This paper presents a PID tuning method for unstable processes using an adaptive-network-based-fuzzy-inference system (ANFIS) for given gain and phase margin (GPM) speci)cations. PID tuning methods are widely used to control stable processes. However, PID controller for unstable processes is less common. In this paper, the PID controller parameters can be determined by the ANFIS. Because the de...

The paper presents a multi-axis motion controller based on DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array) to meet the communication demands of modern complex control systems. In details, the paper first introduces a design method of the structure of the motion controller which is based on PC. This controller consists of FIFO (First In First Out) circuit block and baud r...

Memristor predicted and described by L. O. Chua is a new electrical element. Memristor with variable resistance which changes automatically as its voltage changing can be used as a tunable parameter in control systems. Phase-lead controller is widely used in industrial process control applications. The conventional method for adjusting phase-lead controller parameters is based on the “trial and...

Wafer manufacturing Industries uses conventional controller, but in order to control the position in sub nanometer range conventional controller is not suitable, why because Tuning and augmenting the controller becomes difficult and expensive. So a robust controller is designed for wafer manufacturing system. The controller design in this paper is performed for the translational x and y DOFs in...

This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learning technique is applied to generate the required modelling rules from input/output measurements recorded in the off-line structure learning phase. Second, a fully differentiable fuzzy neural network is developed to construct the inverse dynamics part of the controller for the on-line parameter lea...

In this paper modeling of an inverted pendulum is done using Euler – Lagrange energy equation for stabilization of the pendulum. The controller gain is evaluated through state feedback and Linear Quadratic optimal regulator controller techniques and also the results for both the controller are compared. The SFB controller is designed by Pole-Placement technique. An advantage of Quadratic Contro...