The control of nonlinear systems is difficult because no systematic mathematical tools exist to help find necessary and sufficient conditions to guarantee their stability and performance. The problem becomes yet more complex if some of the plant parameters are unknown. By using a Takagi-Sugeno-Kang (TSK) fuzzy plant model [1]-[4], a nonlinear system can be expressed as a weighted sum of some si...

The development of a Self-Tuning Neuro-Fuzzy Generalized Minimum Variance (GMV) controller is described. It uses fuzzy expert knowledge of the dynamic weightings to meet desired closed-loop stability and performance requirements. The controller is formulated in a polynomial system approach mixed with a Neuro-Fuzzy model and Fuzzy Self-Tuning mechanism. The proposed method is applied to a model ...

In this paper we address the design of a fuzzy flight controller that achieves stable and robust “aggressive” manoeuvrability for an unmanned helicopter. The fuzzy flight controller proposed consists of a combination of a fuzzy gain scheduler and linguistic (Mamdani-type) controller. The fuzzy gain scheduler is used for stable and robust altitude, roll, pitch, and yaw control. The linguistic co...

Based on parameter self-tuning fuzzy PID controller, a fuzzy inference method is utilized to realize automatic regulating PID parameter, and the application of the controller in a system is studied with MATLAB in this paper. The combination of PID controller system and fuzzy controller system combines the convenience of PID control together with the flexibility of fuzzy control, and takes advan...

Two problems: Parameter uncertainty and chattering effect present in Control signal are have a great deal in performance of system with the designed controllers. This paper presents Fuzzy Sliding Mode Controller (FSMC) for Multi Area Load Frequency Control problem or Automatic Generation Control (AGC) in a De-regulated environment. The first problem is addressed by designing a sliding mode cont...

This study proposes a combination of a fuzzy sliding mode controller (FSMC) with integral-proportion-Derivative switching surface based superconducting magnetic energy storage (SMES) and PID tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. The goal of design is to improve the dynamic response of power systems after load demand changes. In t...

New trends and the effect of key factors influence the quality of the holes produced by ECM processes. Researchers developed a fuzzy logic controller by adding intelligence to the ECM process. Maintaining optimum ECM process conditions ensures higher machining efficiency and performance. This paper presents the development of a fuzzy logic controller to add intelligence to the ECM process. An e...

This paper presents two optimal approaches of two-stage fuzzy controller for traffic signals at isolated intersections. Firstly, in the light that traffic status variables in two-stage controller leads to the inefficiency of traffic status weakening under low traffic flow, a two-stage combination fuzzy controller is designed from the perspective of structural optimization; this controller intro...

This paper demonstrates the detailed analysis of Proportional-Integral (PI) controller and Fuzzy Logic controller for speed control of a Permanent Magnet Brushless DC (PMBLDC) motor for different speed commands and varying load torque conditions. Implementation of PI controller in closed loop conditions is done. Analysis of classical tuning methods to obtain best PI parameters for speed control...