Search Results (102)

This paper presents a novel speed controller design for a brushless DC motor (BLDCM) operating under field-oriented control (FOC). The proposed speed controller is developed by integrating the zebra optimization algorithm (ZOA) with sliding mode theory (SMT). In this approach, the parameter ranges of the sliding mode dynamic trajectory control gain, exponential reaching gain, and constant speed reaching gain—three key components of the exponential reaching law-based sliding mode controller (ERLSMC)—are defined as the research space for the ZOA. The feedback speed error and its rate of change are used as features to calculate the fitness value. Subsequently, the fitness value computed by the algorithm is compared with the current best fitness value to determine the optimal position coordinates. These coordinates correspond to the optimal set of gain parameters for the sliding mode speed controller. During the operation of the BLDCM, these optimized parameters are applied to the controller in real time. This enables the system to adjust the three gain parameters dynamically under different operating conditions, thereby reducing the overshoot commonly induced by the ERLSMC. As a result, the speed response of the BLDCM drive system can more accurately and rapidly track the speed command. Therefore, the proposed control strategy is not only characterized by a small number of parameters and ease of tuning, but also does not require large datasets for training, making it highly practical and easy to implement. Finally, the proposed control strategy is simulated using Matlab/Simulink (2024b version) and applied to the BLDCM drive system for experimental testing. Its performance is compared against three types of sliding mode controllers employing different reaching laws: the constant speed reaching law, the exponential reaching law, and the exponential reaching law combined with extension theory (ET). Simulation and experimental results confirm that the proposed novel speed controller outperforms the other three sliding mode controllers based on different reaching laws, both in terms of speed command tracking and load regulation response. Full article

This paper proposes a super-twisting sliding-mode control (STSMC) strategy to enhance the efficiency and stability of a heaving point absorber wave energy converter (PAWEC) system equipped with a permanent magnet synchronous generator (PMSG). In particular, the STSMC is designed to address both generator-side and grid-side control challenges by ensuring precise regulation under varying wave conditions. A dynamical model of the PAWEC is developed to describe system responses, while the power take-off (PTO) mechanism is tailored to maintain consistent generator speed and efficient energy conversion. Lyapunov stability theory is employed to verify the stability of the proposed controller. Simulation studies and tests on a small-scale experimental setup with a 500 W PAWEC model under regular and irregular waves demonstrate that STSMC improves generator speed regulation and power output by more than 30% compared to field-oriented control (FOC), nonlinear adaptive backstepping (NAB), and first-order sliding-mode control (FOSMC). The proposed approach also manages grid-side total harmonic distortion (THD) effectively, keeping it below 5%. These results indicate that STSMC can substantially improve the dynamic performance and energy efficiency of wave energy systems. Full article

In reactive power compensators applied in drives with asynchronous motors, a control strategy focusing on the compensation of higher-order current harmonics is implemented. Control schemes of such compensators typically employ low-pass Butterworth filters with fixed cut-off frequencies to isolate the reactive power component. However, the impact of alternative filter types on compensator performance remains insufficiently explored. Furthermore, in the control systems under consideration, stator phase current signals of the asynchronous motor are used as reference inputs. This approach proves effective under the steady-state operating conditions of the drive. Under non-steady-state operating conditions—typical for traction drive systems—this approach becomes ineffective due to the increased complexity in obtaining accurate reference current signals. As a result, the performance of the filters also deteriorates. It is therefore proposed to investigate the impact of alternative filter types on the efficiency of compensator operation. To address this challenge, the following strategies are suggested: implement higher-order harmonic compensation in the system of stator phase supply voltages of the asynchronous motor; use the control signals from the Field-Oriented Control (FOC) algorithm as reference inputs; and adapt the cut-off frequencies of the filters dynamically to match the frequency of the supply voltage. The simulation results indicate that the use of an elliptic filter in compensator control systems yielded the highest effectiveness. Moreover, the results confirmed the efficiency of the proposed solutions under both steady-state and non-steady-state operating conditions of the traction drive. These approaches support the development of reactive power compensators integrated into traction drive systems for railway rolling stock. Full article

This paper introduces a novel field-oriented control (FOC) strategy for an open-end stator three-phase winding induction motor (OEW-TP-IM) using dual space vector modulation-pulse width modulation (SVM-PWM) inverters. This configuration reduces common mode voltage at the motor’s terminals, enhancing efficiency and reliability. The study presents a backstepping control approach combined with a mean value theorem (MVT)-based observer to improve control accuracy and stability. Stability analysis of the backstepping controller for key control loops, including flux, speed, and currents, is conducted, achieving asymptotic stability as confirmed through Lyapunov’s methods. An advanced observer using sector nonlinearity (SNL) and time-varying parameters from convex theory is developed to manage state observer error dynamics effectively. Stability conditions, defined as linear matrix inequalities (LMIs), are solved using MATLAB R2016b to optimize the observer’s estimator gains. This approach simplifies system complexity by measuring only two line currents, enhancing responsiveness. Comprehensive simulations validate the system’s performance under various conditions, confirming its robustness and effectiveness. This strategy improves the operational dynamics of OEW-TP-IM machine and offers potential for broad industrial applications requiring precise and reliable motor control. Full article

This paper proposes a sensorless field-oriented control (FOC) strategy for permanent magnet synchronous motors (PMSMs), focusing on rotor flux position estimation based on back-electromotive force (back-EMF) signals. The limitations of conventional phase-locked loop (PLL) techniques for rotor flux position estimation along the motor shaft are analyzed, and an enhanced PLL structure is developed to address these deficiencies.In electric vehicle traction applications, precise flux position estimation alone is insufficient; accurate generation of d–q-axis current commands is equally critical. To address this need, a zero-pole-free PI regulator is designed within the PLL module, enabling more accurate flux estimation. Additionally, a gradient-based self-tuning algorithm is employed to identify system parameters, particularly the stator inductance, enabling the controller to optimize current command generation.Comprehensive system-level simulations have been conducted to validate the effectiveness of the proposed sensorless control scheme. Comparative studies demonstrate that the proposed method significantly improves feasibility and robustness for practical PMSM drive applications. Full article

The integration of renewable energy sources, such as wind power, into the electrical grid is essential for the development of sustainable energy systems. Doubly fed induction generators (DFIGs) have been significantly utilized in wind energy conversion systems (WECSs) because of their efficient power generation and variable speed operation. However, optimizing wind power extraction at variable wind speeds remains a major challenge. To address this, an artificial neural network (ANN) is adopted to predict the optimal shaft speed, ensuring maximum power point tracking (MPPT) for a wind energy-driven DFIG connected to a matrix converter (MC). The DFIG is controlled via field-oriented control (FOC), which allows independent power output regulation and separately controls the stator active and reactive power components. Through its compact design, bidirectional power flow, and enhanced harmonic performance, the MC, which is controlled by the simplified Venturini modulation technique, improves the efficiency and dependability of the system. Simulation outcomes confirm that the ANN-based MPPT enhances the power extraction efficiency and improves the system performance. This study shows how wind energy systems can be optimized for smart grids by integrating advanced control techniques like FOC and simplified Venturini modulation with intelligent algorithms like ANN. Full article

Accurate estimation of the rotor flux angle remains a significant challenge when conventional direct or indirect field-oriented control (FOC) strategies are applied to induction motor drives. This paper proposes a novel method for determining the rotor flux angle under steady-state conditions using only stator voltage and current measurements. An adjustable steady-state detection mechanism is introduced and integrated into a phase-locked loop (PLL)-based indirect field-oriented framework to enable a smooth injection of the actual rotor flux angle into the control system. Both simulation and experimental results validate the effectiveness of the proposed method, demonstrating a significant reduction in stator current compared to conventional FOC approaches under identical load torque conditions. Full article

Recent advancements in neural networks (NNs) have underscored their potential for deployment in domains that demand computationally intensive operations, including applications on resource-constrained edge devices. This study investigates the integration of a compact neural network, TinyFC, within the Field-Oriented Control (FOC) framework of a Permanent Magnet Synchronous Motor (PMSM). While proportional–integral (PI) controllers remain a widely adopted choice for FOC due to their simplicity, their performance can degrade significantly under high-frequency speed transitions, where nonlinear dynamics introduce notable inaccuracies. The TinyFC model complements the PI controller by learning the intrinsic dependencies within the control loops and generating corrective signals to alleviate these inaccuracies. To ensure practical implementation, TinyFC underwent extensive optimization procedures, incorporating advanced techniques such as hyperparameter tuning, pruning, and 8-bit quantization. These measures successfully reduced the model’s computational overhead while preserving predictive accuracy. Simulation results demonstrated that embedding TinyFC within the FOC framework substantially reduced overshoot, with the pruned TinyFC entirely eliminating overshoot when integrated into the speed control unit. These findings highlight the feasibility of employing lightweight neural networks for real-time motor control applications, establishing a foundation for more efficient and precise control strategies in edge automotive and industrial systems. Full article

Medium- and high-power drive applications have grown since the past decade as the most common solution for high demanding industrial processes. Multilevel converters, in particular the three-level neutral point clamped (3L-NPC) topology driving medium-voltage induction machines, has become the most commonly adopted solution. In this context, several AC drive control schemes are suitable, such as scalar control (SC), field-oriented control (FOC), model predictive control (MPC), and direct torque control (DTC). Each of these control strategies exhibit a particular operational profile which affects the switching pattern of the converter semiconductors, thus conditioning the switching and conducting losses of these power devices. This work presents a comparison of the conduction and switching losses between different drives control schemes, such as scalar control, field-oriented control, direct torque control, and model predictive control, analyzing their impact on thermal efficiency in a 3L-NPC multilevel converter, under different loading operational conditions. This analysis allows for choosing the most suitable control strategy and switching frequency for a given operational profile. Full article

This paper presents the simulation and controller optimization of a quadrotor Unmanned Aerial Vehicle (UAV) system. The quadrotor model is derived adopting the Newton-Euler approach, and is intended to be constituted by four three-phase Permanent Magnet Synchronous Motors (PMSM) controlled with a velocity control loop-based Field Oriented Control (FOC) technique. The Particle Swarm Optimization (PSO) algorithm is used to tune the parameters of the PID controllers of quadrotor height, quadrotor attitude angles, and PMSMs’ rotational speeds, which represent the eight critical parameters of the PMSM-quadrotor UAV system. The PSO algorithm is designed to optimize eight Square Error (SE) cost functions which quantify the error dynamics of the controlled variables. For each stabilization task, the PID tuning is divided in two phases. Firstly, the PSO optimizes the error dynamics of altitude and attitude angles of the quadrotor UAV. Secondly, the desired steady-state rotational speeds of the PMSMs are derived, and the PSO is used to optimize the motors’ dynamics. Finally, the complete PMSM-Quadrotor UAV system is simulated for stabilization during the target task. The study is carried out by means of simulations in MATLAB/Simulink^®. Full article

This paper presents a cost-efficient estimation method, the filtering observer (FOBS), which provides a smooth estimation through prior estimation, enhancing the field-oriented control (FOC) performance of motion control systems by estimating the angular rotor position, angular rotor velocity, and disturbance torque of permanent magnet synchronous motors (PMSMs). The cost-effective FOBS demonstrates characteristics akin to optimal estimating methods and employs arbitrary pole placement, facilitating more straightforward adjustment of the FOBS gain. The non-linear characteristics of low-resolution and low-cost encoders, the computation of angular rotor velocity using traditional techniques, and disturbances over broad frequency ranges in the servo drive system impair the efficacy of the motion control system. As a cost-effective solution, the FOBS minimizes the deficiencies of the low-cost encoder, reduces oscillations and measurement delays in the speed feedback signal, and provides smooth estimation of disturbance torque. Based on the results from experiments, the FOBS was compared against traditional approaches and the performance of the motion control system was examined. Also, the performance of the motion control system was investigated. The results indicate that these enhancements were achieved with low processing power and an easily implementable estimate technique suitable for low-cost industrial systems. Full article

With their cost-effective manufacturing process, hybrid stepper motors (HSMs) are a popular choice for position control in low-power industrial applications. These versatile motors offer a compelling solution for reducing system costs and size since at standstill/low speeds, HSMs typically have higher torque density with respect to low-power permanent magnet (PM) motors. This higher torque density determines a reduced use of rare-earth PMs and, therefore, a lower environmental footprint. In practical applications, the commonly used microstepping control faces low efficiency, low dynamic performance, vibrations, and a variable maximum continuous torque depending on the working point. In this paper, the operating region of an HSM is extended in the field-weakening (FW) region, showing how field-oriented control (FOC) with FW allows one to strongly increase the drive performance with a slight cost increase thanks to the availability of low-cost magnetic encoders. Due to the fact that FOC provides only the requested current, the HSM faces lower temperatures, lower insulation degradation, and lower permanent magnet demagnetization issues. An experimental evaluation comparing the commonly used microstepping and the proposed FOC with FW is performed on four commercial HSMs with different DC voltage power supplies using an industrial test bench. In particular, the experimental campaign has a focus on steady-state conditions in the case of the maximum continuous torque, showing the advantages of FOC with FW because the advantages in transient conditions are well known. Full article

As high-performance drives, asynchronous motor (AM) drives find extensive use in electric cars, elevators, and machine tools. For these applications, AM drives with direct torque control (DTC) are typically chosen over AM drives with field-oriented control because of their simplicity and quick torque control. Direct torque control of AM drives is frequently achieved using proportional–integral–derivative (PID) controllers. With variable set points and AM parameter ambiguity, these controllers perform poorly. New controllers called fractional-order controllers (FOCs) offer notable improvements over traditional PID controllers due to their enhanced flexibility, robustness, and fine control. In order to provide fast torque performance, this research suggests an AM drive that is regulated by direct torque control theory; nevertheless, the inverter control is optimized for fast response. On the other hand, by employing an optimized fractional-order PI (FOPI) controller, the AM drive speed response is enhanced. The particle swarm optimization (PSO) algorithm is used to optimize the FOPI’s parameters. The MATLAB/Simulink platform was used to model every part of the AM drive with the optimized control system. Three distinct controllers—optimized FOPI, standard PI, and optimized PI—were used to compare the performances of the introduced drive. According to the simulation results, the optimum response in terms of torque and speed was offered by the optimized FOPI controller. The average improvement in the settling time is about 84.4%, and that in the steady-state error is almost killed for all disturbances using the proposed optimized FOPI controller. Furthermore, under parameter uncertainties, the AM’s performance using the suggested optimized FOPI was examined. The outcomes of the simulation demonstrated how resilient the optimized FOPI controller was to changes in the parameters. Full article

Field oriented control (FOC) and direct torque control (DTC) are two strategies used in electric motor control, both with their respective advantages and disadvantages. This paper presents a comparative analysis of these two control methodologies, focusing on their application and performance within a MATLAB Simulink (R2024b) environment for an automotive Permanent Magnet Synchronous Motor (PMSM) drive. The models are created with a focus on realistic drive and test parameters. The simulation results are analyzed to highlight the strengths and weaknesses of each strategy and identify use cases where one method may be superior to the other. In conclusion, this paper contributes to the understanding of FOC and DTC by offering a systematic comparison of their features, performance characteristics, and application scenarios for automotive use. Full article

This paper presents the design of a robust speed controller for brushless DC motors (BLDCMs) under field-oriented control (FOC). The proposed robust controller integrates extension theory (ET) and sliding mode theory (SMT) to achieve robustness. First, the speed difference between the speed command and the actual speed of the BLDCM, along with the rate of change of the speed difference, are divided into 20 interval categories. Then, the feedback speed difference and the rate of change of the speed difference are calculated for their extension correlation with each of the 20 interval categories. The interval category with the highest correlation is used to determine the appropriate control gain for the sliding mode speed controller. This gain adjustment tunes the parameters of the sliding surface in the SMT, thereby suppressing the overshoot of the motor’s speed. Because a sliding surface reaching law of the sliding mode controller (SMC) adopts the exponential approach law (EAL), the system’s speed response can quickly follow the speed command in any state and exhibit an excellent load regulation response. The simplicity of this robust control method, which requires minimal training data, facilitates its easy implementation. Finally, the speed control of the BLDCM is simulated using Matlab/Simulink software (2023b version), and the results are compared with those of the SMC using the constant-speed approach law (CSAL). The simulation and experimental results demonstrate that the proposed robust controller exhibits superior speed command tracking and load regulation responses compared to the traditional SMC. Full article