Essay: Design speed controller for BLDC motor with satisfied speed control characteristics

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  • Design speed controller for BLDC motor with satisfied speed control characteristics
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Brushless DC motors (BLDC) find wide applications in industries due to their high power density and ease of control. These motors are generally controlled using a three phase power semiconductor bridge. For starting and the providing proper commutation sequence to turn on the power devices in the inverter bridge the rotor position sensors required. Based on the rotor position, the power devices are commutated sequentially every 60 degrees. To achieve desired level of performance the motor requires suitable speed controllers. In case of permanent magnet motors, usually speed control isachieved by using proportional-integral-derivative (PID) controller. Although conventional PID controllersare widely used in the industry due to their simple control structure and ease of implementation, these controllers pose difficulties where there are some control complexity such as nonlinearity, load disturbances and parametric variations. Moreover PID controllers require precise linear mathematical models.

Brushless DC motors (BLDCM) are widely used for many industrial applications because of their high efficiency, high torque and low volume. This paper proposed an improved Adaptive Fuzzy PID controller to control speed of BLDCM. This paper provides an overview of performance conventional PID controller, Fuzzy PID controller and Adaptive Fuzzy PID controller. It is difficult to tune the parameters and get satisfied control characteristics by using normal conventional PID controller. As the Adaptive Fuzzy has the ability to satisfied control characteristics and it is easy for computing. The experimental results verify that a Adaptive Fuzzy PID controller has better control performance than the both Fuzzy PID controller and conventional PID controller. The modeling, control and simulation of the BLDC motor have been done using the software package MATLAB/SIMULINK.

Key words— Brushless DC (BLDC) motors, proportional integral derivative (PID) controller, Fuzzy PID controller, Adaptive Fuzzy PID controller.

There are primarily two types of dc motor utilized as a part of industry. The first is the traditional dc motor where the flux is made by the current through the field coil of the stationary shaft structure. The second type is the brushless dc motor where the permanent magnet gives the important air gap flux rather than the wire-wound field poles. BLDC motor is typically characterized as a permanent magnet synchronous motor with a trapezoidal Back EMF waveform shape. As the name suggests, BLDC motor don\’t utilize brushes for replacement; rather, they are electronically commutated. As of late, elite BLDC motor drives are generally utilized for variable rate drive systems of the modern applications and electric vehicles.

The electric drive system is a crucial part to drive any motor. The electric drive system is utilized to control the position, velocity and torque of the electric motor. Numerous works has been done on force converter topologies, control plan of the electric drive systems and on the motortypes with a specific end goal to upgrade and enhance the execution of the electric motor to precisely perform and do what is required.

BLDC motor have a few focal points over ordinary brushed motor and acceptance motor. Some of these are; better speed versus torque characteristics, high element reaction, high productivity, long working life, silent operation and higher rate ranges. Furthermore BLDC motor are dependable, simple to control, and modest. Due to their positive electrical and mechanical properties, BLDC motor are generally utilized as a part of servo applications, for example, car, aviation, restorative, instrumentation, incitation, apply autonomy, machine apparatuses, and modern computerization hardware thus on as of late.

Established PID controllers are regularly utilized as a part of businesses because of their straightforwardness and simplicity of usage. In straight system model, controller parameters of the PID controller are anything but difficult to decide and coming about great control exhibitions. In any case, for nonlinear system model applications, for example, BLDC motor drive, control execution of the PID controller gets to be poor and hard to decide the controller parameters.

Keeping in mind the end goal to enhance control execution of the BLDC motor drive, knowledge controllers, for example, fuzzy logic control for BLDC motor is utilized. Fuzzy logic has numerous favorable circumstances over customary control. It doesn\’t utilize numerical model of the system and along these lines is less delicate to system parameter changes. Plan targets that are hard to express mathematically will be effectively combined in a fuzzy controller by linguistic rules. What\’s more, its execution is basic and direct.

1.2 Motivation

The brushless dc motors are gradually replacing dc motors and ac motors because of their small size, high operating speed, high efficiency, less maintenance and excellent speed torque characteristics. They are used in robotics, computer disk drives, machine tools, electric vehicle and battery powered applications.

Fuzzysystems are showing great guarantee in customer items, modern and business systems, and choice emotionally supportive networks. The expression \”fuzzy\” refers to the capacity of managing uncertain or obscure sources of info. Rather than utilizing complex numerical conditions, fuzzylogic utilizes phonetic portrayals to characterize the relationship between the info data and the yield activity. In building systems, fuzzylogic gives an advantageous and easy to understand front-end to create control programs, helping originators to focus on the utilitarian targets, not on the arithmetic. This basic content examined the way of fuzziness and demonstrated how fuzzy operations are performed, and how fuzzy tenets can combine the underlyingknowledge. Fuzzylogic is an intense device that is infesting each field and signing successful usage.

The conventional control scheme such as proportional (P), proportional integral (PI) and proportional integral derivative (PID) have been produced for position control ofBLDCmotor. Nonetheless, these controllers require an exact scientific model and can be connected just to exceptionally direct systems. These controllers neglect to yield better execution when the system gets to be non-straight and it is a lumbering procedure to tune these controllers. As we probably am aware, the BLDC motor control systems are non-direct due to the variety in their parameters and shifting burdens; fuzzylogic with PID controller can be utilized to have the system to manage nonlinearity.

1.3 Objective

• Main objective of this study is to design speed controller for BLDC motor with satisfied speed control characteristics.

• Speed control characteristics of BLDC motor will be improved using different control techniques, which are simulated using simulation software.

• After studying different controllers, a novel approach using adaptive fuzzy logic PID controller will be simulated.

• By observing all stimulated results for controller, a speed controller with speed characteristics having less rise time, overshootis implemented.

These are the types of applications where a variable speed is more important thankeeping the accuracy of the speed at a set speed. In these types of applications, the load is directly coupled to the motor shaft. For example, fans, pumps and blowers come under these types of applications. These applications demand low-cost controllers, mostly Operating in open-loop.

1.4.2. Applications with Varying Loads

These are the types of applications where the load on the motor varies over a speedrange. These applications may demand high-speed control accuracy and good dynamic responses. In home appliances, washers, dryers and compressors are good examples. In Automotive, fuel pump control, electronic steering control, motor control and electric vehicle control are good examples of these. In aerospace, there are a number of applications, like centrifuges, pumps, robotic arm controls, gyroscope controls and so on. These applications may use speed feedback devices and may run in semi-closed loop or in total closed loop. These applications use advanced control algorithms, thus complicating the controller. Also, this increases the price of the complete system.

1.4.3. Positioning Applications

Most of the industrial and automation types of application come under this category.The applications in this category have some kind of power transmission, which could be mechanical gears or timer belts, or a simple belt driven system. In these applications, the dynamic response of speed and torque are important. Also, these applications may havefrequent reversal of rotation direction. A typical cycle will have an accelerating phase, a constant speed phase and a deceleration and positioning phase. The load on the motor may vary during all of these phases, causing the controller to be complex. These systems mostly operate in closed loop.

There could be three control loops functioning simultaneously: Torque Control Loop,Speed Control Loop and Position Control Loop. Optical encoder or synchronous resolves are used for measuring the actual speed of the motor. In some cases, the same sensors are used to get relative position information. Otherwise, separate position sensors may be used to get absolute positions. Computer Numeric Controlled (CNC) machines are a good example of this.

1.5. A Comparison of BLDC with conventional DC motors

In a conventional (brushed) DC-motor, the brushes make mechanical contact with aset of electrical contacts on the rotor (called the commutator), forming an electrical circuit between the DC electrical source and the armature coil-windings. As the armature rotates on axis, the stationary brushes come into contact with different sections of the rotating commutator. The commutator and brush-system form a set of electrical switches, each firing in sequence, such that electrical-power always flows through the armature-coil closest to the stationary stator (permanent magnet).

In a BLDC motor, the electromagnets do not move; instead, the permanent magnets rotate and the armature remains static. This gets around the problem of how to transfer current to a moving armature. In order to do this, an intelligent electronic controller replaces the commutator assembly. The controller performs the same power-distribution found in a brushed DC motor, but using a solid-state circuit rather than a commutator. BLDC motors have many advantages over DC motors. A few of these are:

• High dynamic response

• High efficiency

• Long operating life

• Noiseless operation

• Higher speed ranges

BLDC\’s main disadvantage is higher cost which arises from two issues. First, BLDCmotors require complex electronic speed controllers to run. Brushed DC-motors can be regulated by a comparatively trivial variable resistor (potentiometer or rheostat), which is inefficient but also satisfactory for cost-sensitive applications.

1.6. Problem statement:

To achieve desired level of performance the motor requires suitable speed controllers.In case of permanent magnet motors, usually speed control is achieved by using proportionalintegral derivative (PID) controller. Although conventional PID controllers are widely used in the industry due to their simple control structure and ease of implementation, these controllers pose difficulties where there are some control complexity such as nonlinearity, load disturbances and parametric variations. Moreover PID controllers require precise linear mathematical models. As the PMBLDC machine has nonlinear model, the linear PID may no longer be suitable.

The Fuzzy Logic (FL) approach applied to speed control leads to an improved dynamic behavior of the motor drive system and an immune to load perturbations and parameter variations. Fuzzy logic control offers an improvement in the quality of the speed response. Most of these controllers use mathematical models and are sensitive to parametric variations. These controllers are inherently robust to load disturbances. Besides, fuzzy logic controllers can be easily implemented.

There are predominantly two types of dc motor utilized as a part of industry. The first is the routine dc motor where the flux is created by the current through the field loop of the stationary shaft structure. The second type is the brushless dc motor (BLDC motor) where the permanent magnet gives the fundamental air hole flux rather than the wire-wound field poles. This type of motor not just has the benefits of DC motor, for example, better speed ability and no mechanical commutates, additionally has the upside of AC motor, for example, basic structure, higher unwavering quality and free upkeep. Likewise, brushless DC motor has the accompanying preferences: littler volume, high compel, and basic system structure. Brushless DC motor (BLDC) contain an intense permanent magnet rotor and settled stator windings. The stationary stator windings are normally three stages, which implies that three separate voltages are supplied to the three distinct arrangements of windings.

A “brushless” DC Motor does not use brushes. It uses a permanent magnet and accomplishes the switching by electronically switching the polarity. In order to accomplish this in a controlled manner a position/speed feedback mechanism and an electronic controller are required. Feedback may be through a physical device mounted on the motor such as Hall Effect devices or a complex algorithm based on the motors own changing characteristics such as back EMF. The controller may be mounted on the motor or may be separate. It is easy to see that without brushes the brushless DC motor has a much greater MTBM (mean time between maintenance). However what is forgotten is the brushless motor design is more complex with the addition of the feedback and the controller and therefore has lower reliability. This difference becomes more pronounced when the motor must operate in environments that are considered hostile to electronics.. BLDC motors are used in industries such as Appliances, HVAC industry, medical, electric traction, road vehicles, aircrafts, military equipment, hard disk drive, etc. Hence it is needful to design low cost, efficient speed controller for BLDC motor. The time response characteristics of the BLDC Motor are observed and compared from the design of different controllers.

The different type’s controller design techniques that are used for the speed control of Brush Less DC motor involve [1]:

1. Fuzzy PID controller

2. Genetic Algorithm based PID controller

3. QFT Controller.

Traditional PID controllers are generally utilized as a part of industry because of their straightforwardness, clear usefulness and simplicity of usage. Then, fuzzy control, a shrewd control technique emulating the intelligent considering human and being autonomous on precise numerical model of the controlled item, can defeat a few weaknesses of the customary PID. Yet, the fuzzy is a nonlinear control and the yield of the controller has the static mistake. At that point fuzzy PID control which combines the conventional PID control and the fuzzy control calculation is an answer.

Run of the mill fuzzy PID controllers are tentatively planned in view of working states of the control systems and their dynamic reactions. Subsequently, the run of the mill fuzzy PID controllers can\’t adjust for an extensive variety of workplaces with expansive variety of annoyances. Thus, other control strategies, for example, vigorous control, keen hypothesis, or estimation techniques are expected to combine with the fuzzy PID to conquer this shortcoming. Among them, fuzzy PID joined with neural system is a practical arrangement [2]. Consequently Genetic control Algorithm has been executed for the control of BLDC Motor. Hereditary Algorithms (GAs) are a stochastic worldwide pursuit strategy that copies the procedure of characteristic advancement. Hereditary Algorithms have been appeared to be fit for finding superior territories in complex areas without encountering the challenges connected with high dimensionality or false optima as may happen with angle OK methods. Utilizing hereditary calculations to play out the tuning of the controller will bring about the ideal controller being assessed for the system without fail. In any case, certain enhancement issues can\’t be fathomed by utilizing hereditary calculations. This happens because of ineffectively known wellness capacities which create awful chromosome obstructs regardless of the way that lone great chromosome squares traverse furthermore there is no total affirmation that the hereditary calculation will locate a worldwide ideal. Consequently the vigorous control outline strategy QFT has been considered. QFT is a powerful controller outline strategy for direct and nonlinear systems, with uncommon accentuation on the utilization criticism for accomplishing great execution against vulnerability and aggravations.

Before applying human intelligence techniques to PID controller, PWM schemes are used for speed control [3]. PWM is based on the assumption of linear relationship between the phase current and the torque, similar to that in a brushed dc motor. Therefore, by adjusting phase current, the electromagnetic torque can be controlled to meet the requirement. Instantaneous current in the motor is regulated in each phase by a hysteresis regulator, which maintains the current within adjustable limits.

Design of a PID controller for a brushless DC motor using particle swarm optimization is also has better performance [4] compared to Linear Quadratic Regulator and Genetic Algorithm methods. PSO is one of the optimization techniques and a kind of evolutionary computation technique in which assumptions based on behaviour of human is decided.

BLDC motor drives, systems in which a permanent magnet excited synchronous motor is fed with a variable frequency inverter controlled by a shaft position sensor. There appears a lack of commercial simulation packages for the design of controller for such BLDC motor drives.

One fundamental reason has been that the high programming advancement cost acquired is not defended for their common ease fragmentary/basic kW application regions, for example, CNC machine devices and robot drives; even it could suggest the likelihood of demagnetizing the rotor magnets amid authorizing or tuning stages. All things considered, recursive prototyping of both the motor and inverter might be included in novel drive setups for development and specific applications, bringing about high formative expense of the drive system. Enhanced magnet material with high (B.H), item additionally pushes the BLDC motor business sector to many kW application territories where authorizing blunders turn out to be restrictively excessive. Displaying is along these lines vital and may offer potential cost investment funds.

A brushless dc motor is a dc motor turned back to front, so that the field is on the rotor and the armature is on the stator. The brushless dc motor is really a lasting magnet air conditioning motor whose torque-current characteristics impersonate the dc motor. Rather than commutating the armature current utilizing brushes, electronic compensation is utilized. This disposes of the issues connected with the brush and the commutator plan, for instance, starting and destroying of the commutator-brush course of action, in this manner, making a BLDC more rough when contrasted with a dc motor. Having the armature on the stator makes it simple to lead warm far from the windings, and if sought, having cooling game plan for the armature windings is much less demanding when contrasted with a dc motor.

In actuality, a BLDC is a changed PMSM motor with the adjustment being that the back-emf is trapezoidal as opposed to being sinusoidal as on account of PMSM. The \”substitution area\” of the back-emf of a BLDC motor ought to be as little as could reasonably be expected, while in the meantime itshould not be so thin as to make it hard to commutate a period of that motor when driven by a Current Source Inverter. The level consistent part of the backemf ought to be 120°for a smooth torque generation. The position of the rotor can be detected by utilizing lobby sensors.

Driving hardware comprises of three stage power convertors, which use six force transistors to invigorate two BLDC motor stages simultaneously. The rotor position, which decides the exchanging grouping of the MOSFET transistors, is identified by method for 3 Hall sensors mounted on the stator. By utilizing Hall sensor data and the indication of reference current (created by Reference current generator), Decoder piece produces signal vector of back EMF. The fundamental thought of running motor in inverse bearing is by giving inverse current. A brush less dc motor is characterized as a lasting synchronous machine with rotor position criticism. The brushless motor are by and large controlled utilizing a three stage power semiconductor span. The motor requires a rotor position sensor for beginning and for giving appropriate compensation succession to turn on the force gadgets in the inverter span. In view of the rotor position, the force gadgets are commutated consecutively every 60 degrees. Rather than commutating the armature current utilizing brushes, electronic replacement is utilized hence it is an electronic motor. This takes out the issues connected with the brush and the commutator course of action, for instance, starting and destroying of the commutator brush plan, consequently, making a BLDC more rough when contrasted with a dc motor. The basic block diagram brushless dc motor as shown Fig.3.3.The brush less dc motor consist of four main parts power converter, permanent magnet-synchronous machine (PMSM) sensors, and control algorithm. The power converter transforms power from the source to the PMSM which in turn converts electrical energy to mechanical energy. One of the salient features of the brush less dc motor is the rotor position sensors ,based on the rotor position and command signals which may be a torque command ,voltage command ,speed command and so on the control algorithms determine the gate signal to each semiconductor in the power electronic converter.

The structure of the control calculations decides the kind of the brush less dc motor of which there are two fundamental classes voltage source based drives and current source based drives. Both voltage source and current source based drive utilized with permanent magnet synchronous machine with either sinusoidal or non-sinusoidal back emf waveforms .Machine with sinusoidal back emf (Fig.3.4) might be controlled in order to accomplish almost steady torque. In any case, machine with a non-sinusoidal back emf (Fig.3.5) offer lessens inverter sizes and decreases misfortunes for the same influence level.

Permanent  Magnet  Synchronous Machine piece works either in generator or motor mode. The method of operation is chosen by indication of mechanical torque. On the off chance that indication of mechanical torque is sure it will be in motor mode. In the event that sign is negative it will be in generator mode.

All electrical and mechanical  parts of machine are each represented by second order state space model. Using  following equations block is implemented.

Lobby Effect sensors give the part of data need to synchronize the motor excitation with rotor position keeping in mind the end goal to deliver steady torque. It identifies the change in attractive field. The rotor magnets are utilized as triggers the lobby sensors. A sign molding circuit coordinated with lobby switch gives a TTL-perfect heartbeat with sharp edges. Three lobby sensors are set 120 degree separated are mounted on the stator outline. The lobby sensors computerized signs are utilized to sense the rotor position. A Proportional Integral Derivative controller (PID Controller) is a control input instrument broadly utilized as a part of modern control systems. The PID is most ordinarily utilized criticism controller. A PID controller figures as blunder worth as distinction between a deliberate procedure variable and a sought set point. The controller endeavours to minimize a mistake by conforming the procedure control inputs. The PID controller estimation includes three separate steady parameters, and is likewise now and again called three term control: the relative, the vital and subordinate qualities, signified as P, I and D individually. These qualities can be deciphered as far as time. P relies on upon the present mistake, I on amassing of past blunders and D is forecast of future mistakes, taking into account current rate of progress. The weighted entirety of these three activities is utilized to change the procedure. By tuning the three parameters in PID control calculation, the controller can give control activity intended to particular procedure necessities. The reaction of controller can be portrayed as far as responsiveness of controller to a mistake, how much the controller overshoots the set point and the level of system wavering. Note that utilization of PID calculation for control does not ensure ideal control of system or system security. PID control is an exceptionally helpful strategy utilized as a part of criticism control systems. The mistake created after the correlation between measured sign and the objective sign is relatively duplicated, coordinated and separated and yields of the three administrator are directly summed to produce the sign connected to actuator.

Some applications may require using only one or two actions to provide the appropriate system control. This is achieved by setting the other parameter to zero. A PID controller will be called a PI, PD, P or I controller in absence of respective control actions. PI controller are fairly common, since derivative action is sensitive to measurement noise, whereas the absence of an integral term may prevent the system from reaching target value due to control action.

A high corresponding increase brings about a substantial change in the yield for a given change in blunder. On the off chance that relative addition is too high, the system can get to be flimsy. Conversely, a little pick up results in a little yield reaction to an extensive info blunder, and a less responsive or less touchy controller. On the off chance that a relative increase is too low, the control activity might be too little when comparing to system unsettling influences. Tuning hypothesis and modern practice demonstrate that corresponding term ought to contribute the main part of yield change. Fuzzylogic has quickly gotten to be a standout amongst the best of today\’s innovation for creating advanced control system. With it help complex necessity so might be actualized in amazingly basic, effortlessly stamped and reasonable controllers. The previous couple of years have seen a fast development in number and variety of utilization of fuzzylogic. The application range from buyer items, for example, cameras ,camcorder ,clothes washers and microwave stoves to mechanical procedure control ,medicinal instrumentation ,and choice emotionally supportive network. Numerous basic leadership and critical thinking errands are excessively intricate, making it impossible to be see quantitatively in any case, individuals succeed by utilizing learning that is uncertain as opposed to exact. Fuzzylogic is about the relative significance of exactness .fuzzylogic has two distinct implications in a restricted faculties, fuzzylogic is a coherent system which is an augmentation of multi esteemed logic .yet in more extensive sense fuzzylogic is synonymous with the hypothesis of fuzzy sets . Fuzzy set hypothesis is initially presented by LotfiZadeh in the 1960,s[15] looks like rough thinking in it utilization of surmised data and instability to create choices. A few studies appear, in both re-enactments and exploratory results, that Fuzzy Logic control yields better results with deference than those acquired by ordinary control calculations in this manner, in mechanical hardware the FLC control has turned into an appealing arrangement in controlling the electrical motor drives with extensive parameter varieties like machine instruments and robots. Nevertheless, the FL Controllers outline and tuning procedure is regularly unpredictable in light of the fact that few amounts, for example, participation capacities, control guidelines, info and yield picks up, and so on must be balanced. The configuration procedure of a FLC can be streamlined on the off chance that a portion of the said amounts is acquired from the parameters of a given Proportional-Integral-Derivative controller (PIDC) for the same application.

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