Adaptive backstepping control of a DC-DC converter in photovoltaic systems

Martín, Aránzazu D.; Vázquez, Jesús R.; Herrera, Reyes S.

doi:10.1109/eurocon.2013.6625096

Cited by 7 publications

(11 citation statements)

References 16 publications

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“…The backstepping control proposed by A. D. Martin and J. R. Vazquez, [13][14], is a robust non-linear control. Besides, it guarantees the stability of the system through Lyapunov functions, reaching the control objective, to extract the maximum power even when there are changeable environmental conditions.…”

Section: Backstepping Mppt Controlmentioning

confidence: 99%

“…This control used a neuro-fuzzy system to find the voltage that supplies the MPP and a fuzzy control to achieve the reference voltage given by the neuro-fuzzy system. Finally, a backstepping control has been designed to implement the MPPT algorithm, [13][14][15]. In this case, the PV output reference voltage is provided by a regression plane and the reference voltage is reached by controlling the duty cycle of the buckboost converter through the switches using a robust non-linear control that guarantees the stability of the system by means of Lyapunov functions.…”

Section: Introductionmentioning

confidence: 99%

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MPPT algorithms comparison in PV systems: P&O, PI, neuro-fuzzy and backstepping controls

Martín

Vázquez

2015

2015 IEEE International Conference on Industrial Technology (ICIT)

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This paper presents a comparative analysis of control methods to extract the maximum power and to track the maximum power point (MPP) from photovoltaic (PV) systems under changeable environmental conditions. The PV system consists of a solar module and a DC/DC converter, in this case a buck-boost converter, connected to a load. The maximum power point tracking (MPPT) algorithms compared are the perturb and observe (P&O) method, the PI control, a neuro-fuzzy and fuzzy technique and finally a backstepping control. The parameters considered for the comparison are the efficiency of the MPPT algorithm taking into account the extracted power from the PV system, steady and dynamic response of the system under changeable conditions such as the temperature and the irradiance and the signals ripple. The methods have been compared and the algorithm with the best results has been implemented in an experimental platform.

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Section: Backstepping Mppt Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MPPT algorithms comparison in PV systems: P&O, PI, neuro-fuzzy and backstepping controls

Martín

Vázquez

2015

2015 IEEE International Conference on Industrial Technology (ICIT)

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“…Previous works [22], [23] have derived the backstepping and the adaptive backstepping MPPT algorithm for the buck-boost, without considering the single-phase inverter dynamics, as the dynamic separation, which is a crucial contribution of this paper, was not used. Therefore, in the simulation results published, a hysteresis current controlled three-phase inverter (constant power) with a PI voltage controller had to be used in [22] and [23] to inject all the PV array power into the grid.…”

Section: Introductionmentioning

confidence: 96%

“…Therefore, in the simulation results published, a hysteresis current controlled three-phase inverter (constant power) with a PI voltage controller had to be used in [22] and [23] to inject all the PV array power into the grid. Powering loads in the dc grid was not considered in [22] and [23].…”

Section: Introductionmentioning

confidence: 99%

Backstepping Control of Smart Grid-Connected Distributed Photovoltaic Power Supplies for Telecom Equipment

Martín

Cano

Silva

et al. 2015

IEEE Trans. Energy Convers.

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Backstepping controllers are obtained for distributed hybrid photovoltaic (PV) power supplies of telecommunication equipment. Grid-connected PV-based power supply units may contain dc-dc buck-boost converters linked to single-phase inverters. This distributed energy resource operated within the selfconsumption concept can aid in the peak-shaving strategy of ac smart grids. New backstepping control laws are obtained for the single-phase inverter and for the buck-boost converter feeding a telecom equipment/battery while sourcing the PV excess power to the smart grid or to grid supply the telecom system. The backstepping approach is robust and able to cope with the grid nonlinearity and uncertainties providing dc input current and voltage controllers for the buck-boost converter to track the PV panel maximum power point, regulating the PV output dc voltage to extract maximum power; unity power factor sinusoidal ac smart grid inverter currents and constant dc-link voltages suited for telecom equipment; and inverter bidirectional power transfer. Experimental results are obtained from a lab setup controlled by one inexpensive dsPIC running the sampling, the backstepping and modulator algorithms. Results show the controllers guarantee maximum power transfer to the telecom equipment/ac grid, ensuring steady dc-link voltage while absorbing/injecting low harmonic distortion current into the smart grid.

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“…Moreover, according to non-minimum phase nature of the boost status, this controller cannot be used directly in DC-DC buck/boost converters. Although adaptive nonlinear controllers are designed for non-minimum phase DC-DC converters in discontinuous and continuous operations [12], [13], the applications of a single controller for both modes are not reported yet.…”

Section: Introductionmentioning

confidence: 99%

Lyapunov Based Adaptive-Robust Control of the Non-Minimum phase DC-DC Converters Using Input-Output Linearization

Salimi¹,

Zakipour²

2015

Journal of Power Electronics

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In this research, a combined adaptive-robust current controller is developed for non-minimum-phase DC-DC converters in a wide range of operations. In the proposed nonlinear controller, load resistance, input voltage and zero interval of the inductor current are estimated using developed adaptation rules and knowing the operating mode of the converter for the closed-loop control is not required; hence, a single controller can be employed for a wide load and line changes in discontinuous and continuous conduction operations. Using the TMS320F2810 digital signal processor, the experimental response of the proposed controller is presented in different operating points of the buck/boost converter. During transition between different modes of the converter, the developed controller has a better dynamic response compared with previously reported adaptive nonlinear approach. Moreover, output voltage steady-state error is zero in different conditions.

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Adaptive backstepping control of a DC-DC converter in photovoltaic systems

Cited by 7 publications

References 16 publications

MPPT algorithms comparison in PV systems: P&O, PI, neuro-fuzzy and backstepping controls

MPPT algorithms comparison in PV systems: P&O, PI, neuro-fuzzy and backstepping controls

Backstepping Control of Smart Grid-Connected Distributed Photovoltaic Power Supplies for Telecom Equipment

Lyapunov Based Adaptive-Robust Control of the Non-Minimum phase DC-DC Converters Using Input-Output Linearization

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