A Simulation of Artificially Intelligent Flexible Pole Cart using Dev C++ Engr. Edgar Caburatan Carrillo II, Dr. Elmer P. Dadios College of Engineering, De La Salle University 2401 Taft Avenue, 1004 Manila, Philippines edgar_carrillo@dlsu.ph, elmer.dadios@dlsu.edu.ph Abstract— Artificial intelligence has many applications today. It can be used in different fields like robotics, and motion program. One of the motion problems is flexible pole cart. This study is making a simulation of flexible port cart balance. Flexible port cart can be interpreted as inverted pendulum[1]. The dynamics of the system was established already[1] and a computer simulation using dev c++ was used as program simulator. For the flexible pole cart program, it started with the user inputting whether the pole is rigid or elastic. After inputting its pole characteristic, the user is then asked to input data for the pole characteristic. For rigid pole, 13 inputs are required and for elastic pole, 10 inputs were required. The result of the inputs will be 5 outputs like time, distance, velocity, acceleration, pole angle, rigid pole angle and force. After the data were computed using the program, a simulation of distance vs. time, velocity vs. time, acceleration vs time, pole angle vs time, elastic pole angle vs. time and force vs time was shown. As a result of simulation, the graph states that it is a sin function. Keywords— Artificial intelligence , Simulation, C++, Flexible pole cart I. INTRODUCTION Since 1970's, flexible beams have been a topic of research in the field of robotics[2] and artificial intelligence [25, 26, 27, 28, 30]. This researches [3, 4, 5, 6, 7, 8] created an impact in increasing control and operational efficiency of systems [9, 10, 11, 34] . Flexible systems are applied in robotics and intelligent systems provide advantages compared to its rigid counterparts. Among them are the moving of larger payloads without increasing the mass of the linkages, requirements for less material and smaller actuators, less link weight, less power consumption, and the machines are more manoeuvrable and transportable[30]. Flexible robot manipulators[35, 37] are not presently used in production industries because robot manipulators are required to have a reasonable accuracy in the response of the manipulator end-effector to the input command from its control system. There were experiments and studies described [2, 13, 14] to control the system but first a simulation of its dynamics was needed. It started with the derivation of the dynamic behavior of the system and after it is a computer simulation. Computer simulation is necessary to evaluate whether the derived dynamics of the system are correct. It is therefore most appropriate to study analogues of such systems. The flexible pole-cart system provides such an analogue[1]. This presents a rule based control system for the flexible pole-cart balancing problem (the inverted pendulum using an elastic pole) that operates on a simulation of the system. The task of this system is to balance an elastic pole that is hinged on a movable cart. It is assumed that the hinge is frictionless. The cart is allowed to move along a track with limited length and that has friction. Forces of different magnitude are applied to the cart in either a left or right direction. The initial angle of the pole can be varied up to 30 degrees. This is more difficult than the conventional rigid pole-cart system because of the complexity in its dynamics. The deflection of the elastic pole gives additional degrees of freedom to this system. A computer simulation of the use of the cart to balance a flexible pole under first mode of vibration is presented here[36, 37]. The dynamic equations of the system were derived using Newton’s laws, Bernoulli-Euler analysis, and beam theories. The system was analyzed with the presence of friction. Numerical integration using fourth order Runge- Kutta was conducted [15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 33]. Results on the analysis of the behavior of the system under various conditions has also been obtained in order to explore the practicality of attempting to control such a system[1]. The system can help simulate the elastic and rigid pole in the flexible pole cart. The simulation was able to solve highly nonlinear system of flexible pole cart. As part of its feature, it can print data results of simulation and also it was able to graph the input data. An artificially intelligent program will make it possible for a machine or system to behave in a human way. For a machine to be artificially intelligent, it must know how to do the right or correct thing[1]. A. Flexible pole cart dynamics of the system The derivation of the program was based on the dynamics of the system. It started with basic 2 nd law of newton, F=ma. It's free body diagram was determined together with the derivation of the standard dynamics equation for pole angle,pole velocity,pole acceleration, cart velocity and cart acceleration for both rigid and elastic pole[1,29,31,32].