Design Intelligent PID like Fuzzy Sliding Mode Controller for Spherical Motor

Abstract

The minimum rule base Proportional Integral Derivative (PID) Fuzzy Sliding Mode Controller (SMC) with application to spherical motor is presented in this research. The popularity of PID Fuzzy Sliding Mode Controller can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID Fuzzy Sliding Mode Controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing especially in nonlinear and uncertain systems. Proportional Integral Derivative methodology has three inputs and if any input is described with seven linguistic values, and any rule has three conditions, we will need 343 rules. It is too much work to write 343 rules and have lots of problem to design embedded control system e.g., Field Programmable Gate Array (FPGA). In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PD-like fuzzy controller and a conventional PI controller to have the minimum rule base and good trajectory follow disturbance to control of spherical motor. However Sliding Mode Controller is work based on cancelling decoupling and nonlinear terms of dynamic parameters for each direction of three degree of freedom spherical motor, this controller is work based on motor dynamic model and this technique is highly sensitive to the knowledge of all parameters of nonlinear spherical motor"s dynamic equation which caused to challenge in uncertain system. This research is used to reduce or eliminate the Sliding Mode Controller problem based on minimum rule base fuzzy logic theory to control of three degrees of freedom spherical motor system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.

Design Intelligent Model-free Hybrid Guidance Controller for Three Dimension Motor

“…This is suitable for real-time control applications when powerful processors, which can execute complex algorithms rapidly, are not accessible. However, since joints coupling is neglected, control performance degrades as operating speed increases and a manipulator controlled in this way is only appropriate for relatively slow motion [14]. The fast motion requirement results in even higher dynamic coupling between the various robot joints, which cannot be compensated for by a standard robot controller such as PID [13], and hence model-based control becomes the alternative.…”

“…Fuzzy Logic Controller: Based on foundation of fuzzy logic methodology; fuzzy logic controller has played important rule to design nonlinear controller for nonlinear and uncertain systems [11][12][13][14][15]. However the application area for fuzzy control is really wide, the basic The fuzzy inference engine offers a mechanism for transferring the rule base in fuzzy set which it is divided into two most important methods, namely, Mamdani method and Sugeno method.…”

“…Although the fuzzy-logic control is not a new technique, its application in this current research is considered to be novel since it aimed for an automated dynamic-less response rather than for the traditional objective of uncertainties compensation [14][15]. The intelligent tracking control using the fuzzy-logic technique provides a cost-and-time efficient control implementation due to the automated dynamic-less input.…”

“…Feedback control system development is the most important thing in many different fields of safety engineering. The main targets in design control systems are safety stability, good disturbance rejection to reach the best safety, and small tracking error [11][12][13][14][15]. At present, in some applications spherical motors are used in unknown and unstructured environment, therefore strong mathematical tools used in new control methodologies to design nonlinear robust controller with an acceptable safety performance (e.g., minimum error, good trajectory, disturbance rejection).…”

Design New PID like Fuzzy CTC Controller: Applied to Spherical Motor

“…Although the fuzzy-logic control is not a new technique, its application in this current research is considered to be novel since it aimed for an automated dynamic-less response rather than for the traditional objective of uncertainties compensation [38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55]. The intelligent tracking control using the fuzzy-logic technique provides a cost-and-time efficient control implementation due to the automated dynamic-less input.…”