Brushless DC Motor System Research Articles

Ultrasonic Obstacle Avoidance and Full-Speed-Range Hybrid Control for Intelligent Garages.

In the current study, which focuses on the operational safety problem in intelligent three-dimensional garages, an obstacle avoidance measurement and control scheme for the AGV parking robot is proposed. Under the premise of high-precision distance detection using Kalman filtering, a mathematical model of a brushless DC (BLDC) motor with full-speed range hybrid control is established. MATLAB/Simulink (R2022a) is used to build the control model, which has dual closed-loop vector-controlled motors in the low- to medium-speed range, with photoelectric encoders for speed feedback. The simulation results show that, at lower to medium speeds, the maximum overshoot of the output response curve is 1.5%, and the response time is 0.01 s. However, at higher speeds, there is significant jitter in the speed output waveform. Therefore, the speed feedback is switched to a sliding mode observer (SMO) instead of the original speed sensor at high speeds. Experiments show that, based on the SMO, the problem of speed waveform jitter at high motor speeds can be significantly improved, and the BLDC motor system has strong robustness. The above shows that the motor speed under the full-speed range hybrid control system can meet the AGV control and safety requirements.

Research on the speed control system of brushless DC motor based on fuzzy PID control

Research on the speed control system of brushless DC motor based on fuzzy PID control

Period-1 Motions and Bifurcations of a 3D Brushless DC Motor System with Voltage Disturbance

Abstract: In this paper, the nonlinear dynamic system of a brushless DC motor with voltage disturbance is studied analytically via a generalized harmonic balance method. A truncated Fourier series with time-varying coefficients is utilized to represent the analytical variations of nonlinear currents and voltages within this dynamic system. Bifurcations of periodic currents and voltages are obtained, and their stability is discussed through eigenvalue analysis. The frequency–amplitude characteristics of periodic currents and voltages exhibit complexity in the frequency domain. Comparative illustrations are provided to contrast the analytical solutions with numerical outcomes for periodic currents and voltages. These analytical findings can be effectively employed for controlling the brushless DC motors experiencing voltage disturbances.

A Cascade PID Controller Design with Cuckoo Optimization Algorithm (COA) and Input Shaping (IS)

From past to present, Proportional-Integral-Derivative (PID) controllers stand out as the most widely used types of controllers. Due to the high-performance requirements, experimentally determined controller coefficients necessitate the application of modern optimization techniques. In this study, Ziegler-Nichols, Chien-Hrones-Reswick, and Cohen-Coon methods, which allow parameter calculation through the open-loop system's step response method, were compared with the Cuckoo Optimization Algorithm for PID controllers designed for a brush-commutated DC motor with unknown parameters in the Matlab environment. The comparison was based on Integral of Absolute Error (IAE), Integral of Square Error (ISE), Integral of Time-weighted Absolute Error criterion. Similarly, the performance of the Cuckoo Algorithm was discussed in terms of stability margins and stability peaks. In this comparison, it was observed that the PID controller optimized with the Cuckoo Algorithm operated with high proportional and integral coefficients to minimize the cost function, resulting in overshoot in the system response. Input shaping, a commonly used method in open-loop control of both brushed and brushless DC motor systems, was integrated into the system to mitigate this overshoot. The hybrid controller achieved the best performance in terms of IAE, ISE and ITAE in the system response, with less overshoot compared to the other mentioned methods.

Research on Active Disturbance Rejection Control of Brushless DC Motor Based on Vector Control

A Active Disturbance Rejection Control strategy based on vector control is proposed to address the problems of poor speed overshooting immunity in the control system of brushless DC motor. The motor magnetic chain and torque are decoupled by vector control method to simplify the control, and the traditional PI controller in the speed loop is replaced by a active disturbance rejection controller. The transition process is arranged by tracking differential (TD) to smooth the given speed, which overcomes the contradiction between speed overshoot and rapidity, and improves the response capability of the system; a second-order extended state observer (ESO) is introduced, which estimates and compensates the total system disturbance and improves the system's immunity to disturbance; and the nonlinear law state error feedback (NLSEF) is utilized by the Through the nonlinear law state error feedback (NLSEF), the control accuracy of the system is improved by utilizing the nonlinear control principle of "large gain with small error and small gain with large error". The simulation results show that the control strategy proposed in this paper is characterized by fast response, no overshooting, strong resistance to load disturbance, and strong robustness to changes in load and speed, which proves the feasibility and advancement of this strategy.

Optimized Model Torque Prediction Control Strategy for BLDCM Torque Error and Speed Error Reduction System

This paper presents an improved whale optimization algorithm (IWOA) for optimizing the model predictive torque control (MPTC) of brushless DC motor (BLDCM) to further reduce the problems of strong torque pulsation and high ripple caused by the special structure of BLDCM. IWOA adds a randomized convergence factor strategy to the original algorithm, enabling the parameter weights to be adjusted in time. The relative error between the training set and the predicted values is reduced, and a suitable interval is selected for the target. The proposed method takes into account the switching frequency loss factor in the MPTC system of BLDCM, discarding the traditional trial-and-error method and choosing to control the parameter adjustment by the degree of deviation. The IWOA is compared with the popular whale optimization algorithm (WOA), dragonfly algorithm (DA), ant colony optimization (ACO) algorithm, and grey wolf optimization (GWO) algorithm on the MATLAB SIMULINK platform to verify the effectiveness of the method in dealing with improved chain tracking, reduced torque pulsation, and reduced speed error. The simulation results show that IWOA performs well, with an efficiency of 94.32%.

Neural Network-Based Optimisation of Sinusoidal PWM Controller for VSI-Driven BLDC Motor

Abstract Although increasing the number of switches increases the switch losses, most designed controllers focus on controlling an inverter circuit with more than six switches. The paper aims to address this issue that arises in implementation of the voltage source inverter (VSI) for brushless DC (BLDC) motors. It optimises the sinusoidal pulse width modulation (PWM) controller, minimising total harmonic distortion (THD) while keeping the VSI’s circuit at six switches to avoid increased switching losses. This was achieved by applying an artificial neural network (ANN) to generate a signal, which combines with the already existing reference and carrier signals. The addition of the new signal to the existing signals contributed to generating more pulses compared with the conventional sinusoidal PWM. Simulink was used to design the system and analyse its performance with the conventional and neutral point clamped (NPC) VSI systems. Results indicated that the proposed system performs better when controlled with an LCC filter. Compared with the control experiments, its output waveform has the lowest THD value, which is 6.04%. The switching losses of all the systems were also computed. Results from the computation indicated that the proposed system is capable of reducing the switching losses by 0.6 kW compared with the NPC VSI brushless DC motor (BLDCM) system. BLDCM speed was tested across various conditions; the results are reported in Section 5.

An AEFA-Based Optimum Design of Fuzzy PID Controller for Attitude Control Flywheel with BLDC Motor

A new method for optimizing the fuzzy PID controller, based on an artificial electric field algorithm (AEFA), is proposed in this paper, aiming at improving the stability indicator of the Brushless DC (BLDC) motor for the small satellite attitude control flywheel. The BLDC motor is the basic part of the small satellite attitude control flywheel. In order to accurately control the attitude of the small satellite, a good motor control system is very important. Firstly, the mathematical model of the BLDC motor is established and the BLDC motor speed control system using traditional PID control is designed. Secondly, considering that the small satellite speed control system is a nonlinear system, a fuzzy PID control is designed to solve the shortcomings of the fixed parameters of the traditional PID control. Finally, we find that the control accuracy of the fuzzy PID control will change with the range of the input. Therefore, we introduce the AEFA to optimize fuzzy PID to achieve high-precision attitude control of small satellites. By simulating the BLDC motor system, the proposed fuzzy PID controller based on AEFA is compared with the traditional PID controller and the fuzzy PID controller. Results from different controllers show that the proposed control method could effectively reduce steady state error. In addition, the proposed fuzzy PID–AEFA controller has the better anti-jamming capability.

Design of a Two-phase Brushless DC Motor Control System

With the depletion of petrochemical resources in the whole region, reducing the dependence on petrochemical energy, and reducing environmental pollution and carbon emissions have become the common goal of the world. Pure electric vehicles are a kind of new energy vehicle. Compared with fuel vehicles and other types of electric vehicles, they have high energy utilization efficiency, low price, and less pollution emission. Therefore, this paper will discuss the structure, working principle, and control system of the two-phase brushless DC motor and put forward the two-phase four-bridge arm drive scheme to improve the voltage utilization rate and achieve more environmentally friendly and efficient electric energy application.

A Novel Voltage-Boosting Modulation Strategy to Reduce DC-Link Capacitance for Brushless DC Motor Drives

In this article, a novel method is proposed to reduce the dc-link capacitance of the brushless dc motor (BLDCM) system. In the proposed strategy, the charging mode of dc-link capacitor is designed to improve the energy stored by dc-link capacitor in the charging process instead of reducing the discharge time of dc-link capacitor used in previous article. The new modulation strategy and controller is designed to pump the dc-link capacitor voltage and ensure that it exceeds the ac voltage peak. The proposed modulation strategy has three vectors. The charging vector is used to improve the dc-link capacitor voltage, and the effective vector and zero vector are used to adjust the motor speed. For practical application, we provide an engineering calculation method to get the dc-link capacitance, and prove that the dc-link voltage can exceed the average voltage of the BLDCM. The experimental results verify the correctness of the theoretical analysis and the feasibility of the proposed method.

Modeling and analysis of brushless DC motor system based on intelligent controllers

The constant innovative advancements of brushless DC motors (BLDCMs) have discovered a wide scope of utilizations. For instance, underground electric vehicles, drones, and submerged bikes have just confirmed elite BLDCMs. Be that as it may, their appropriation requires control frameworks to screen torque, speed and other execution attributes. This paper presents numerous brilliant controllers structure and order line programming to assemble, alter and mimic intelligent to control BLDCMs. Recently planned graphical user interface (GUI) structure for Multi controllers: conventional proportional integral derivative (PID) controller, intelligent controller based fuzzy techniques: type 1, type 2, and modified type 2 fuzzy logic controller (T1FLC, IT2FLC, and MIT2FLC respectively). Different phases of the problematic framework configuration process, from the underlying depiction to the last usage, can be acquired from the altered tool compartment. MATLAB Ver.2019b was utilized to mimic and plan all procedure GUI. The agreeable aftereffects of MIT2FLC have been approved also; the examination gives the subtleties of the GUI program through estimations, shapes, flowcharts and code, giving understanding into the presumptions of common-sense boundaries that may emerge in such a minimal effort mentor for BLDCM. At last, the outcomes acquired through a few reproduction tests affirm the legitimacy of the showed math model and designing of intelligent controllers.

Decentralized Time-Delay Control Using Partial Variables With Measurable States for a Class of Interconnected Systems With Time Delays.

This article deals with the problems of stability and control of the interconnected system (IS) with unknown time-varying delays via decentralized time-delay control using partial variables with measurable states. First, the model of the IS with time delays is established, and the relevant control scheme is proposed. The control scheme just needs to control all or partial state variables corresponding to the elements on the main diagonal of the gain matrices, which can reduce the control cost and improve the flexibility of control. In addition, there are no additional restrictions in the process of designing the controller. Second, relevant lemmas are derived. The exponential boundedness and stability analysis of the IS with time delays are presented, respectively, by stability theory, and related results are derived. Meanwhile, the stability domain of the IS is estimated. Besides, the obtained results can also be used for many practical systems, such as the interconnected power system, the multislave teleoperation systems, the brushless dc motor (BLDCM) system, and the chaotic system. Finally, the effectiveness and application of the obtained results are verified by several examples.

Predictor-Based Neural Dynamic Surface Control of a Nontriangular System With Unknown Disturbances

For a class of nontriangular nonlinear systems in presence of unknown disturbances, we propose a predictor-based neural dynamic surface control (PNDSC) strategy in this paper. This nontriangular system is transformed via the mean value theorem, and a predictor is then constructed. To avoid an algebraic loop problem, partial state vectors are employed as input signals of neural networks (NNs) for approximating unknown dynamics, and compensation items are designed to compensate for approximation errors from NNs. Different from the traditional NDSC, the PNDSC in this paper utilizes prediction errors to update learning parameters for improving NNs’ learning behaviors with overlarge adaptive gains. On the basis of improved NNs’ approximation behaviors, a predictor-based NNs disturbance observer (PNNDO) is constructed for compensation for external disturbances and approximation errors from NNs. Furthermore, with predictors, a normalization method of weights is developed to reduce the number of online learning parameters. On the basis of the aforementioned result, measurement noises are taken into account in our predictor-based neural control strategy. We employ predictor states, rather than measurement information paralyzed by noises, in design of our control strategy. This reduces high-frequency oscillations in control input. A Lyapunov-based stability analysis shows that all signals are ultimately bounded in the closed-loop system. Finally, the effectiveness of the proposed control strategy is verified by a numerical example and a permanent magnet brushless DC motor system.

Design of LLC resonant converter with silicon carbide MOSFET switches and nonlinear adaptive sliding controller for brushless DC motor system

Introduction. The high voltage gain DC-DC converters are increasingly used in many power electronics application systems, due to their benefits of increased voltage output, reduced noise contents, uninterrupted power supply, and ensured system reliability. Most of the existing works are highly concentrated on developing the high voltage DC-DC converter and controller topologies for goal improving the steady state response of brushless DC motor driving system and also obtain the regulated voltage with increased power density and reduced harmonics, the LLC resonant DC-DC converter is implemented with the silicon carbide MOSFET switching devices Problem. Yet, it facing the major problems of increased switching loss, conduction loss, error outputs, time consumption, and reduced efficiency. Also the existing works are mainly concentrating on improving the voltage gain, regulation, and operating performance of the power system with reduced loss of factors by using the different types of converters and controlling techniques. The goal of this work is to obtain the improved voltage gain output with reduced loss factors and harmonic distortions. Method. Because, this type of converter has the ability to generate the high gain DC output voltage fed to the brushless DC motor with reduced harmonics and loss factors. Also, the nonlinear adaptive sliding controller is implemented to generate the controlling pulses for triggering the switching components properly. For this operation, the best gain parameters are selected based on the duty cycle, feedback DC voltage and current, and gain of silicon carbide MOSFET. By using this, the controlling signals are generated and given to the converter, which helps to control the brushless DC motor with steady state error. Practical value. The simulation results of the proposed LLC silicon carbide MOSFET incorporated with nonlinear adaptive sliding controller controlling scheme are validated and compared by using various evaluation indicators.

Commutation Torque Ripple Reduction Strategy of Brushless DC Motor Drives Based on Boosting Voltage of DC-Link Small Capacitor.

Based on the brushless DC motor system with DC-link small capacitance powered by a single-phase AC power source, a boosting DC-link voltage strategy to reduce the commutation torque ripple of brushless DC motors is proposed in this paper. The control strategy utilizes the special topology of the motor system to boost the DC-link capacitor voltage in a specific zone during the non-commutation period. During the commutation period, the high voltage of the DC-link capacitor is released to meet the voltage requirement of the brushless DC motor during commutation. In order to reduce the commutation torque ripple and ensure the normal operation of the brushless DC motor, each rectifier cycle is divided into three zones according to the characteristics of the periodic change of the rectifier output voltage. Different operation modes are proposed for different zones. In DC-link capacitor boost voltage mode, the DC-link capacitor boosts the voltage to meet the voltage of the motor demand during the commutation period for achieving the purpose of reducing the commutation torque ripple. In this paper, the controller of the brushless DC motor system is designed and the experimental platform is built. The experimental results verified the correctness of the theoretical analysis and the feasibility of the proposed method.

Control for Isokinetic Exercise with External Disturbance

Isokinetic exercise is considered as one of the most effective ways for rehabilitation and muscle strength enhancement. As rehabilitation equipment, the isokinetic exercise device assists isokinetic movement using a single fixed axis and relevant joint adapters, and it requires high stability and safety performances to cooperate with human. In this paper, a brushless DC motor (BLDCM) was adopted to make a study of isokinetic control. Fractional‐order fuzzy PID (FOFPID) controller is an effective controller for the nonlinear system to realize isokinetic control according to reference speed and irregular disturbance (load torque). The model of the BLDCM and FOFPID controller system is built in MATLAB/Simulink to simulate the velocity response of the controller, and a comparison between the FOFPID controller and PID controller is made to verify the system stability.

Mathematical modeling and analysis of fractional-order brushless DC motor

In this paper, we consider a fractional-order model of a brushless DC motor. To develop a mathematical model, we use the concept of the Liouville–Caputo noninteger derivative with the Mittag-Lefler kernel. We find that the fractional-order brushless DC motor system exhibits the character of chaos. For the proposed system, we show the largest exponent to be 0.711625. We calculate the equilibrium points of the model and discuss their local stability. We apply an iterative scheme by using the Laplace transform to find a special solution in this case. By taking into account the rule of trapezoidal product integration we develop two iterative methods to find an approximate solution of the system. We also study the existence and uniqueness of solutions. We take into account the numerical solutions for Caputo Liouville product integration and Atangana–Baleanu Caputo product integration. This scheme has an implicit structure. The numerical simulations indicate that the obtained approximate solutions are in excellent agreement with the expected theoretical results.

Fault Diagnosis Method for Joint Motor Inverter Power Tube of Live Working Robot

The joint motor of live working robot adopts brushless DC motor system. Because of the interference of unstable factors in working environment and the vulnerability of power electronic devices, inverter power tube is the most vulnerable link in the system. Based on the model of brushless dc motor system and simulation analysis of the open circuit fault mode of inverter power tube, this paper summarizes the distortion characteristics of the three-phase current waveform of inverter power tube output. An open circuit fault diagnosis method for inverter power tube based on the variation of three-phase current waveform is presented, and the correctness and feasibility of the method are verified.

Stability Analysis of a Class of Fractional-Order Nonlinear Systems Under Unknown Stochastic Disturbance and Actuator Saturation

This brief investigates the problem of mean-square exponential stability for a class of fractional-order nonlinear systems (FNSs) subject to unknown stochastic disturbance and actuator saturation. By means of theory of stochastic system and fractional calculus theory, and Cauchy-Schwartz inequality, mean-square exponential stability criteria are obtained. The constraint on the order of the system is relaxed. Meantime, the relevant state feedback controller is designed to overcome the influence of the stochastic disturbance and actuator saturation. Finally, effectiveness of the results is demonstrated via the fractional-order brushless DC motor(BLDCM) system.

Design and implementation of an intelligent multi modular joint (MMJ)-brain controller: application to aircraft and brushless DC (BLDC) systems

This paper presents a new intelligent controller by inspiring the mammalian brain connections with various internal parts. Cerebrum, Cerebellum and brain stem are modeled to develop a new intelligent control scheme. There is a modular connection between Cerebellum and Cerebrum with deep nuclei and red nuclei that passes through brain stem to send an action signal. A computational model is developed by inspiring connections and named as Multi Modular Joint-Brain controller (MMJ-BC). The proposed MMJ-BC controller effectiveness is validated by applying on nonlinear dynamical systems such as position control of Aircraft system and speed control of Brushless DC motor. MMJ-BC performance has been analyzed under various operating conditions and obtained results are verified by comparing with the performance of existing Cerebrum (BELBIC) and with Cerebellum based controllers. The results demonstrates excellent performance and capable to withstand under different operating conditions.