Hybrid Computing for BLDC Speed Control and Stability Analysis

By Sybil Swanson

Hybrid Computing for BLDC Speed Control and Stability Analysis, written by Sybil Swanson, is a comprehensive guide to the design, control, and stability analysis of Brushless DC (BLDC) motors using hybrid computing techniques. This book is an excellent resource for researchers, engineers, and students in the fields of electrical engineering and control systems.

The book begins by introducing the basics of BLDC motors and their applications, followed by an overview of the mathematical models used for their analysis. The author then presents the fundamental concepts of hybrid computing techniques, including artificial neural networks, fuzzy logic systems, and genetic algorithms. These techniques are used to design control systems for BLDC motors, optimizing their speed and stability.

The book also covers various simulation and optimization techniques, including Matlab/Simulink, PSO, and particle swarm optimization. The author provides detailed examples and case studies of BLDC speed control and stability analysis, including the effects of parameter variations and disturbances.

Hybrid Computing for BLDC Speed Control and Stability Analysis is an essential resource for anyone interested in the design and control of BLDC motors using hybrid computing techniques. The book provides a comprehensive and practical approach to understanding the principles of BLDC control, making it an excellent reference for both students and professionals in the field.

• Language: English
• Publisher: Sybil Swanson
• Release date: Apr 9, 2024
• ISBN: 9798224022342

Book preview

GENERAL

In the industrial applications, mainly two types of direct current motors are utilized. One is the traditional Direct Current (DC) motor where  the flux gets induced by the current flowing through the field windings of the static pole structure. The other class is the Brushless Direct Current (BLDC) motor in which the permanent magnet delivers the required air gap flux replacing the wire-wound field poles. BLDC motors have their applications in wide range of industrial sectors due to its structure and suitability in handling any critical situations. These motors are popular and widely  employed  because of their superior performance characteristics. Few of the merits of BLDC motor include – long operational life as no brushes are there; minimal maintenance; constructive dynamical characteristics; high efficiency rate; comparatively linear torque-speed characteristics; free from  noise;  controllable DC sources and so on. Speed of the motor and torque depends on the magnetic field strength developed by the energized motor windings that depends on the current. Henceforth the speed of the motor is varied by adjusting the rotor current and rotor voltage. These motors are driven with respect to the nominal power so as to guarantee safe operation and high efficiency (Godfrey & Sankaranarayanan 2018, Hung et al. 2007, Vanchinathan & Valluvan 2018, Lad & Chudamani 2018).

Speed regulation is one of the significant characteristics to be adopted in the field of brushless DC motor drive for effective and accurate speed and position control operations. In this research thesis, stability analysis and performance characteristics of brushless direct current motor is studied  and implemented with the novel hybrid soft computing techniques. The performance characteristics of the designed speed controller employing the proposed techniques are tested for a step change in input speed and also for impulsive load disturbances. Further, the stability analysis of the new  proposed controller is investigated with Lyapunov stability criterion by deriving the positive definite functions. From the results simulated and hardware realization, it is well proven that the proposed controller is more stable and guarantees consistent performance than other  considered  controllers in all aspects. Simulation-based comparisons illustrate that the design methodologies outperform other controller designs from the literature.

OPERATIONAL FEATURES AND IMPORTANCE  OF  BLDC MOTOR

Fundamentally, a brushless direct current motor is an electronically commuted direct current motor without brushes. The controller delivers  current pulses to the windings of the motor that controls the speed and torque of the synchronous motor. BLDC motor is constructed with two parts – rotor and stator. The rotating part is the rotor and possesses rotor magnets and stationary part is the stator with stator windings. In the construction of BLDC motor, permanent magnets are attached to the rotor and this moves the electromagnets to the stator. In order to activate the electromagnets of the  shaft turns, high power transistors are employed. The power distribution is carried out by the controller employing solid-state circuit. BLDC  motor  differs from the conventional motor in a manner that it does not contains brushes and here commutation is carried out electrically employing an

electronic drive so as to feed the stator windings. Fig 1.1 shows a typical BLDC motor. The arrangement of rotor can be done in two ways in BLDC motors,

  Rotor can be placed outside the core and the windings in the  core

  By placing the windings outside the core

In the first case, the rotor magnets perform as an insulator and this reduces the heat dissipation rate from the motor and operates at a low current. This is widely employed in fans. In the second case, the  motor  dissipates more heat and this increases the torque of the motor. This type of BLDC motors are used in hard disk drives. Table 1.1 presents a comparison between brushed and brushless motors.

Table 1.1 Comparison between brushed and brushless motor

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Figure 1.1 A typical BLDC motor

The importance of BLDC motors lies in their advantages as presented below:

  BLDC motors velocity is calculated by the frequency during which the current is supplied and not on the voltage, hence are more efficient.

  Since no brushes are used, the losses due to friction are minimal and achieve increased efficiency.

  High speed operation under any condition.

  Much less noise and no sparking during operation.

  They possess lower rotor inertia hence BLDC motors are  capable to accelerate and decelerate easily.

  Employs more electromagnets on the stator for better control mechanism.

  BLDC motors do not have brushes hence are more reliable and have low maintenance cost.

  No ionizing sparks from the commutator and as well reduced electromagnetic interference.

  They automatically get cooled by conduction and for inner cooling they do not require separate air flow.

Due to their efficiency and reliability, BLDC motors are widely employed in devices that require continuous  running. They are employed in  air conditioners, washing machines, and consumer electronics and in fans, wherein their high efficiency rate has resulted in prominent reduction  of  power consumption. BLDC motors are as well used in spin hard disc drives and these motors maintain the drive to operate over longer span of time due to their durability. They are better suited for controlling the force in respect of robot arm control and positioning; wherein it requires a current proportionate to the external force. BLDC motors are replacing brushed motors in mobility carts and they perform precise control resulting in extended battery  life.  BLDC motors are employed in drones as well; here the drone’s attitude is controlled by controlling the rotational speed of each rotor.

Considering these advantages and applicability of BLDC motors, this research thesis focussed to work on the  control operations of brushless  DC motors and also aims to develop better speed controller models so as to achieve better efficiency and reliability of the motor.

PROBLEM DEFINITION AND NEED FOR RESEARCH WORK

Speed control and regulation is one of the most prominent characteristics to be adopted in BLDC motor drive for effective and accurate

control operations. In the current scenario, control unit is designed with micro-electronic devices employing a micro-controller, hard-wired micro- electronics unit and so on. The applicability of analog controllers is still present, but they cannot carry out feedback mechanism and  control  operations. But employing these type of analog controllers, it is possible to implement high performance control algorithms like field control and vector control.

Currently, Pulse Width Modulation (PWM) controllers are used to control the speed of the motor. In this case, the mean voltage given or the  mean current flowing through the motor gets changed based on the ON and OFF time of the pulses that control the speed of the motor. The duty cycle of the pulse modulated wave controls the speed of the motor. When the duty  cycle changed, the speed can be changed.

The main problem addressed in this work is the speed control of BLDC motor and subsequently its stability aspect is analysed. It is highly important to control the speed of the BLDC motor to make the motor to operate at a desired rate. On controlling the input dc voltage of the motor the speed of the brushless dc motor can be controlled. When the voltage becomes higher, the higher is the speed of the motor. During normal operation of the motor or when it runs below the rated speed, the input voltage of the armature gets changed through the controller model. When the motor gets operated above the rated speed, the flux gets weakened by advancing the exiting  current.

In this research contribution, closed loop speed control of BLDC motor is carried out. This methodology involves in controlling the input  supply voltage by means of speed feedback from the motor. Thus the supply voltage gets controlled based on the error signal. This approach of changing  the supply voltage based on the error signal is executed with a PID controller

or employing soft computing based controllers like – fuzzy, neural models or soft computing based PID controllers.

The desired speed of the motor is given as input to the controller model. The difference evaluated between the sensed speed and the desired speed is the error signal and the devised controllers generate the control signal based on this error signal and presents to the system through feedback mechanism. This is the performance measure and is specified as  ‘Mean  Square Error’. Mean square error (MSE) is one of the error indices used to indicate the performance of the developed hybrid soft computing models.

− 2

MSE can be defined as, MSE = :Ι

––––––––

(1.1)

i=1 N

where, Ydesired is the desired output, Ycalculated is the calculated output and ‘N’ refers to the number of samples. Equation (1.1) is the fitness function for the developed hybrid soft computing models and this can be rewritten as,

––––––––

min

N ( Ydesired − Ycalculated )2

f ( y )

i=1 N

constraint s : Ydesired � 1500,Ycalculated � 1500

(1.2)

This intends the designed hybrid soft computing based controllers  to give the dc power input to the motor. Hence, using this controller mechanism, the speed of the brushless dc motor shall be controlled and it is made to rotate at any desired speed.

REVIEW ON EARLIER WORKS

It is well inferred from the review on the existing literatures that numerous works have been carried out for developing an effective speed controller for speed regulation of a BLDC motor. In this section, the review is

carried out on three different aspects. Initially, a review is made on  the  various methods of speed control of BLDC motors employing both traditional and heuristic methods. A survey is made on the growth of different neural network models and how they are employed for different control applications. Based on this review on growth of neural network models, a conclusion was derived to devised neural network controllers for speed control of BLDC motors. Additionally, survey is also made on the evolution and importance of Particle Swarm Optimization (PSO).

There have been so many evolutionary and swarm based optimization algorithms devised day-by-day, but in this research contribution PSO algorithm is employed. Even though PSO algorithm was devised in the year 1995 (Kennedy & Eberhart 1995) and is two decades old, the versatility and reliability can never be compromised. Considering its effective search mechanism process, in this work variants and hybrid forms of PSO algorithms are formulated and applied along with neural network models to  perform speed control of BLDC motor.

Literature Survey on Speed Control of BLDC Motors

A review on different traditional and heuristic techniques employed for speed control of BLDC motor is presented in this section. Also, related works carried over the past years in speed control and stability analysis of BLDC motors along with PID controller tuning is as well presented in this section.

In a work by Milivojevic et al. (2011), the authors discussed digital PWM control for a BLDC drive in both motoring and generating modes of operation. This work also investigated potential stability issues under various conditions of load disturbances and also owing to the reduction in processor

capability. The brushless DC motor drive system with input shaping using classical control theory was analyzed by Murugan et al. (2013).

A sensorless control method for a high-speed brushless DC motor based on the line-to-line back electromotive force (back EMF) was proposed by Liu et al. (2014). In order to obtain the commutation signals, the line-to- line voltages are obtained by the low-pass filters. However, due to the low- pass filters, wide speed range, and other factors, the actual commutation signals are significantly delayed by more than 90 electrical degrees which limits the acceleration of the motor. Zolfaghari & Taher (2014) presented a new controller for speed control problem of the BLDC motors. The nonlinear model of the motor is approximated by implementation of fuzzy rules. Using this model and Linear Matrix Inequality (LMI) optimization, a robust controller for purpose of speed control of the motor has been designed and applied to it.

Parveen & Muralidhar (2015) compared two methods of controlling speed of BLDC motor. First method uses a controlled voltage source for controlling speed of BLDC motor. The speed is regulated by PI controller. Second method is a simplified one which is current controlled modulation technique.Here, different values of damping ratio are used to understand the generalized drive performance. A simple novel digital sensor Pulse Width Modulation (PWM) control has been implemented for a trapezoidal BLDC motor drive system (Wang & Zai2015).

Two different speed controllers i.e., fuzzy online gain tuned anti wind up Proportional Integral and Derivative (PID) controller and fuzzy PID supervised online ANFIS controller for the speed control of brushless  dc motor has been developed by Premkumar & Manikandan (2015). In order to validate the effectiveness of the proposed controllers, the brushless dc motor  is operated under constant load condition, varying load conditions and

varying set speed conditions. Design and development of remote controlled quadcopter using PID (Proportional Integral Derivative) controller implemented with Ardupilot Mega board has been proposed by Praveen & Pillai (2016). The system consists of IMU (Inertial Measurement Unit) which consists of speed control of four BLDC motors to enable the  quad copter fly  in six directions.

Jeddi et al. (2016) described the modelling and implementation of a sensorless control system (back-EMF control) on a brushless DC motor used  in a traction drive system for an electric vehicle. The dynamic behaviour of  the motor is first modelled, so speed PI controller, DC-AC inverter and commutation logic blocks are developed, in order to  obtain a  full control of the entire drive system. Arun Noyal Doss et al. (2016) presented a cost effective speed control method for brushless dc (BLDC) motor drive using PI controller. Pulse Width Modulation (PWM) technique is used