Because of extreme local saturation at pole tips of excited phase and uncircular shape of rotor and stator, a Swithed Reluctance Motor (SRM) does not have a simple and accurate mathematical model. Therefore, the output control of this motor requires a robust controller which is not based on an accurate model of the process. Fuzzy controllers, to some extent, will satisfy these requirements. Tet...

A new technique for selecting, in real time, diierent sensing techniques for a robotic system has been developed. The proposed method is based on stochastic dynamic programming, which provides an eeective solution to multi-stage decision problems. At each stage in the decision process a sensor selection controller has the option of consulting a new process monitoring technique to improve the kn...

Conventional staged ventilation systems are commonly used in agriculture to maintain interior environments near desired conditions for livestock housing and greenhouses. This paper identifies design parameters for fuzzy-based control of these staged ventilation systems. A simple non-steady state heat balance is used in conjunction with a broiler house simulation model, and coupled with a model ...

Abstract: This paper considers a robust decentralized H∞ control problem for uncertain multi-channel systems. The uncertainties are assumed to be time-invariant, normbounded, and exist in both the system and control input matrices. Our interest is focused on dynamic output feedback. A necessary and sufficient condition for the uncertain multi-channel system to be robustly stabilizable with a sp...

one of the most important fuel cells (fcs) is proton exchange membrane fuel cells (pemfcs). the outputvoltage of this fc depends on current loads. this paper tries to introduce, implement and control the voltage ofpemfc, during load variations. the output voltage of fuel cell should be constant during load variation. toachieve this goal, a controller should be designed. here, the lead-lag contr...

We present a method for planning the motion of arbitrarily-shaped volumetric deformable bodies or robots through complex environments. Such robots have very highdimensional configuration spaces and we compute trajectories that satisfy the dynamics constraints using a two-stage learning method. First, we train a multitask controller parameterized using dynamic movement primitives (DMP), which en...

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual out...

In this paper, a chattering free sliding mode control (SMC) for a robot manipulator including PID part with a fuzzy tunable gain is designed. The main idea is that the robustness property of SMC and good response characteristics of PID are combined with fuzzy tuning gain approach to achieve more acceptable performance. For this purpose, in the first stage, a PID sliding surface is considered su...

Premature convergence is a major challenge for particle swarm optimization algorithm (PSO) when dealing with multi-modal problems. The reason is partly due to the insufficient exploration capability because of the fast convergent speed especially in the final stage. In this paper, the PSO is regarded as a two-inputs one-output feedback system, and two PID controllers are incorporated into the m...