Yazar "Komurcugil, Hasan" seçeneğine göre listele

Listeleniyor 1 - 6 / 6
  • Küçük Resim Yok
    Öğe
    Dual-sliding mode control of nine-switch inverter
    (Wiley, 2021) Gulbudak, Ozan; Gokdag, Mustafa; Komurcugil, Hasan
    This work introduces a novel dual-sliding mode control approach for nine-switch inverter topology. The nine-switch inverter helps regulate multiple ac-loads by using fewer semiconductor devices than the conventional two parallel voltage source inverter system. However, achieving independent control of two sets of ac loads is not a straightforward task when a nine-switch inverter feeds separate load stages. Regarding this consideration, a dual-sliding mode controller that includes a specific decision-making algorithm can be an efficient solution for a multi-load control problem. The proposed strategy offers a good compensation performance for the unconnected load stage under different load utilization profiles. The designed closed-loop system has a rapid response to sudden load change, and no unwanted interaction between individual load stages is observed. The detailed design steps and performance analyses are reported. Experimental results demonstrate the capability and usefulness of the proposed control strategy.
  • Küçük Resim Yok
    Öğe
    Lyapunov-based model predictive control of dual-induction motors fed by a nine-switch inverter to improve the closed-loop stability
    (Elsevier Sci Ltd, 2023) Gulbudak, Ozan; Gokdag, Mustafa; Komurcugil, Hasan
    This study presents a novel Lyapunov-based model predictive control strategy for a nine-switch inverter-based multi-drive system. The drive system includes two ac motors and a single nine-switch inverter (NSI) that is capable of feeding the multiple induction motors. The model predictive control (MPC) is a popular feedback strategy in ac-drive applications due to its fast dynamic characteristics and the skill of handling multiple control goals. Although the MPC offers a rapid dynamic response to load variations, it suffers from closed-loop instability when the cost function is poorly designed. The unwise choice of the tuning parameters, cost function terms, and control constraints cause instability resulting in poor system performance. In particular, the formulation of the selected objective function greatly impacts the closed-loop stability since it tailors the closed-loop characteristics. A simple penalization of the control goal error in the cost function may not ensure asymptotic stability. Motivated by the MPC stability problem, the cost function is reformulated as a Lyapunov energy function to strengthen the closed-loop stability in this paper. The proposed method selects the control input that meets the Lyapunov stability criterion and applies it to the multi-motor driver. The proposed strategy ensures asymptotic stability and provides a robust motor operation by introducing the Lyapunov control constraints. The proposed feedback strategy is experimentally verified using a lab-scaled hardware test platform. The experimental results demonstrate that the suggested control routine offers an improved steady-state characteristic compared to the conventional MPC method. (c) 2017 Elsevier Inc. All rights reserved.
  • Küçük Resim Yok
    Öğe
    Model Predictive Control Strategy for Induction Motor Drive Using Lyapunov Stability Objective
    (Ieee-Inst Electrical Electronics Engineers Inc, 2022) Gulbudak, Ozan; Gokdag, Mustafa; Komurcugil, Hasan
    This article presents a novel Lyapunov-based model predictive control strategy for squirrel-cage induction motor fed by a voltage source inverter. The model predictive control method has received enormous attention thanks to its rapid response to load perturbations. However, the traditional model predictive control method may suffer from instability due to the poor choice of the objective function, weighting factors, or other design parameters. In particular, the selection of the objective function may not be sufficient to ensure global stability. Since the performance of the model predictive control method highly relies on the explicit model of the system, a simple penalization term in the objective function can lead to system instability. As a result, the transient and steady-state performances are negatively affected. The objective function is reformulated as the Lyapunov energy function to deal with this ambiguous situation in this article. The control input constraints are defined in the formulated optimal control problem, and the optimal solution is explored by assessing the Lyapunov stability criterion. The proposed method ensures asymptotic stability since the control action that satisfies the Lyapunov stability condition is selected. The experimental work proves the theoretical concepts. Moreover, the proposed method does not require the weighting factors to control the multiple control goals. The experimental results demonstrate that the proposed control strategy improves the steady-state performance. The machine torque and speed are well regulated, and the quality of the stator current is improved.
  • Küçük Resim Yok
    Öğe
    Model predictive sliding mode control of six-phase induction motor using nine-switch converter
    (Wiley, 2022) Gulbudak, Ozan; Gokdag, Mustafa; Komurcugil, Hasan
    This article proposes a new control strategy to regulate the six-phase induction machine fed by a nine-switch converter. The traditional model predictive control method is a favorable feedback control routine in variable-drive applications. However, the lack of the term that assess the closed-loop stability in the conventional cost function formulation may cause potential closed-loop instability and be incapable of tolerating the parameter mismatch. Furthermore, the conventional model predictive control formulation cannot ensure global optimality in case of deviation from the nominal operating point. In this paper, the closed-loop stability is enhanced by including a sliding mode stability term in the objective function. The traditional cost function is redeveloped as a sliding mode control stability term, and the selection of the control input that satisfies the closed-loop loop stability condition is ensured. The robustness performance of the system is improved, and a better steady-state performance is achieved. The proposed control strategy is proved using a hardware setup including a six-phase 30 degrees spatially shifted induction motor and nine-switch converter prototype. The experimental results demonstrate that a secured six-phase induction motor operation is guaranteed while improving the closed-loop robustness.
  • Küçük Resim Yok
    Öğe
    Optimized sliding surface predictive control of a voltage source inverter with improved steady-state performance
    (Elsevier Science Inc, 2022) Gulbudak, Ozan; Gokdag, Mustafa; Komurcugil, Hasan
    In this paper, an optimized sliding surface predictive control of a three-phase voltage source inverter is introduced. In power electronics, the model predictive control method (MPC) is broadly used and applied to a wide range of energy conversion systems. However, analyzing the stability of the MPC is not a straightforward task, and Lyapunov-based approaches are used to examine the stability characteristics in most cases. MPC is a nonlinear control technique, and the traditional frequency -domain stability tools cannot be used to examine the closed-loop stability. Therefore, a poor design of the MPC without considering the stability may worsen the system performance. Even the norm choice of the objective function leads to closed-loop instability, for example, t1 norm is not a sufficient choice to guarantee the global asymptotical stability. Even though t1 norm offers a low computational burden during the online optimization process, the system may suffer from closed-loop instability. For all these reasons, a stability-guaranteed objective function design procedure is proposed in this paper. The proposed objective function selection process is based on the sliding-mode control theory. The objective function is reformulated as a sliding surface function, and the switching combination that satisfies the sliding mode control stability criteria is selected as an optimum input. The mathematical concepts are experimentally validated, and the results demonstrate the potency of the proposed strategy. (c) 2021 Published by Elsevier Ltd on behalf of ISA.
  • Küçük Resim Yok
    Öğe
    Predictive sliding surface control of squirrel cage induction motor fed by a voltage source inverter: experimental validation and analyses
    (Springer, 2022) Gulbudak, Ozan; Gokdag, Mustafa; Komurcugil, Hasan
    This paper introduces a novel predictive sliding surface control ((PSC)-C-2) strategy for ac-drive applications. The proposed predictive sliding mode control routine is inspired by the model's indirect field-oriented control strategy, including the sliding mode stability criterion. The (PSC)-C-2 method uses the sliding surface function as an objective function to regulate the closed-loop dynamics. The multi-objective objective function is reformulated as a sliding surface function. The feasible control input that guarantees the sliding mode control stability criterion is selected as an optimum control input. The proposed (PSC)-C-2 method is skillful at effectively regulating the stator current, mechanical speed, and torque. The proposed idea is experimentally validated using a hardware setup. The experimental results demonstrate that the proposed control strategy offers a robust squirrel cage induction motor (SCIM) control operation and quick responses to ac load variations. Comprehensive comparison results between the proposed method and the traditional feedback strategies are presented.