Modeling And Pid Cascade Control For Uav Type Quadrotor

Similar documents
Design of Self-tuning PID Controller Parameters Using Fuzzy Logic Controller for Quad-rotor Helicopter

Controlling of Quadrotor UAV Using a Fuzzy System for Tuning the PID Gains in Hovering Mode

QUADROTOR STABILITY USING PID JULKIFLI BIN AWANG BESAR

QUADROTOR ROLL AND PITCH STABILIZATION USING SYSTEM IDENTIFICATION BASED REDESIGN OF EMPIRICAL CONTROLLERS

Control System Design for Tricopter using Filters and PID controller

OPTIMAL AND PID CONTROLLER FOR CONTROLLING CAMERA S POSITION IN UNMANNED AERIAL VEHICLES

A 3D Gesture Based Control Mechanism for Quad-copter

Design and Implementation of FPGA Based Quadcopter

Adaptive Fuzzy Control of Quadrotor

Robust Control Design for Rotary Inverted Pendulum Balance

Modeling and Control of a Robot Arm on a Two Wheeled Moving Platform Mert Onkol 1,a, Cosku Kasnakoglu 1,b

Trajectory Tracking and Payload Dropping of an Unmanned Quadrotor Helicopter Based on GS-PID and Backstepping Control

Segway Robot Designing And Simulating, Using BELBIC

A New Perspective to Altitude Acquire-and- Hold for Fixed Wing UAVs

Active Fault Tolerant Control of Quad-Rotor Helicopter

Teleoperation of a Tail-Sitter VTOL UAV

A Mini UAV for security environmental monitoring and surveillance: telemetry data analysis

Hopper Spacecraft Simulator. Billy Hau and Brian Wisniewski

Modelling and Implementation of PID Control for Balancing of an Inverted Pendulum

Embedded Control Project -Iterative learning control for

Experimental Study of Autonomous Target Pursuit with a Micro Fixed Wing Aircraft

Construction and signal filtering in Quadrotor

Investigations of Fuzzy Logic Controller for Sensorless Switched Reluctance Motor Drive

Frequency-Domain System Identification and Simulation of a Quadrotor Controller

The Mathematics of the Stewart Platform

Performance Analysis of Boost Converter Using Fuzzy Logic and PID Controller

Auto-Balancing Two Wheeled Inverted Pendulum Robot

Design of Attitude Control System for Quadrotor

Modeling & Simulation of PMSM Drives with Fuzzy Logic Controller

SELF-BALANCING MOBILE ROBOT TILTER

Glossary of terms. Short explanation

Negative Output Multiple Lift-Push-Pull Switched Capacitor for Automotive Applications by Using Soft Switching Technique

Introducing the Quadrotor Flying Robot

FUZZY CONTROL FOR THE KADET SENIOR RADIOCONTROLLED AIRPLANE

Classical Control Based Autopilot Design Using PC/104

AIRCRAFT CONTROL AND SIMULATION

A Searching Analyses for Best PID Tuning Method for CNC Servo Drive

The Next Generation Design of Autonomous MAV Flight Control System SmartAP

Jurnal Teknologi IMPROVEMENT OF QUADROTOR PERFORMANCE WITH FLIGHT CONTROL SYSTEM USING PARTICLE SWARM PROPORTIONAL-INTEGRAL-DERIVATIVE (PS-PID)

Active Vibration Isolation of an Unbalanced Machine Tool Spindle

Reconnaissance micro UAV system

A NEURAL CONTROLLER FOR ON BOARD TRACKING PLATFORM

SELF STABILIZING PLATFORM

드론의제어원리. Professor H.J. Park, Dept. of Mechanical System Design, Seoul National University of Science and Technology.

Modeling and Implementation of Closed Loop PI Controller for 3 Phase to 3 Phase Power Conversion Using Matrix Converter

Artificial Neural Networks based Attitude Controlling of Longitudinal Autopilot for General Aviation Aircraft Nagababu V *1, Imran A 2

ZJU Team Entry for the 2013 AUVSI. International Aerial Robotics Competition

FUZZY LOGIC CONTROL FOR NON-LINEAR MODEL OF THE BALL AND BEAM SYSTEM

An Application of 4-Rotor Unmanned Aerial Vehicle: Stabilization Using PID Controller

Comparative Study of PID and Fuzzy Controllers for Speed Control of DC Motor

Integration Intelligent Estimators to Disturbance Observer to Enhance Robustness of Active Magnetic Bearing Controller

Thrust estimation by fuzzy modeling of coaxial propulsion unit for multirotor UAVs

STUDY OF FIXED WING AIRCRAFT DYNAMICS USING SYSTEM IDENTIFICATION APPROACH

Location Holding System of Quad Rotor Unmanned Aerial Vehicle(UAV) using Laser Guide Beam

Development of an Experimental Testbed for Multiple Vehicles Formation Flight Control

CDS 101/110a: Lecture 8-1 Frequency Domain Design

Penn State Erie, The Behrend College School of Engineering

GPS-based Position Control and Waypoint Navigation System for Quadrocopters

Ball Balancing on a Beam

A Simple Approach on Implementing IMU Sensor Fusion in PID Controller for Stabilizing Quadrotor Flight Control

ROBOTICS ENG YOUSEF A. SHATNAWI INTRODUCTION

EMBEDDED ONBOARD CONTROL OF A QUADROTOR AERIAL VEHICLE 5

Digital Control of MS-150 Modular Position Servo System

Comparative Analysis of PID, SMC, SMC with PID Controller for Speed Control of DC Motor

Small Unmanned Aerial Vehicle Simulation Research

Comparisons of Different Controller for Position Tracking of DC Servo Motor

A Machine Tool Controller using Cascaded Servo Loops and Multiple Feedback Sensors per Axis

Development of Fuzzy Logic Controller for Quanser Bench-Top Helicopter

DESIGN & FABRICATION OF UAV FOR DATA TRANSMISSION. Department of ME, CUET, Bangladesh

TEAM AERO-I TEAM AERO-I JOURNAL PAPER DELHI TECHNOLOGICAL UNIVERSITY Journal paper for IARC 2014

GPS System Design and Control Modeling. Chua Shyan Jin, Ronald. Assoc. Prof Gerard Leng. Aeronautical Engineering Group, NUS

A Fuzzy Sliding Mode Controller for a Field-Oriented Induction Motor Drive

Modeling Position Tracking System with Stepper Motor

Actuators. EECS461, Lecture 5, updated September 16,

Analysis and Design of Conventional Controller for Speed Control of DC Motor -A MATLAB Approach

DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING BANGLADESH UNIVERSITY OF ENGINEERING & TECHNOLOGY EEE 402 : CONTROL SYSTEMS SESSIONAL

Speed Control of DC Motor Using Fuzzy Logic Application

A Do-and-See Approach for Learning Mechatronics Concepts

Mobile Robots (Wheeled) (Take class notes)

Vibration Control of Flexible Spacecraft Using Adaptive Controller.

302 VIBROENGINEERING. JOURNAL OF VIBROENGINEERING. MARCH VOLUME 15, ISSUE 1. ISSN

Mechatronics 19 (2009) Contents lists available at ScienceDirect. Mechatronics. journal homepage:

SIMULINK MODELING OF FUZZY CONTROLLER FOR CANE LEVEL CONTROLLING

Active sway control of a gantry crane using hybrid input shaping and PID control schemes

OughtToPilot. Project Report of Submission PC128 to 2008 Propeller Design Contest. Jason Edelberg

Design of A Closed Loop Speed Control For BLDC Motor

AUTOMATIC VOLTAGE REGULATOR AND AUTOMATIC LOAD FREQUENCY CONTROL IN TWO-AREA POWER SYSTEM

Modeling of Electro Mechanical Actuator with Inner Loop controller

Robot Joint Angle Control Based on Self Resonance Cancellation Using Double Encoders

Comparative Analysis of Air Conditioning System Using PID and Neural Network Controller

DATA ACQUISITION SYSTEM & VISUAL SURVEILLANCE AT REMOTE LOCATIONS USING QUAD COPTER

ANALYSIS OF V/f CONTROL OF INDUCTION MOTOR USING CONVENTIONAL CONTROLLERS AND FUZZY LOGIC CONTROLLER

Tuning Methods of PID Controller for DC Motor Speed Control

CURRENT FOLLOWER APPROACH BASED PI AND FUZZY LOGIC CONTROLLERS FOR BLDC MOTOR DRIVE SYSTEM FED FROM CUK CONVERTER

Fuzzy Logic Based Speed Control System Comparative Study

Optimal Control System Design

Position Control of a Hydraulic Servo System using PID Control

Estimation and Control of a Tilt-Quadrotor Attitude

DC Motor Control using Fuzzy Logic Controller for Input to Five Bar Planar Mechanism

Haptic Collision Avoidance for a Remotely Operated Quadrotor UAV in Indoor Environments

Transcription:

IOSR Journal of Dental and Medical Sciences (IOSR-JDMS) e-issn: 2279-0853, p-issn: 2279-0861.Volume 15, Issue 8 Ver. IX (August. 2016), PP 52-58 www.iosrjournals.org Modeling And Pid Cascade Control For Uav Type Quadrotor Renuka Ramkishan Choudhari 1, Subhash.S. Sankeshwari 2. 1.Department Of Electrical Engineering, MBES College Of Engineering Ambejogai, India 2. Department Of Electrical Engineering, MBES College Of Engineering Ambejogai, India Abstract: This paper present the mathematical model of UAV type Quadrotor under the Newton-Euler formulation. A transfer function has been chosen which represents a brushless motor and its driver as one system. PID cascade control has been designed to solve the path tracking problem for quadrotor. The controller is evaluated in a 3D environment in simulink. Keyword: Cascade controller, PID controller, Quadrotor, UAV. I. Introduction Quadrotor is multirotor helicopter, which is also known as quadcopter. The most recent design of quadrotor is Unmanned Aerial Vehicle (UAV). A four rotor helicopter was firstly designed by Louis Breguet. In the year of 1920. Some of the groups have developed their own platform for UAV. Such as, Dragan- Flyer, the X-UFO and the MD4-200. Quadrotor is useful tool for researchers to test and evaluate new ideas in number of different fields. Including flight control theory, navigation, real time system and robotics. UAV type quadrotor are also applicable for agriculture and film production. There are numerous advantages using quadrotor as a versatile test platforms. They are relatively cheap and available in variety of sizes, simple control mechanism, highly manuarable, and has potential to hover and take off, fly and land in small areas. The most challenging part for the new generation, is to achieve greater performance. The various control techniques used for modeling and controlling of quadrotor such as LQR method, control of UAV using sliding mode control, Fuzzy controller, PID controller. In this paper we concentrate on stabilization problem of quadrotor in presence of actuator and sensor fault is considered. The dynamic describing the quadrotor parameters, which affect the dynamic of flying structure. The cascade control mechanism is used in this paper to achieve improved performance and reduce adverse effect. The main aim of this paper is to examine the effectiveness of designed attitude control with different type of PID controller.[1]. The paper is organized as follows, first the mathematical model of UAV type quadrotor is described. Second part presents the general structure of cascade control system and investigation of two type of PID controller with modified loop structure. This section include description of Type-A PID controller and Type-B PID controller. II. Quadrotor model The Structure of UAV type Quadrotor is simple one. Basically comprising of four rotors attached at the end of a symmetric cross. The main features that should be taken in such a structure are symmetry and rigidity. To avoid unstable flight structure should be as rigid as possible. The best way to achieve this is through use of lightweight alloys or composites. Figure 1. Quadrotor Thrust aerial vehicle DOI: 10.9790/0853-1508095258 www.iosrjournals.org 52 Page

The two pair of propeller as shown in figure1, (1,3) and (2,4) rotates in apposite direction.the pair (1,3) rotates clockwise and remaining pair (2,4) rotates anticlockwise. This combination of rotation produce apposite torque. This results propellers generate vertical lifting force upward which raises quadrotor body in the air and it can moves in pitch, roll, yaw, hover, take off and landing. Pitch and roll movement can be achieved by altering the speed of any one pair of motor. while other motor pair speed remain constant. Yaw movement can be achieved by altering the speed of both motor pairs in quadrotor. III. Mathematical model The UAV type quadrotor is six degree of freedom system. X=[φ,θ,ψ,x,y,z,φ, θ, ψ, x, y, z ] (1) U=[u 1, u 2, u 3, u 4 ]. where u i - control input (2) i = 1,2,3,4 - motor input. 2 u 1 = b (ω 1 + ω 2 2 2 + ω 3 + ω 2 4 ) u 2 = b (-ω 2 2 + ω 2 4 ) u 3 = b (ω 2 1 - ω 2 3 ) u 4 = d(- ω 2 1 + ω 2 2 - ω 2 3 + ω 2 4 ) The relation between the kinetic energy and potential energy is represented by Lagrange equation L=D k -P (3) F= d dt L X L X where; L is Lagrangian, D k is Kinetic energy, P is potential energy, X = [ x, y, z, φ, θ, ψ ] T is a vector of generalized coordinates, F=( F E, M) are generalized forces coordinates and moments M applied to the quadrotor due to control input. For translation motion the Lagrange equation has the form: L F E = d dt Ƹ where: Ƹ = [x,y,z] T - Position coordinates sin θ F E = sin φ cos θ. f g cos φ cos θ f g = F 1 + F 2 + F 3 + F 4 2 F i = bω i ω i - Rotor speed, b - Thrust factor The Lagrange equation for rotational motion is represented as follows: T= d dt L η L Ƹ - L η Where: η = [φ, θ, ψ] T - Euler angles T = [T φ. T θ, T ψ ] T T φ = bl (ω 4 2 - ω 2 2 ) - I r θ (ω 1 + ω 3 + ω 2 - ω 4 ) T θ = bl (ω 3 2 - ω 1 2 ) + I r φ (ω 1 + ω 3 + ω 2 - ω 4 ) T ψ =d(ω 1 2 - ω 2 2 + ω 3 2 - ω 4 2 ) Above equation T φ T θ T ψ consist of action of thrust forces difference of each pair. The quadrotor dynamic model with X,Y,Z motion as consequence of pitch, roll and yaw rotation is as follows. θ = 1 (I Ixx xx -I zz ) s(θ) c(θ) -φ ψ I zz c(θ) +T θ ) (7) 1 φ = zz Iyy (1+s2(θ)) s(θ )- θ φ c(θ) s(θ) (8) (2I zz -2I yy )-θ ψ c(θ)+t φ ) ψ= 1 zz s(θ)+t Izz ψ ) (9) (10) y. m= -f g c(θ)s(φ) (11) z.m + g = f g c(θ) c(φ) (12) where: c and s are abbreviations of 'sin' and 'cos', I xx, I yy, I zz are inertia moments. (4) (5) (6) DOI: 10.9790/0853-1508095258 www.iosrjournals.org 53 Page

IV. Control Scheme PID controller has been applied for attitude control of UAV type quadrotor. The PID controller is applied to regulate both position and orientation (angular momentum) of quadrotor. The performance of PID controller indicate good attitude stabilization. The time response is good, with almost zero steady state error in order to achieve better performance and reduce external disturbance. The cascade controller consist of two loops inner loop and outer loop. Figure 2: Cascade controller The geometry of this block diagram as shown in figure 2 defines inner loop involving secondary controller and outer loop involving primary controller. The inner loop function like a traditional feedback control with set point, a system variable and controller acting on system by means of actuator. In this paper cascade controller perform control task as an angular stabilization. The angular velocity of rotating platforms are additional measurement that can be used in inner loop. The outer loop is based on Euler angles. The block diagram of cascade control for UAV type quadrotor is as shown in figure2. In both loop three type of PID controllers are considered. 1) Type-A PID Controller In control theory PID controller is represented in continues time domain is u(t)= k p e(t) + k i t 0 e t dt + k d de (t) dt where; k p is proportional gain, k i is integral gain and k d is derivative gain. Type-A PID controller consist of proportional gain, integral gain, derivative gain. Block diagram of PID controller is shown in figure 3 Figure 3: Type-A PID Controller DOI: 10.9790/0853-1508095258 www.iosrjournals.org 54 Page

2) Type-B PID Controller The process of setting the optimal gain to get ideal response from control system is known as tuning of PID controller. In most practical control system very small derivative term is used, because derivative response is highly sensitive to noise in variables. Therefore in type-b PID controller, we minimize the derivative gain. Figure 4 represents the block diagram of Type-B PID controller. The mathematical equation for Type-B PID controller is; t 0 u(t)=k p e(t) + k i e t dt - k d Figure4:Type-B PID controller dy (t) dt In general increasing k p, speed of control system increases. The integral term response will be continually increasing unless error is zero. Therefore the PID controller with minimum value of k d gives good results, as compare to Type-A PID controller. 3) Type-C PID controller Mathematical equation for Type-C PID controller is as follows: u(t)= -k p y(t) + k i e( t)dt k 0 d Block diagram for Type C PID controller is t dy (t) dt Figure 5 : Type C PID Controller DOI: 10.9790/0853-1508095258 www.iosrjournals.org 55 Page

V. Simulation Results In this section we present the simulation results which are conducted to evaluate performance of designed attitude control system in cascade structure with different type of PID controller. In design process we consider two type of PID controller optimizing the parameters in view of the assumed reference model. Feedback data for regulators are six variables: Euler angles θ, ψ, φ (outer loop), angular velocities θ, ψ, φ (inner loop). Control signals are motor input u 1, u 2, u 3, u 4. Type- A Results Figure 6: Quadrotor 3D path Figure 7: Motion in XYZ plane Figure 8: Error response Type B Results Figure 9: Motion in xyz plane Figure 10: Quadrotor 3D path DOI: 10.9790/0853-1508095258 www.iosrjournals.org 56 Page

Figure 11: Roll angle Response Figure 12: Pitch angle Response Figure 13: Yaw angle response Type-C results Figure14 Quadrotor 3D path Figure 15: Motion in xyz plane Figure 16: Roll angle response Figure 17: Pitch angle response DOI: 10.9790/0853-1508095258 www.iosrjournals.org 57 Page

VI. Conclusion In this paper the three approaches of PID controller are considered to the problem of attitude control of UAV type Quadrotor. Main goal of this research is to achieve the angular response for different approaches of PID controller. Three architecture are presented and examined with best performance. All the reviewed architecture of controller resulted in almost same output response. The application of cascade control structure gives the possibility to adapts the simple PID algorithm for controlling complex system, such as vertical take-off and landing platforms. As PID controller gives steady state error zero, so the system becomes more stable. Angular stabilization is obtained by using PID controller for UAV type quadrotor References [1]. H.L. Wade, "Basic and advanced regulatory control system design and application," ISA, United state of America, 2004 [2]. S. Bouabdallah, A Noth, and R. Siegwart, PID vs LQ Control Techniques applied to an indoor micro Quadrotor, Proc. Of Int. Conf. On intelligent Robot and Systems, Japan, 2004. [3]. A. Tayebi and S.McGilvray, "attitude stabilization of a VOLT quadrotor aircraft", IEEE trans. on control system technology, vol. 14, no. 3, 2006, pp. 562-571 [4]. K.P Valavanis, advances in Unmanned Aerial Vehicles. The Netherland: Springer-Verlag, 2007. [5]. P. Lindahl, E. Moog and S.R. Shaw, Simulation design and validation of UAV propulsion system. 2009. [6]. R. Goel, S. M. Shah, N.K. Gupta, N. Ananthkrishnan, 2009. Modelling, Simulation and flight of an Autonomous Quadrotor. Proceeding of ICEAE. [7]. Hongning Hou. Jian Zhuag, Hu Xia,Guanwei wang and Dehong Yu."A simple control of UAV type Quadrotor" in Mechatronics and automation (ICMA), 2010. [8]. Farid Kendoul. Survey of advance in guidance, navigation and control of unmanned rotorcraftsystem. Journal field robotics 29 (2),2012 DOI: 10.9790/0853-1508095258 www.iosrjournals.org 58 Page