Sensitivity Study of a Class of Fuzzy Control Systems

The paper performs the sensitivity study with respect to the parametric variations of the controlled plant in case of a class of fuzzy control systems dedicated to servo systems. The presentation is particularized to fuzzy control systems to solve the tracking control problem in case of wheeled mobile robots of tricycle type with two degrees of freedom. There is proposed a new development method for Takagi-Sugeno PI-fuzzy controllers based on the application of the Extended Symmetrical Optimum method to the basic linear PI controllers in a cascaded control system structure. There are derived sensitivity models, validated by considering a case study concerning the speed control of a servo system with DC motor as actuator in mobile robot control. Experimental results validate the development method for Takagi-Sugeno PI-fuzzy controllers

A CENTER MANIFOLD THEORY-BASED APPROACH TO THE STABILITY ANALYSIS OF STATE FEEDBACK TAKAGI-SUGENO-KANG FUZZY CONTROL SYSTEMS

The aim of this paper is to propose a stability analysis approach based on the application of the center manifold theory and applied to state feedback Takagi-Sugeno-Kang fuzzy control systems. The approach is built upon a similar approach developed for Mamdani fuzzy controllers. It starts with a linearized mathematical model of the process that is accepted to belong to the family of single input second-order nonlinear systems which are linear with respect to the control signal. In addition, smooth right-hand terms of the state-space equations that model the processes are assumed. The paper includes the validation of the approach by application to stable state feedback Takagi-Sugeno-Kang fuzzy control system for the position control of an electro-hydraulic servo-system

An expert fuzzy logic controller employing adaptive learning for servo systems

An expert fuzzy logic controller with adaptive learning is proposed as an intelligent controller for servo systems. A key component of this controller is an adaptive learning mechanism which is used to self-regulate the scaling factors and the control action based on the error between the desired value and the plant output. The inference engine of this controller is based on the principle of approximate reasoning and the learning strategy is based on reinforcement learning. A novel approach of model reference adaptive control is also proposed for servo systems. The comparison of the performance between the proposed controller and PID controllers is discussed. The simulation results show that the performance of the proposed controller is better than the conventional approach or previous research. The real-time application demonstrates that a faster response of a servo system can be achieved. Furthermore, the proposed controller is relatively insensitive to variations in the parameters of control systems

A survey of fuzzy control for stabilized platforms

This paper focusses on the application of fuzzy control techniques (fuzzy type-1 and type-2) and their hybrid forms (Hybrid adaptive fuzzy controller and fuzzy-PID controller) in the area of stabilized platforms. It represents an attempt to cover the basic principles and concepts of fuzzy control in stabilization and position control, with an outline of a number of recent applications used in advanced control of stabilized platform. Overall, in this survey we will make some comparisons with the classical control techniques such us PID control to demonstrate the advantages and disadvantages of the application of fuzzy control techniques

Performance comparison between PID and fuzzy logic controller in position control system of dc servomotor

The objective of this paper is to compare the time specification performance between conventional controller and artificial intelligence controller in position control system of a DC motor. This will include design and development of a GUI software using Microsoft Visual Basic 6.0 for position control system experiment. The scope of this research is to apply direct digital control technique in position control system. Two types of controller namely PID and fuzzy logic controller will be used to control the output response. An interactive software will be developed to visualize and analyze the system. This project consists of hardware equipment and software design. The hardware parts involve in interfacing MS150 Modular servo System and Data Acquisition System with a personal computer. The software part includes programming real-time software using Microsoft Visual Basic 6.0. Finally, the software will be integrated with hardware to produce a GUI position control system

Identification of Nonlinear Systems From the Knowledge Around Different Operating Conditions: A Feed-Forward Multi-Layer ANN Based Approach

The paper investigates nonlinear system identification using system output data at various linearized operating points. A feed-forward multi-layer Artificial Neural Network (ANN) based approach is used for this purpose and tested for two target applications i.e. nuclear reactor power level monitoring and an AC servo position control system. Various configurations of ANN using different activation functions, number of hidden layers and neurons in each layer are trained and tested to find out the best configuration. The training is carried out multiple times to check for consistency and the mean and standard deviation of the root mean square errors (RMSE) are reported for each configuration.Comment: "6 pages, 9 figures; The Second IEEE International Conference on Parallel, Distributed and Grid Computing (PDGC-2012), December 2012, Solan

Fuzzy anti-windup scheme for practical control of point-to-point (Ptp) positioning systems

The Positioning Systems Generally Need A Controller To Achieve High Accuracy, Fast Response And Robustness. In Addition, Ease Of Controller Design And Simplicity Of Controller Structure Are Very Important For Practical Application. For Satisfying These Requirements, Nominal Characteristic Trajectory Following (NCTF) Controller Has Been Proposed As A Practical PTP Positioning Control. However, The Effect Of Actuator Saturation Cannot Be Completely Compensated Due To Integrator Windup Because Of Plant Parameter Variations. This Paper Presents A Method To Improve The NCTF Controller For Overcoming The Problem Of Integrator Windup By Adopting A Fuzzy Anti-Windup Scheme. The Improved NCTF Controller Is Evaluated Through Simulation Using Dynamic Model Of A Rotary Positioning System. The Results Show That The Improved NCTF Controller Is Adequate To Compensate The Effect Of Integrator Windup