# DDC Control Techniques for Three-Phase BLDC Motor Position Control
## 1 Introduction  
In the past two decades, the brushless direct current motor has played a vital role in industrial development. These motors are widely used in industrial applications because of their better architecture that is quite suitable for many critical tasks [1; 2]. The rapid development of BLDC motors in the automobile industry, based on hybrid drives that require higher efficiency permanent magnet motor (PMM) drives, was the establishment of awareness in BLDC motors [3; 4]. These motors have a linear relationship between torque, current, and voltage, and they operate on a revolution per minute (RPM) basis. A BLDC motor has the same speed torque curve as a conventional permanent magnet DC motor. However, it has different advantages, such as a small volume, a quick dynamic response, greater power density, better efficiency, and it can be directly associated with the mechanical load [5; 6; 7]. The BLDC motor does not use brushes, and it has extended operating life without noise. Moreover, it has Permanent Magnet, which is why its ratio is quite a bit higher between torque and motor size and is quite suitable for that application where weight and space are significant. It has a variety of speed ranges, better torque and speed characteristics as compared to other motors, and it is more suitable for applications such as a gimbal platform. However, in this research, the BLDC motor is chosen due to its low inertia in the rotor that helps to improve its acceleration time when it is operating for a short period of time [8]. In this research, a BLDC motor is selected as compared to a DC servo motor because it has many problems, such as maintenance and durability issues and higher noise. On the other hand, one of the major drawbacks of a BLDC motor is that its control is very difficult compared with a DC servo motor. For the real time operating scenario of a BLDC motor, the number of poles and coils plays an important role to control the motor. If the number of poles and coils are greater, the motor will be more responsive to its input. However, this research uses a three-phase BLDC motor along with 14 poles and 12 coils because using BLDC motors with fewer coils and poles will reduce their performance. Previously, different control algorithms have been used to control the position of three-phase BLDC motors, including the Proportional Integral controller [8], the variable structure controller [9; 10; 11], model predictive control [12], and model reference adaptive control [13]. However, in this research, the proposed hybrid controller is a combination of discrete time sliding mode control with model free adaptive control to control the position of a three-phase BLDC motor, since MFAC is the modest form of a robust control scheme with less mathematical calculations. The nonlinear behavior of the system is linearized by using compact form dynamic linearization (CFDL) and partial form dynamic linearization (PFDL) [14; 15; 16; 17]. Previously, SMC-based algorithms used a pseudo partial derivative (PPD) to linearize the system. The proposed control algorithm compared with the traditional proportional integral derivative, MFAC, MFLAC and model free adaptive based sliding mode control (MFA-SMC) methods. The above algorithms are applied to control the three-phase BLDC motor successfully, and their performance analysis is verified by using simulations on MATLAB. The simulated results show that our proposed controller exhibits greater robustness and more accurate tracking. In this manuscript, the position control of a BLDC motor is considered by using a data-driven MFA-based controller. The major advancements of this manuscript are: (1) the description of control system modeling and preliminary information to validate the model-based control design.