1109/access.2020.2979987

Cited by 23 publications

(10 citation statements)

References 39 publications

(37 reference statements)

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“…According to limited and uncertain information from different sensors, the methodology is able to merge this information and be applied to the problem of trace optimization in an unknown maneuvering target in Sichuan province in China. In Asl et al (2020), an optimization methodology of adaptive Unscented Kalman Filter (UKF) is presented by an evolutionary fuzzy algorithm named Fuzzy Adaptive Grasshopper Optimization Algorithm, and it is efficiently applied to different benchmark functions, such as robotic manipulator and servo-hydraulic system, whose performance is better compared to previous versions of UKF. Despite the extensive literature in these contexts, there are still many fields to be explored regarding the association of Kalman filters and fuzzy systems.…”

Section: Related Workmentioning

confidence: 99%

A novel interval type-2 fuzzy Kalman filtering and tracking of experimental data

Gomes

Serra

2021

Evolving Systems

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In this paper, a methodology for design of fuzzy Kalman filter, using interval type-2 fuzzy models, in discrete time domain, via spectral decomposition of experimental data, is proposed. The adopted methodology consists of recursive parametric estimation of local state space linear submodels of interval type-2 fuzzy Kalman filter for tracking and forecasting of the dynamics inherited to experimental data, using an interval type-2 fuzzy version of Observer/Kalman Filter Identification (OKID) algorithm. The partitioning of the experimental data is performed by interval type-2 fuzzy Gustafson–Kessel clustering algorithm. The interval Kalman gains in the consequent proposition of interval type-2 fuzzy Kalman filter are updated according to unobservable components computed by recursive spectral decomposition of experimental data. Computational results illustrate the efficiency of proposed methodology for filtering and tracking the time delayed state variables of Chen’s chaotic attractor in a noisy environment, and experimental results illustrate its applicability for adaptive and real time forecasting the dynamic spread behavior of novel Coronavirus 2019 (COVID-19) outbreak in Brazil.

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Section: Related Workmentioning

confidence: 99%

A novel interval type-2 fuzzy Kalman filtering and tracking of experimental data

Gomes

Serra

2021

Evolving Systems

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“…with φ cc := L a,0 i * a + R a,0 i a + k T,0 ω m , d ia = − dia , which can be stabilized by the proposed control law: (11) ∀t ≥ 0, with the current error convergent rate k cc > 0 and active-damping parameter b d,cc > 0 resulting in the polezero cancellation together with the control gain form above. See Section IV for details.…”

Section: ) Current Controllermentioning

confidence: 99%

Pole-Zero Cancellation Speed Control With Variable Current Cut-Off Frequency for Servo Motors

You

Kim

2021

IEEE Access

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This article presents a novel system parameter-independent double-loop solution to the speed control problem of servo motors incorporating the variable current cut-off frequency into the current-loop. The active damping terms for both the inner and outer loops make it possible to assign the pole-zero cancellation nature to the closed-loop system by cooperating the structured proportional-integral gains. The proposed analytic variable cut-off frequency mechanism automatically boosts the transient current-cut off frequency and decreases it to its initial value in the steady-state operation to secure the improved relative stability and reduced current ripple level, maintaining the rapid speed tracking behavior (feasibility of the high-speed cut-off frequency). The QUBE-servo2 kit experimentally verifies the practical benefits of the proposed solution.

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“…This is in order to simultaneously reduce the ripples caused by the inaccurate external sensors and inappropriate weighting factor for the IM FCS-MPTC working over the highspeed range. The fuzzy control theories are employed in this paper as the fuzzy logic has the advantage of providing a solution to the machine control problem that can be cast in terms that human operators can understand [30][31][32][33][34][35], making it easier to mechanize tasks that are already successfully performed by humans. It deserves to be mentioned the adaptive weighting factor tuning method is able to solve the second internal problem above when it is executed alone.…”

Section: Introductionmentioning

confidence: 99%

“…This assists in evaluating the effectiveness of the proportional and integral factors designed in the previous period and ultimately provide guidelines for generating new control parameters. What needs to be mentioned is that although the fuzzy control strategies that are achieved by using the previous states or errors were studied previously in [33][34][35]. The proposed fuzzy controller is still pretty novel considering its structure and role in suppressing the steady-state ripples of an IM.…”

Section: Introductionmentioning

confidence: 99%

Ripple Attenuation for Induction Motor Finite Control Set Model Predictive Torque Control Using Novel Fuzzy Adaptive Techniques

et al. 2021

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Finite control set model predictive torque control (FCS-MPTC) strategy has been widely used in induction motor (IM) control due to its fast response characteristic. Although the dynamics of the FCS-MPTC method are highly commended, its steady-state performance—ripple deserves attention in the meantime. To improve the steady-state performance of the IM drives, this paper proposes an improved FCS-MPTC strategy, based on a novel fuzzy adaptive speed controller and an adaptive weighting factor, tuning strategy to reduce the speed, torque and flux ripples caused by different factors. Firstly, a discrete predicting plant model (PPM) with a new flux observer is established, laying the ground for achieving an FCS-MPTC algorithm accurately. Secondly, after analyzing the essential factors in establishing a fuzzy adaptive PI controller, with high ripple suppression capacity, an improved three-dimensional controller is designed. Simultaneously, the implementation procedures of the fuzzy adaptive PI controller-based FCS-MPTC are presented. Considering that a weighting factor must be employed in the cost function of an FCS-MPTC method, system ripples increase if the value of the weighting factor is inappropriate. Then, on that basis, a novel fuzzy adaptive theory-based weighting factor tuning strategy is proposed, with the real-time torque and flux performance balanced. Finally, both simulation and hardware-in-loop (HIL) test are conducted on a 1.1 kW IM drive to verify the proposed ripple reduction algorithms.

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Fuzzy-Based Parameter Optimization of Adaptive Unscented Kalman Filter: Methodology and Experimental Validation

Cited by 23 publications

References 39 publications

A novel interval type-2 fuzzy Kalman filtering and tracking of experimental data

A novel interval type-2 fuzzy Kalman filtering and tracking of experimental data

Pole-Zero Cancellation Speed Control With Variable Current Cut-Off Frequency for Servo Motors

Ripple Attenuation for Induction Motor Finite Control Set Model Predictive Torque Control Using Novel Fuzzy Adaptive Techniques

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