Implementation of LQR Mapped Sensory Fuzzed Fuzzy Logic Controller on Inverted Pendulum System

When designing a controller, the very first step is mathematical modeling of the concerned plant. As we know that during this mathematical modeling several mathematical approximation, uncertainties in the form of system parameter variations, plant nonlinearities and disturbances are involved. Although the conventional PID controller is vastly used controller but it is linear in nature thus it demands a very accurate mathematical model of the plant. Suppose for the given operating conditions, the system has nonlinear behavior then the conventional PID controller may perform unsatisfactorily hence in such conditions fuzzy controller may perform better. As fuzzy controller can be designed with nonlinear characteristics thus a well-designed fuzzy controller can handle plant uncertainties and inherent nonlinearities in quite effective manner. But if the number of inputs is more then while designing the rules for the fuzzy controller will be large and complex. Having large number of rules may degrade the performance of the controller and sometimes cause the rule explosion in FLC. To overcome this problem LQR (Linear Quadratic Regulator) fusion technique is proposed which reduces the possibility of rule explosion by reducing the number of inputs as well as the number of rules. As in case of Inverted pendulum system, there are four inputs to conventional fuzzy controller which has been reduced to two inputs with LQR fusion technique. The performance of the designed controller is evaluated in simulations as well as in real time using MATLAB and SIMULINK on Inverted Pendulum. The results shown in this report show the satisfactory performance of the controller in each case Keywords– Fuzzy logic controller, LQR fusion.Inverted pendulum system.