Minimum time control of a buck converter by means of fuzzy logic approximation

Gomáriz, S.; Alarcón, Enrique; Martínez, José Antonio; Poveda, A.; Madrenas, Jordi; Guinjoan, F.

doi:10.1109/iecon.1998.724242

Cited by 18 publications

(8 citation statements)

References 6 publications

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“…In some cases that are difficult to implement the electronic configuration of nonlinear control law on the system, the fuzzy logic controller is a good choice due to its simple implementation. In [77], minimum time control is achieved using the fuzzy logic controller.…”

Section: ) Fuzzy Logic Controlmentioning

confidence: 99%

Topologies and Control Schemes of Bidirectional DC–DC Power Converters: An Overview

et al. 2019

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Bidirectional DC-DC power converters are increasingly employed in diverse applications whereby power flow in both forward and reverse directions are required. These include but not limited to energy storage systems, uninterruptable power supplies, electric vehicles, and renewable energy systems, to name a few. This paper aims to review these converters from the point of view of topology as well as control schemes. From the point of view of topology, these converters are divided into two main categories, namely non-isolated and isolated configurations. Each category is divided into eight groups along with their respective schematics and a table of summary. Furthermore, the common control schemes and switching strategies for these converters are also reviewed. Some of the control schemes are typically applied to all DC-DC power converters such as PID, sliding mode, fuzzy, model predictive, digital control, etc. In this context, it should be noted that some switching strategies were designed specifically for isolated bidirectional DC-DC converters in order to improve their performance such as single phase shift, dual phase shift, triple phase shift, etc. The features of each topology and control scheme along with their typical applications are discussed, in order to provide a ground of comparison for realizing new configurations or finding the appropriate converter for the specific application.INDEX TERMS Batteries, bidirectional power flow, control systems, dc-dc power converters. 5) CASCADED BIDIRECTIONAL DC-DC CONVERTER [19], [20] 4) FORWARD BIDIRECTIONAL DC-DC CONVERTER [35]-[39]

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Section: ) Fuzzy Logic Controlmentioning

confidence: 99%

Topologies and Control Schemes of Bidirectional DC–DC Power Converters: An Overview

et al. 2019

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“…In this situation, the use of neural-like algorithms to adjust or tune both the characteristics of membership functions -position over the universe of discourse, and slope-and the output first-order Sugeno coefficients may be considered [10]. The system being discussed will be trained with the ANFIS neuro-fuzzy learning algorithm proposed in [22] [30], by making use of chip-in-the-loop techniques in order to account, at the training phase, for implementation non-idealities.…”

Section: Motivationmentioning

confidence: 99%

Mixed-Signal Neuro-Fuzzy Processor Implementations: Sequential Architectures and Circuit-Level Description

Madrenas¹,

Alarcón²

2002

Series in Machine Perception and Artificial Intelligence

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Mixed-signal VLSI design provides a tradeoff between the fast and compact but fixed analog implementations of neuro/fuzzy feedforward algorithms and the programmable but area and power consuming digital counterparts. In this chapter, a sequentiality study of such systems is performed. Basic blocks for sequential mixed-signal neural and fuzzy computing are proposed, and two sequential example processors are described. Feedback from the designed processors and subcircuits allowed considering the technology constraints for analysis and extension to different sequentiality degrees. IntroductionIn this chapter, we introduce architecture analysis and guidelines to develop sequential analog processing circuits. By means of switched techniques and analog memory elements, analog sequential processing circuits can be designed. These techniques are applied to the development of mixed-signal neural and fuzzy processors. For this purpose, the characteristics, constraints and properties of analog circuits, that are very different from their digital counterparts, have to be taken into account. At the architectural level, starting from sequential architectures of neural and fuzzy models, a performance analysis in terms of area and speed as a function of the sequentiality -or parallelism-degree is developed.Efficiency in terms of silicon area occupancy versus computation performance (speed) is fundamental in autonomous intelligent systems. For 93 Neural Networks and Systolic Array Design Downloaded from www.worldscientific.com by MONASH UNIVERSITY on 04/23/17. For personal use only.

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“…In analog controller implementations, the challenges of implementing a nonlinear control law are notable. For example, current-mode circuit techniques to implement squaring functions are proposed in [22], whereas fuzzy approximation techniques are used to synthesize the multi-input nonlinear switching surface in [23].…”

Section: Introductionmentioning

confidence: 99%

Proximate Time-Optimal Digital Control for Synchronous Buck DC–DC Converters

Yousefzadeh

Babazadeh

Ramachandran

et al. 2008

IEEE Trans. Power Electron.

177

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This paper introduces an approach to near timeoptimal control for synchronous buck dc-dc converters. The proposed proximate time-optimal digital (PTOD) controller is a combination of a constant-frequency pulsewidth modulation (PWM) controller employing a linear PID compensator close to a reference point, and a linear or nonlinear switching surface controller (SSC) away from the reference, together with smooth transitions between the two. A hybrid capacitor current estimator enables switching surface evaluation and eliminates the need for current sensing. The SSC, which is implemented as a small Verilog HDL module, can be easily added to an existing digital PWM controller to construct the PTOD controller. In steady state, the controller operates exactly the same as a standard constant-frequency PWM controller with a linear PID compensator. Simulation and experimental results are shown for a 6.5 V-to-1.3 V, 10 A synchronous buck converter.

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Minimum time control of a buck converter by means of fuzzy logic approximation

Cited by 18 publications

References 6 publications

Topologies and Control Schemes of Bidirectional DC–DC Power Converters: An Overview

Topologies and Control Schemes of Bidirectional DC–DC Power Converters: An Overview

Mixed-Signal Neuro-Fuzzy Processor Implementations: Sequential Architectures and Circuit-Level Description

Proximate Time-Optimal Digital Control for Synchronous Buck DC–DC Converters

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