Real-Time Acceleration Control using Bluetooth Mobile App

Using Arduino mega 2560, stepper motors and sensors

Venkatesh PrasadUIN: 124003455

Electrical and Computer Engineering Departmentvenkateshprasad13@gmail.com

Divya AnbalaganUIN: 224003354

Electrical and Computer Engineering Departmentdivyaanbalagan7@gmail.com

Lance Alpuerto UIN: 423004329

Electrical and Computer Engineering DepartmentLanceg90@tamu.edu

Abstract — This document illustrates the real-time control of a stepper-motor driven robot, which is fed acceleration input from a Bluetooth device (a mobile phone). The action of RT controller is used to generate error signals from the actual acceleration – data that is collected using an accelerometer. The ultrasonic sensor is used for distance measurement and obstacle detection, which causes the robot to either speed up (absence of obstacle) or slow down (presence of obstacle).

Keywords—Acceleration control, Ultrasonic sensors, Accelerometer, Real time controller for stepper motor system, Sensors&Actuators, Bluetooth modules.

I. OBJECTIVE AND SIGNIFICANCE

The purpose of this project is to have a deeper understanding of the fundamentals of control systems and the entire plant that it controls. The automated acceleration control system will allow remote setting of distance and speed to determine positive and negative acceleration characteristics needed, given no load description. The two sensors used – ultrasonic and accelerometer – provide critical data about the position and velocity of the robot, and any objects obstructing its path. In the control system, the proportional and integral gains are set upon modeling the plant. These values are continuously updated within the real-time control loop based on the error of the readings. The device will be able to recognize and adjust to any slippage of the wheels at any point and adjust the torque produced by the motor for steady movement. Finally, the BT application allows the user to provide the acceleration (distance??) set-point. The robot is then intelligent enough to perform obstacle-detection to make sure collisions are avoided.

The significance of the project lies in the realization of a complete closed-loop design of a system using sensors, actuators, digital logic and microcontroller. By doing a real-time acceleration control, safe speeds and minimum braking distances for moving objects such as cars can be ascertained. In the field of autonomous vehicles, control through BT is an added feature.

II. ENGINEERING DRAWINGS FOR FINAL DESIGN A. Robot Modeling and 3D Fabrication

One of the new technologies implemented in our project was the use of 3-D printing to create the robot body. Instead of procuring the parts as commercial-off-the-shelf, it was built from scratch using Sketchup and converting it to a .STL file. It was then printed overnight (~9 hours), the material used was ABS.

Prior to building the bot body, calculations were done depending on the parts needed. Space requirements were estimated to mount the required devices. The main considerations were made with respect to the following:

1. Stepper motor + Motor Drivers2. 3 Nos. of 9V Batteries 3. Space for BT module, accelerometer, ultrasonic sensor and the Arduino microcontroller

Figure 1 Stepper Motor 42M100B2U Figure 2 9Vx3 Batteries

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Once the required dimensions were ascertained, the 3D model was built on Sketchup. Shown below are the lateral and top views of the 3D model. As can be observed, holes were included next to the motor to ensure it can screwed on to the bot body.

Figure 3 3D View Figure 4 Top View

B. Controller Diagram

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Set values (Ad, Sd, Df)

Run Calculations

Begin?

Acceleratea(t) at t=0

Initialize timers(place A, S, & D

eqs.)

Monitor G(t) (ΔOCR, a(t), v(t))

Calculate Safe Distance in Loop

Is dis

tance>safe_distance?

Accelerate ++a(t)

Decelerate - -a(t)

CONTINUE

START

Yes No

III. INTEGRATION OF ALL COMPONENTS

A. Stepper Motor + Motor Driver

Stepper motors are used instead of DC motors as they provide a better control of motion. 42M100B2U is the motor used, and in order to drive this motor, the L298 dual full-bridge driver is used.

B. Battery Sizing

Once the mechanical part of the design was done, batteries were selected depending on the current drawn, motor voltage rating and size. Since the motors are rated at 12V, a battery with voltage greater than that was selected. Also, the current drawn by the motors are approx. 100-200mA. One of the issues we faced was the amount of power consumed by the motors. The Ah ratings of the batteries sufficed even though we did not use the larger 12V batteries. The smaller batteries were selected as they are a reduced payload that do not occupy too much space.

Battery Specs: 03 x 9V, 4700mAh, Alkaline

C. Ultransonic Ranging Sensor

The HC - SR04 is used for object detection and distance measurement. The specifications of the sensor outlined its principle of working. Using two pins, the Trigger and pulse width of Echo, distance calculations are done. This was preferred over IR sensors as they can detect better in substandard lighting conditions.

D. Digital Accelerometer

The accelerometer is used to provide the real-time actual rate at which the robot is accelerating. Using this data, and the data that is input from the BT module, the controller calculates the error. The accelerometer we had initially selected was an analog device, however, the resolution was not small enough to capture the small changes in acceleration.

Accelerometer Specs: LSM303DLH 3-axis accelerometer and 3-axis magnetometer

E. Bluetooth Module

The BT module connects to the Arduino via Serial1 (TX1 RX1). It is enabled to take commands from the mobile application, which feeds it with the acceleration values. For this project, additionally, the BT module was used to read serial data (accelerometer, distance, acceleration readings) onto the phone and stored as BT logs. The code written to interface the BT module with any mobile device is attached in Appendix B.

IV. PROCEDURE

Highlighted below is the general step-by-step approach to building the project. Further explanation is given in Appendix B which contains the final code implemented.

Step 1: Designing the mechanical structure

As described above, the robot was built by 3D printing and all the components were mounted on it. 4 | P a g e

Step 2: Testing all the componentsThis process was time consuming as each component had to be tested and calibrated before it could be integrated using the Arduino. The following are described in brief:

a) BTThe BT module transmits and receives data from the Arduino. This is then controlled by an app. Fill this!!

b) MotorsThe 2 motors were tested once connected to the L298 drivers. They are connected to run in the bipolar mode, thus, the motor excitation sequence was: 1010, 1001, 0101, 0110. Functions are written in the code which initialize the motors and control them to run at commanded speeds. Initially, the inbuilt Stepper.h and AccelStepper.h libraries were used for speed and acceleration control, however, writing directly into the pins gave a better control of the delay between the steps. Timer4 of the Arduino is used for all control purposes – the registers of Timer4 were used for speed and acceleration control by modifying registers such as TCCRxA/B , OCRxA/B, TIMSKx. The Output Compare Register was crucial to determining the velocity of the bot’s operation. And its rate of change in turn, determines the acceleration. Every time the overflow is detected, a step change occurs in the motor. This is calculated as shown:Arduino’s timer frequency = 16MHzPrescaler = 1024So, every tick would correspond to 64μsThus, setting the value of the OCR to, say, 255 16.32ms. This value is the time taken for each step of the motor. Thus, it is seen that the varying OCR value can control the step time, consequently controlling the motor speed.

c) Ultrasonic SensorThe ping is the wave that is transmitted and the echo is the received wave. Timer1 is used to control the sensor. The timer is initialized to a certain value, and at each loop of the specified time, the ISR to calculate the echo duration is called. This duration which is the difference in time between the time the ping is sent out and an echo is received, is then used to calculate the distance at which an object is located.

d) AccelerometerThe digital raw readings from the accelerometer need to be converted to linear acceleration data. This was one of the most challenging aspects of the project. The issue with the initially used analog accelerometer was that it was not sensitive enough to detect changes of acceleration in the bot. However, the digital accelerometer was too sensitive and even the slightest vibration in any of the 3 axes would lead to spillage and error in the other axes. Thus, a filter was implemented. Being digital data, RC filters were not used, instead digital code was used for data sampling and smoothing out the noisy values. The code provides a certain period of time (~10seconds) for sensor calibration wherein the offsets are calibrated and a zero value is calculated.Once the values are read, the conversion is done by using:16-bit digital data 216 corresponds to ±2g (the sensitivity of the sensor selected)Thus, each bit of data corresponds to 0.05981 cm/s2.

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Step 3: Writing and integrating the above with the closed-loop controller Using a Proportional Integral (PI) controller the acceleration of the automated car was directed. The proportional controller was used to stabilized the otherwise unstable motor. This controller will decrease the steady state error as we increase the gain constant (kp). Although kp will decrease the systems steady state error, it will also increase the dynamics, therefore gain of the noise. An additional control technique was used to further reduce error. The integration controller was used to minimize the steady state error. For any desired velocity achieved by the motor through the acceleration profile, the error will be reduced. The data received from the accelerometer was used as for unity gain feedback. The difference in the measured data and the designated acceleration command was found. Once the error was found, a proportional controlling constant (kp) was applied. In addition, an integration of the acceleration was determined by the previous error plus the integrated term of the present error. The use of these two coefficients allowed the automated car to produce reasonable control from the reference to the output. The full system block diagram is shown under part II-B

V. EXPERIMENTAL RESULTS The results were observed real-time and the outputs were recorded. The following screenshots show the variation of the accelerometer readings when the robot detects a change in speed. What is displayed in Fig. shows the peaks that correspond to the instants when the bot undergoes a change in speed before and after the filter is applied. Fig. indicates the output at the serial monitor – as described above the OCR value varies in order to change the speed. When an obstacle is detected within a range of ~25-30cm, the bot decelerates and this is observed in the increased OCR value. Lastly, Fig. is a snapshot of a phone screen which has the BT app installed on it. It continuously streams data from the controller while also allowing the user to select the desired acceleration.

Distance from Obstacle: 30New OCR: 900Distance from Obstacle: 28New OCR: 900Distance from Obstacle: 28New OCR: 940Distance from Obstacle: 28New OCR: 940Distance from Obstacle: 24New OCR: 940Distance from Obstacle: 24New OCR: 940Distance from Obstacle: 24New OCR: 980Distance from Obstacle: 24New OCR: 980 Figure 5 Serial Monitor Output Figure 6 BT Phone App

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Figure 7 Accelerometer Readings Before & After Filter

VI. DISCUSSION AND CONCLUSIONS

Some important points to note in the creation of this project would be as follows:1. Body design must house all necessary components for autonomous control.2. Determining load torque requirements 3. Sizing motors for desired motor torque4. Battery sizing to provide for all components 5. Blue tooth connectivity for mobile-wireless initialization6. Obstacle tracking and avoidance procedures using an ultrasonic sensor7. Command acceleration implementation8. Control system for tracking command reference given9. Frequency of error iterations for optimized control10. Internal Service Routine guidelines and implementation11. Delay timing and corrections

Several conclusions were arrived to in this process: 1. The external torque load of the system is of main importance when designing the system.

a. It is necessary to account for all power drawn from the total system in order to appropriately size the system with a source. If not well designed, the extra torque needed for an additional source could exceed the torque available.

2. When using multiple sensors, it is necessary to efficiently use them in tandem to produce a muli-variable controlled system.

a. The delay times and corrections need to be assessed here in length in order for smooth and stable implementation.

3. Filtering is necessary when using any feedback system because noise, when damping is significantly difficult, will be present in the corrections and therefore reducing the tracking and amplifying the instability as the control technique is implemented.

4. The control coefficients can be determined with a model and observed estimation of the system with the state space analysis, LQI, or LQR. Although possible, the model is inefficient when not accounting for all much of the disturbance seen by controlling sensors.

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APPENDIX A CODE

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