OF PROFESSIONAL ENGINEERING STUDIES Volume V /Issue 5 /SEP 205 DESIGN AND IMPLEMENTATION OF ANTENNA SERVO CONTROL SYSTEM FOR GROUND STATION MS. G. RAJINI M.Tech PE G.NARAYANAMMA INSTITUTE OF TECHNOLOGY AND SCIENCE, Affiliated to JNTUH, Hyderabad, Telangana, India. MR. K. KRUSHNA MURTHY Assistant professor G.NARAYANAMMA INSTITUTE OF TECHNOLOGY AND SCIENCE Affiliated to JNTUH, Hyderabad, Telangana, India. Abstract- This article describes design, modeling and analysis of the antenna servo control system for remote sensing satellite ground station. The mathematical modeling of servo control mechanism is presented. The transient behavior of system using PID controller in time as well in frequency domain is demonstrated. The closed loop system stability conditions verified. As per the total mechanical torque requirement the servo sub-systems are formulated. Accordingly a hardware test set-up is implemented, tested and results exhibited. Further, for better performance of system, fuzzy controller is taken up to produce better performance under low and high speed regions for smooth control. This type of controller (FUZZY) provides better settling time, low peak overshoot and less percent of steady state error in overall system output which leads to better stability of closed loop system. In this article, in addition to hardware test-setup, the performance analysis of the conventional PID controller and fuzzy logic controller has been analyzed with use of Matlab. Index Terms position control loop, PID controller, transient analysis, Fuzzy logic controller, test setup. Fig..Block diagram of the servo control system From block diagram, noted that three are the essential control loops which are required to control, move and follow the target angles. Here, load is Antenna, to control the Antenna, it is necessary to monitor the position, speed and torque demanded by load. Hence, these three controls viz. Speed, Current/ Torque and shaft encoder position. The mathematical representation of complete system comprising three essential loops is as exhibited in figure-2. PID G (s Js + B s I. INTRODUCTION A servo control system is a mechatronics system consists of electrical input, electronics control, produces mechanical output and sensing elements provide position feedback to the control system. This kind of servo control system is one of the most important and widely used forms of electromechanical system for motion control purposes especially in antenna control systems. Such kind of system functional block diagram is as exhibited in figure-. Fig.2. Position control system mathematical representation Where, G v (s) is the gain of the rate loop. The rate loop model is as exhibited in figure-3, below:
OF PROFESSIONAL ENGINEERING STUDIES Volume V /Issue 5 /SEP 205 PID Fig.3. Velocity loop mathematical representation Where: L a = Armature of the inductance = Back emf of the motor = Tachometer constant = Drive ampli ier constant G (s) = Rate loop gain R = Armature resistance = Motor torque constant Gear reducer ratio = Encoder constant J= Antenna inertia B= Coefficient of friction Design Considerations & Formulation: The mechanical forces and torques are estimated and the required mechanical torque is derived to be 308N-m including wind torque, frictional torque and inertial torque. Having estimated total mechanical drive torque, the electrical torque required has to be derived. The electrical torque depends on gearing mechanism engaged between mechanical load (antenna) and electrical motor. Gearing ratio N = (7) Where, m and o are the speed of motor and load, respectively. Now, reflected torque and inertia to the motor can be calculated from load inertia Jo' and torque requirement at the load To' by the following expressions, Jo = ² (8) To = To /Nη(9) Here, efficincy of convertetor is η. These equations were convrted to linear motion form and the total motion required by motor shaft is combination of inertial, frictional and damping torques. The gearing ratio is finalised to be 900: based on the inertia principle between load and servo motor. Further, speed of the electrical motor depends on the speed of the tracking antenna which is followig the satellite target from ground. The drive should supply the peak and rms current supply of the system (Dal Y. Ohm [2006]). I = (0) sl + R Js + Where, Kt = torquecontantofmotor. Therefore, drive should be able to supply the voltage expressed: V = RI + Ke m() R = resistance of motor, Ke = back emf constant of motor, I is required motor peak current and m is maximum speed of motor. Due to the variation of the load and possible overcurrent trip, often it is desirable to use maximum motor speed and peak and rms torques of the motor rating instead of calculated requirement of the system. Therefore, considering all the design parameters, the requirements which are derived and design specifications are consolidated in table-. Table Description Quantitative specification Reflector size 2.7m Beam width 0.8 Total Mechanical torque 308 N-m Gearing Ratio 900: Motor Torque.45N-m Motor speed requirement 8*900/6 = 200 rpm Encoder display resolution 0.00 [5 bit encoder (360 /2 5 - )] Drive switching frequency 8 khz (0 times of machine frequency) Antenna Velocity 20 deg/sec Antenna Acceleration 0.5 deg/sec 2 Design of Servo System: To obtain and represent the servo control loops, the electrical representation of equivalent circuit of servo motor, drive amplifier and antenna were carried and transformed the mathematical representations into S-domain. Further, the design calculations and specifications are used to represent and reduce loop block diagrams. The rate loop block reduction is as given below:
OF PROFESSIONAL ENGINEERING STUDIES Volume V /Issue 5 /SEP 205 G(s) =................... Gain of the position loop = Fig.4.Rate loop block reduction in MATLAB The block diagram will be further reduced to obtain the velocity loop gain/ transfer function. By reducing the blocks the rate loop transfer function of the system expressed below.. = (... ) ( ).. ( ) Gain of the rate loop =... Gv(s) =...... ( ) The velocity loop inside the position loop enhances the system stability. The position loop block reduction with the obtained velocity gain is as exhibited in figure-5 The rate loop block reduction is as given below: G(s) =............ RESULTS AND ANALYSIS The design and simulation results for rate loop and position loops are obtained and exhibited in figure respectively. The results in time domain as well as frequency domains are analyzed. The transient behavior of system is studied, analysis carried out, stability conditions fulfilled and the system is optimized to obtain the desired response. It is very clear from the rate loop step response that the rate loop is having higher bandwidth than position loop, it is good to have higher bandwidth rate loop in point of view of attenuating effect of torque disturbances and less bandwidth of position loop as it encloses the rate loop..2 a m plitu d e 0.8 0.6 0.4 0.2 Fig.5. Position loop reduction block in MATLAB 0 0 0.05 0. 0.5 0.2 Time Fig.6. Step response of rate loop The speed loop incorporated the current loops. The ultimate performance of the servo is decided by the position loop controller. It encloses the speed loop with its output forming speed demand. The position error is computed as the difference between commanded position and measured position. The position feed-back is taken from the encoder by default. In case of fault in the encoder the position loop is closed by the position sensed through resolver. The position error (demand position - actual position) is filtered through a position loop compensator. Such system transfer function is as indicated below. The transfer function is obtained on further reduction of position loop block diagram is as expressed below: amplitude.4.2 0.8 0.6 0.4 0.2 Bode plots: 0-0.2 0 2 3 4 5 6 7 8 9 0 Time Fig.7.Step response of position loop
OF PROFESSIONAL ENGINEERING STUDIES Volume V /Issue 5 /SEP 205 Fig.8. Bode plot response of rate loop Fig.. Hardware setup of the system Fig.9. Bode plot response of position loop Hard ware realization: The response of the motor is observed by giving different inputs to the system are step input, sinusoidal input, and parabolic. In these results it represents the actual position and command position of the motor with respect to the time. The practical implementation of servo control system is accomplished comprising various sub-systems viz., controller, drive amplifier, motor and gear reducer. The complete system is implemented on a test bench setup for testing and verification as designed. Further, PC is connected through Ethernet interface to drive amplifier and controller for accessing, configuring the design specifications and monitoring the system performance. The 24V is utilized for brake release of motor and drive enabling also and 3- supply is used as input to drive amplifier. The realized and executed system interface diagram is as exhibited in figure-5 below: Fig.2. Response of the step input Fig.0.Interface diagram of servo control system The hard ware set up of the control system is implemented which is shown in figure. Fig.3.Response of the sinusoidal input
OF PROFESSIONAL ENGINEERING STUDIES Volume V /Issue 5 /SEP 205 logic. The first step was to decide what the inputs to the system are. Here it is considered two parameters as input. The process of fuzzy inference involves all of the functions that are described in membership functions, logical operations, if-then rules. Fuzzy inference system: Fig.4. Response of the parabolic input Design of the system with Fuzzy logic controller: Fuzzy logic control system is control system which converts the analog inputs in to logical inputs (0, ). Fuzzy logic is a complex mathematical method that allows solving difficult simulated problems with many inputs and output variables. In this FLC, a rule base is defined to control output variables. This Fuzzy rule is a simple IF- THEN rule with some condition and conclusion which relates the input variables to the required output variable properties. A fuzzy logic controller input variables involves receiving the error signal and change of error. These variables evaluate the fuzzy logic control rules using the compositional rules of interference and the appropriately computed control action is determined by using the defuzzification. Fig.6.Mamdani Fuzzy Inference System Developed for Fuzzy Controller Membership function: The figure shows the membership function plots for the first input variable. Triangular membership function is taken for both inputs and outputs. Specify the range then assign the variable name. Then take the second input variable. Again member ship functions are assigned with range. Fig.5. Basic block diagram of fuzzy logic controller From the fuzzy block diagram, the fuzzification matches the input data with the conditions of the rules to determine how the condition of each rule matches that particular input instance. Inference Mechanism is the processing program in a fuzzy control system. The defuzzifications involvesthe reverse process of the fuzzification i.e. the process of converting the fuzzy values to a numerical output value. Rule base consist of a group of rules use several variables both in the condition and the conclusion of the rules. They are based on a set of rules and they follow in identify a problem. Design of the fuzzy controller: Fuzzy inference is the process of formulating the mapping from a given input to an output using fuzzy Fig.7. Membership function of fuzzy controller Rule base: After the inputs are fuzzified, we apply the rules. This Fuzzy rules are in a simple IF-THEN rule with some condition. For example:. If the voltage is L (low) and speed is L (low) then out response not good. 2. If the voltage is G (good) and speed is G (good) then the output response is good. 3. If the voltage is G (good) and speed is L (low) then the output response is average.
OF PROFESSIONAL ENGINEERING STUDIES Volume V /Issue 5 /SEP 205 Step 6.625 Tach.cnst 2 Gain Fuzzy Logic Control ler 0.5 Dri ve.cnst.57*0^-3s+5.6 Motor equ 0.58 Mtr.trq 0.000338s+0.0006272 Inerti a Scope Gain s Integrator Dri ve cnst T achmtr cnst 6.625 Fig.9. Simulink model of a rate loop with Fuzzy The output step response of the rate loop using fuzzy controller is shown in below figure. 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0. 0 0. 0.2 0.3 0.4 0.5 0.6 Fig.20. Step response of the rate loop with FLC The position loop consists of the rate loop and current loop. After simplifying, the position loop of the system using PID with fuzzy controller is designed in SIMULINK. Here the response of the system is improved comparing with PID controller. The SIMULINK model of a position loop using Fuzzy logic controller is shown in the below figure Time Position Loop In Out 5.763*0^-4s 2+3.4578s+.526 4.4406*0^-7s 3+7.4763*0^-4s 2+0.3548s+.526 900 343.77s+80.2 s Fig.8. Rule base of the fuzzy controller Step Ken Subsystem Rate l oop tf Antenna tf Integrator Scope The above figure shows the rule base of the fuzzy logic controller for the three element control system. It consists of rule based using If-and-then rules condition. Simulink model of fuzzy logic controller: After designing of the fuzzy logic controller using required rules and conditions it can be modeled in the Simulink. Here the fuzzy logic controller is used with PID for the precision value by rectifying the errors. The Simulink model of the rate loop of the system using fuzzy controller is shown in figure. Ken Fig.2.Position loop using fuzzy logic controller The step response of the position control using fuzzy logic is shown in below figure
OF PROFESSIONAL ENGINEERING STUDIES Volume V /Issue 5 /SEP 205 Fig.22. Step response of the position loop using fuzzy logic controller Parameters obtained by PID and fuzzy logic controllers Communication Engineering Vol. 3, Issue 6, June 204. [3] P.K. Bhaba Position Tracking Performance Of Ac Servomotor Based On New Modified Repetitive Control Strategy IJRRAS, 0(),January 202 [4] Aziz Ahmad, Amit Kumar Position Control Of Servo Motor Using Sliding Mode Fuzzy Controller International Journal of Advances in Engineering & Technology, July 20. [5] Po-Kuang Chang, Jium-Ming Ziegler-Nichols- Based Intelligent Fuzzy PID Controller Design for Antenna Tracking System Proceeding of IMECS 20 March. [6] A. C. Densmore and V. Jamnejad, A satellitetracking Ku- and Ka-band mobile vehicle antenna system, IEEE Trans. Vehicular Technology, vol. 42, no 4, pp. 502 53, 993 [7] K.Ogata (2009) Modern control engineering, 4th edition, dorlingkindersleypvt. Ltd., India. [8] Modern Control System,byI.J.Nagarath, M.gopal. [9] Analysis and Design of Control systems using matlab byraov.dukkipati CONCLUSION The antenna servo control system design is evolved; methodology presented and design of rate and position control system is demonstrated. Complete electromechanical system is taken up for design and stability analysis purpose. The functional detail of servo control system and transfer function closed loop control system is derived. Simulation analysis of position loop control system is carried out in time domain, frequency domain. Transient behavior of a system is studied with PID controller for Stability of complete system. Further, in view of best linearity and performance a fuzzy controller is implemented in Mat lab and system behavior is studied. A hardware test setup is integrated, interfaces between subsystems are implemented and testing is conducted and results were demonstrated. REFERENCES [] R.Heera Singh and B.C.S.Rao Design And Implementation Of Antenna Control Servo System For Satellite Ground Station Volume 4, Issue 4, July-August (203), pp. 93-00 [2] Mr.N.Sai Pavan, Mr.Ramavenkateswaran.N Modelling Of The Stabilization And Tracking Control System For Antenna International Journal of Advanced Research in Computer and MS.G.RAJINI Completed B.Tech. in Electrical & Electronics Engineering in 203 from SKU, ANANTAPUR,AP and currently pursuing M.Tech in Power electronics and drives from G.Narayanamma Institute of Technology and Science, JNTUH, Hyderabad, Telangana, India. Area of interest includes power electronics, control systems, power systems. Email id:rajrocks900@gmail.com MR.K.KRUSHNA MURTHY Assistant professor in dept of Electrical& Electronics Engineering, at G.Narayanamma Institute of Technology and Science Hyderabad. He received B.Tech degree from Vaagdevi College of Engineering, Warangal. He received M.Tech (Power Systems) Degree from JNTUH, Telangana. Area of interest includes Advanced Load Flow Study and Power Quality. Email id:kkm_220@yahoo.com