CHAPTER II
LITERATURE REVIEW
In this chapter, discussion about the basic concept of inverted pendulum system and FLC used for inverted pendulum system will be presented. It will consist
of detail explanation about the model, control approach, results and analysis.
2.1 Literature Review
The Switching Control for Inverted Pendulum System Based on Energy Modification. [1] It is based on a modified energy such that the potential energy is
minimums in the upright position. This method of controlling the inverted pendulum system has been derived by paying attention to the energy of pendulum. The model
of this inverted pendulum is proposed where there is a mass situated at the centre of the pendulum’s pole and the cart dose not has wheels. The equation of motion is
derived by concerning the moment of inertia with respect to the pivot point, the mass of the pole, the distance from the pivot to the centre of mass, the acceleration of
gravity, the acceleration of the pivot and the angle between the vertical and the pendulum.
After considering the system with damping and how to control a system with damping is figured out, a simulation is performed and the switching conditions were
lead and the control parameters were shown.
Inverted pendulum system with the personified intelligent control which is not based on the accurate mathematical model is presented. [2] It used a method that
can develop control laws directly by means of qualitative analysis and synthesis of the plant. The inverted pendulum system is a multiinput singleoutput control
system consisting of four inputs; pole angle, change of the pole angle, cart position and change of cart position and single output; control action. The prerequisite of
applying this control is to understand the physical structure and behaviour of the controlled object as fully as possible. The model for this control is the inverted cart
pendulum situated on a rail and driven by a single motor. The analysis done by reduction of primary problem until small problems that can be solve. Then, the
equations obtained will be programmed in C language and the output can be seen from the graph obtained.
The fuzzy logic controller for an inverted pendulum system does not require a precise mathematical modelling of the system nor complex computations. [3]
Fuzzy control provides an easy solution to this problem as it is shown by the derivation of the fuzzy linguistic rules and its function verified by computer
simulations. From this model of inverted pendulum system, the pendulum’s cart receives an external force for balancing the pendulum provided by a permanent
magnet servomotor mounted on the cart. The fuzzy logic controller changes the human language to fuzzy language before it makes decision to control the system
and back to human language for further control action.
A RuleBased Neural Controller for inverted pendulum system is presented. It demonstrates how a heuristic neural control approach can be used to solve a
complex nonlinear control problem. [4] As well as to swing up the pendulum, the controller is also required to bring the cart back to the origin of the track.
Specializing to the pendulum problem, the global control task is decomposed into subtasks, namely, pendulum positioning and cart positioning. Accordingly, three
separate neural subcontrollers are designed to cater to the subtasks and their coordination. The simulation result is provided to show the actual performance of the
controller. The advantage of this controller is it is able to implement dynamical decisions and rules than just the static mapping actions. The simulation and analysis
of the neural controller for the inverted pendulum system is done on a DECstation using the software package Matlab.
Fuzzy Logic Controller for an Inverted Pendulum System was discussed about the designing Fuzzy Logic Controller for Inverted Pendulum System. [5] The
case of fuzzy logic for the derivation of a practical control scheme for stabilizing the inverted pendulum was presented in this paper. The Fuzzy Logic Controller required
only sensing the pole angular and cart position, and the implementation is simple. In addition, the comparison of Fuzzy Logic Controller and conventional controller
PID was discussed too. In the end of this paper, the Fuzzy Logic Controller is ease for implementation of this type of system and the best performance compare the
conventional controller PID.
Fuzzy Logic Control of Vehicle Suspensions with Dry Friction Nonlinearity is about designing and investigating the performance of Fuzzy Logic Controller
active suspensions on a linear vehicle model with for degrees of freedom without any degeneration in suspension working limits. [6] This article is approach to new linear
combinations of the vertical velocities of the suspension ends as input variable. The effectiveness of the Fuzzy Logic Controller for active suspension system was
discussed too. Decreasing the amplitudes of vehicle body vibration improves ride comfort. In addition, body bounce and pitch motion of the vehicle were presented in
time domain when traveling over a ramp step road profile and in frequency domain. The comparison between uncontrolled system and using the fuzzy logic controller
was discussed and also the performance and advantages and the improvement in ride comfort.
Fuzzy Control of Mechanical Vibrating System. Fuzzy logic is used to control active hydro pneumatic suspension. [7] The ability of fuzzy logic were
discuss that could improve the reduction of the body acceleration caused by the car body with road disturbance from uneven surface, pavement point and etc which are
act the tires of running cars. The Fuzzy Logic Controller used in this design has three inputs are body acceleration, body velocity and body deflection velocity and one
output is desired actuator force. The simulation result is to compare the active and passive suspension system is proposed to achieve both ride comfort and good
handling. Te aim was achieve by simulation result that the active suspension system based on fuzzy logic controller shows the improved stability of the onequartercar
model.
Robust Speed Fuzzy Logic Controller for DC Drive was discussed the robust speed control for a DC drive is considered. [8] The basis of the heuristic reasoning
the main features of the robust speed controller are supposed and the Fuzzy Logic Controller that can control the DC Drive was designed. The comparison between PI
controller and Fuzzy Logic Controller to control the DC Drive was approved. In the end of this paper, the robust fuzzy speed control for a DC Drive was examined. The
Fuzzy Logic Controller is able to overcome the disadvantage of usual PIcontroller in sensitiveness to inertia vibration and sensitiveness to the range of reference speed
alteration.
2.2 Introduction to Inverted Pendulum System
