In pH reactors, determination and control of pH is a common problem concerning chemical-based industrial processes due to the non-linearity observed in the titration curve. We introduced a modified multiregional fuzzybased control system to overcome the complexity of precise control of pH. In order to compensate for the experimental inaccuracies in measurements of pH in-situ values; an observer...

This paper addresses the problem of power quality, and degradation current waveform in distribution network which results directly from proliferation nonlinear loads. We propose to use a five-level neutral point clamped (NPC) inverter topology for implementation shunt active filter (SAPF). The aim SAPF is inject harmonic currents phase opposition at connection point. identification harmonics ba...

Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which t...

− This work presents the method of controlling the motor currents to minimize the torque ripple, using a neuro-fuzzy compensator. By this method, the compensating signal is added to the output of a classical PI controller, in a current-regulated speed control loop.

al. [3] in the case of a humanoid robot based on hybrid fuzzy control methods. This paper proposes a bipedal locomotion controller using an optimized Neuro-Fuzzy inference structure. In which, it is based on an adaptive neuro-fuzzy inference identifier (ANFII) for modeling the inverse dynamics of the biped robot. The proposed learning scheme is based on the zero moment point (ZMP); while the mo...

In this paper, an adaptive control method for trajectory tracking of robot manipulators, based on new neuro-fuzzy modelling is presented. The proposed control scheme uses a three-layer neural fuzzy network (NFN) to estimate system uncertainties. The function of robot system dynamics is first modelled by a fuzzy system, which in the sequel is approximated by a combination of high order neural ne...

This paper deals with the application of a neuro-fuzzy inference system to a mobile robot navigation in an unknown, or partially unknown environment. The final aim of the robot is to reach some pre-defined goal. For this purpose, a sort of a co-operation between three main sub-modules is performed. These sub-modules consist in three elementary robot tasks: following a wall, avoiding an obstacle...

Neuro-fuzzy systems, have recently been applied to the problem of Call Admission Control (CAC) in ATM networks. Their advantage as opposed to classical schemes, based on the modeling of sources connected to the network, is their capability to learn the behavior of data sources through training process, and to predict the future behavior based on the experience acquired in the learning process. ...

The paper describes the application of a combined neuro-fuzzy model for indoor temperature dynamic and automatic regulation. The neural module of the model, an auto-regressive neural network with external inputs (NNARX), produces indoor temperature forecasts that are used to feed a fuzzy logic control unit that simulates switching the heating, ventilation and air conditioning (HVAC) system on a...

Efficient elevator group control is important for the operation of large buildings. Recent developments in this field include the use of fuzzy logic and neural networks. This paper summarizes the development of an evolution strategy (ES) that is capable of optimizing the neuro-controller of an elevator group controller. It extends the results that were based on a simplified elevator group contr...