A robust passivity based model predictive control for buck converter suppling constant power load

Zhou, Jiyao; Zhang, Qianye; Hassan, Mustafa Alrayah; Zhang, Zehua; Hou, Mingxuan; Wu, Shang; Li, Yongjian; Li, Er‐Ping; Guerrero, Josep M.

doi:10.1016/j.egyr.2021.09.193

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…Refs. [9][10][11][12][13][14] listed some of the most effective controllers used for power converters, including sliding mode, fuzzy-based, and model predictive control techniques. These methods are more desirable for practical usages as they depict better output regulation, lower sensitivity to more comprehensive disturbances, and higher control adaptability.…”

Section: Introductionmentioning

confidence: 99%

Design of a novel robust type‐2 fuzzy‐based adaptive backstepping controller optimized with antlion algorithm for buck converter

Khavari

Ghamari

Abdollahzadeh

et al. 2023

IET Control Theory & Appl

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A type‐2 fuzzy logic‐based adaptive backstepping control (T2F‐ABSC) approach is presented for a DC/DC Buck converter. Lyapunov‐based backstepping control (BSC), which can guarantee convergence along with asymptotic stability of the system. Also, the black‐box technique is applied for the proposed system, which does not require an accurate mathematical model resulting in a lower computational burden, easy implementation, and lower dependency on the states of the model. On the other hand, for wider ranges of disturbances, including parametric variations, load uncertainty, supply voltage variation, and noise, this approach shows an unsuitable practical application based on its fixed gain values; therefore, the control parameters need to be optimized again to provide ideal operations. Type‐2 fuzzy structure is adopted here to optimize the gains of the ABSM in challenging conditions. Type‐2 fuzzy (T2F) has higher efficiency and faster dynamics with more adaptability to the system. To enhance the performance of the T2F, antlion optimization (ALO) has been used in this structure. ALO is a modern nature‐inspired algorithm, and it has some advantages over other optimizing algorithms. Furthermore, it has ability to find optimal answers in a shorter time, more accurately in contrast to the other optimization algorithms and is used to tune the membership function parameters of the (T2F) under the diverse search spaces. To depict the strength of the designed work, fuzzy‐PID and backstepping schemes proposed to carry out an analysis with this work.

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Section: Introductionmentioning

confidence: 99%

Design of a novel robust type‐2 fuzzy‐based adaptive backstepping controller optimized with antlion algorithm for buck converter

Khavari

Ghamari

Abdollahzadeh

et al. 2023

IET Control Theory & Appl

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show abstract

“…Power electronic systems using cascaded distributed DC-DC converters are being used in a wide range of scenarios, including smart microgrids, spacecraft, telecommunications, automotive power systems, ships, ground-based computer systems, and medical electronics [5][6][7]. In a cascaded system of DC-DC converters, the later stage's DC converter with a closed-loop control can be considered as a CPL for the previous stage's DC converter.…”

Section: Introductionmentioning

confidence: 99%

An Objective Holographic Feedback Linearization Based on a Sliding Mode Control for a Buck Converter with a Constant Power Load

Li,

Pi,

Zhou

et al. 2023

Electronics

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As a typical load, the constant power load (CPL) has negative impedance characteristics. The stability of the buck converter system with a mixed load of CPL and resistive load is affected by the size of the CPL. When the resistive load is larger than the CPL, the buck converter with the output voltage as an output function is a non-minimum phase nonlinear system, because its linear approximation has a right-half-plane pole. The non-minimum phase characteristic limits the application of many control techniques, but the objective holographic feedback linearization control (OHFLC) method is a good control strategy that can bypass the non-minimum phase system and make the system stable. However, the traditional OHFLC method, in designing the controller, generally uses a linear optimal quadratic design method to obtain a linear feedback control law. It requires a state quantity component with a one-order relative degree to the system. But it is not easy to find such a suitable state quantity with a one-order relative degree to the system. In this paper, an improved OHFLC method is proposed for Buck converters with a mixed loads of CPL and resistive loads, using the sliding mode control (SMC) theory to design the controller, so that the output state quantity components with different relative degrees to the system can be used in the holographic feedback linearization method. Finally, the simulation and experimental results also demonstrate that this method has the same, or even better, dynamic response performance and robustness than the traditional OHFLC method.

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“…A method to passivate a given system by using an input-output transformation matrix was described in [62]. Some versions of variations of passivitybased control methods were described in [62]- [68]. [65] presented the passivity-based control combining proportional integral control to improve robustness in DC Microgrids with constant power loads.…”

Section: Introductionmentioning

confidence: 99%

A Passivity-based Control Combined with Sliding Mode Control for a DC-DC Boost Power Converter

Huynh,

Duong,

Nguyen

2023

Journal of Robotics and Control

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In this paper, a passivity-based control combined with sliding mode control for a DC-DC boost power converter is proposed. Moreover, a passivity-based control for a DC-DC boost power converter is also proposed. Using a co-ordinate transformation of state variables and control input, a DC-DC boost power converter is passive. A new plant is zero-state observable and the equilibrium point at origin of this plant is asymptotically stable. Then, a passivity-based control is applied to this plant such that the capacitor voltage is equal to the desired voltage. Additionally, the sliding mode control law is chosen such that the derivative of Lyapunov function is negative semidefinite. Finally, a passivity-based control combined with sliding mode control law is applied to this plant such that the capacitor voltage is equal to the desired voltage. The simulation results of the passivity-based control, the sliding mode control and the passivity-based control combined with sliding mode control demonstrate the effectiveness and show that the capacitor voltage is kept at the desired voltage when the desired voltage, the input voltage E and the load resistor R are changed. The results show that compared with the passivity-based control, the passivity-based control combined with sliding mode control has better performance such as shorter settling time, 8.5 ms when R changes and it has smaller steady-state error, which is indicated by the value of integral absolute error (IAE), 0.0679 when the desired voltage changes. The paper has limitations such as the assumed circuit parameters.

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A robust passivity based model predictive control for buck converter suppling constant power load

Cited by 8 publications

References 28 publications

Design of a novel robust type‐2 fuzzy‐based adaptive backstepping controller optimized with antlion algorithm for buck converter

Design of a novel robust type‐2 fuzzy‐based adaptive backstepping controller optimized with antlion algorithm for buck converter

An Objective Holographic Feedback Linearization Based on a Sliding Mode Control for a Buck Converter with a Constant Power Load

A Passivity-based Control Combined with Sliding Mode Control for a DC-DC Boost Power Converter

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