Computationally Efficient Self-Tuning Controller for DC–DC Switch Mode Power Converters Based on Partial Update Kalman Filter

Ahmeid, Mohamed; Armstrong, Matthew; Al‐Greer, Maher; Gadoue, Shady

doi:10.1109/tpel.2017.2768618

Cited by 18 publications

(7 citation statements)

References 18 publications

(23 reference statements)

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“…Therefore, employing the RLS algorithm in parameter estimation requires a periodic output perturbation to guarantee converter stability. Most recently, the work in [48] proposed combining the classical Kalman filter with a M-Max partial adaptive filter to form a partial update Kalman Filter (PUKF) scheme. This scheme reduces the computational effort of the conventional KF by 50%.…”

Section: Kf Techniquesmentioning

confidence: 99%

Advances on System Identification Techniques for DC–DC Switch Mode Power Converter Applications

Al‐Greer

Armstrong

Ahmeid

et al. 2019

IEEE Trans. Power Electron.

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System identification is fundamental in many recent state-of-the-art developments in power electronic such as modelling, parameter tracking, estimation, self-tuning and adaptive control, health monitoring, and fault detection. Therefore, this paper presents a comprehensive review of parametric, non-parametric, and dual hybrid system identification for DC-DC Switch Mode Power Converter (SMPC) applications. The paper outlines the key challenges inherent with system identification for power electronic applications; speed of estimation, computational complexity, estimation accuracy, tracking capability, and robustness to disturbances and time varying systems. Based on literature in the field, modern solutions to these challenges are discussed in detail. Furthermore, this paper reviews and discusses the various applications of system identification for SMPCs; including health monitoring and fault detection.

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Section: Kf Techniquesmentioning

confidence: 99%

Advances on System Identification Techniques for DC–DC Switch Mode Power Converter Applications

Al‐Greer

Armstrong

Ahmeid

et al. 2019

IEEE Trans. Power Electron.

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“…Industrial grade feedback controllers must exhibit the following two important properties: 1. robustness against uncertainties 2. computationally efficient.In the above cited literature different linear, nonlinear and intelligent controllers have been discussed, however the implementation complexity of such controllers have rarely been reported in literature. In this regard several researchers reported some analysis such as computationally efficient fuzzy control [48], computationally efficient self-tuning controller for DC-DC switch mode power converters [49], computationally efficient predictive robot control [50],computationally efficient distributed predictive controller [51] and computational resource analysis over FPGA for fractional order control (FOSMC) scheme in [52]. Based on the above cited literature , the contributions of this paper are highlighted as follows:…”

Section: Introductionmentioning

confidence: 99%

Industrial Grade Adaptive Control Scheme for a Micro-Grid Integrated Dual Active Bridge Driven Battery Storage System

et al. 2020

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In this paper, an industrial grade adaptive control scheme is proposed for a micro-grid integrated dual active bridge driven battery management system (DIBMS). A benchmark industrial grade adaptive control scheme depends on two factors namely robustness and computational resource utilization when such controllers are implemented over processors. The mathematical model of DIBMS system is nonlinear, thus for desired response, non-linear controllers based on sliding mode variable structure control theory suits it well for the state regulation problem of DIBMS, however such controllers utilize high computational resources when practically implemented over processors. Keeping in view the above performance indices, this paper proposes an industrial grade computationally efficient and finite time adaptive robust convergent control for DIBMS system. A proportional integral (PI) scheme is used as central control unit and Hebbian algorithm with double integration of the state error is introduced for online tuning the gains of central control unit. The robustness and computational resource efficiency of the proposed control paradigm is validated using a laboratory scale test bench through TI Launchpad (TMS320F28379D). The superiority of the proposed AI based PI control paradigm is compared with classical PI, integer order sliding mode control (SMC), and fractional order SMC (FOSMC) in terms of computational resource utilization and robustness under all test conditions.

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“…Moreover, under varying load conditions the PI gains need rapid tuning. Auto tuning methods are proposed in for PI, PD and PID controllers. But the schemes are rather more complex than conventional PI controllers.…”

Section: Introductionmentioning

confidence: 99%

Fixed frequency sliding mode control of renewable energy resources in DC micro grid

Yasin

Ashraf

Bhatti

et al. 2019

Asian Journal of Control

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The rising cost of fossil fuels, their high depleting rate and issues regarding environmental pollution have brought the attention of the researchers towards renewable energy technologies. Different renewable energy resources like wind turbines, fuel cells and solar cells are connected to DC micro grid through controllable power electronic converters. In presence of these diverse generation units, robust controllers are required to ensure good power quality and to regulate grid voltage. This paper presents a sliding mode control based methodology to address the above mentioned challenges. The proposed technique keeps the switching frequency constant so that electromagnetic compatibility (EMC) issues can be solved with conventional filter design. Parallel operation of converter in DC micro gird is considered. Chattering reduction and power quality improvement by harmonic cancellation is proposed. A scaled down hardware for unregulated 11.5 V to 17.5 V input and 24V output is designed and tested.The experimental results show good performance of the controller under different loads and uncertain input voltage conditions. Moreover, the results show the robustness of the closed loop system to sudden variations in load conditions. Furthermore, a significant improvement in power quality is achieved by harmonic cancellation of chattering in the output of the converters.

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Computationally Efficient Self-Tuning Controller for DC–DC Switch Mode Power Converters Based on Partial Update Kalman Filter

Cited by 18 publications

References 18 publications

Advances on System Identification Techniques for DC–DC Switch Mode Power Converter Applications

Advances on System Identification Techniques for DC–DC Switch Mode Power Converter Applications

Industrial Grade Adaptive Control Scheme for a Micro-Grid Integrated Dual Active Bridge Driven Battery Storage System

Fixed frequency sliding mode control of renewable energy resources in DC micro grid

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