Purpose: The research aims to study the measurement of the performance of accounting units level of the research sample by using the Federal quality Model European (EFQM)   Design/methodology/approach: the (EFQM) which included seven dimensions "Leadership, Strategic Planning, External Focus, Information and Analysis, Faculty / Staff and Workplace Focus, Process Effectiveness & Outcomes and Achievements" And its effect on the Control Environment, which includes three dimensions: "Integrity, management philosophy and commitment to powers" . the sample is supervisory units of colleges affiliated with the University of Baghdad in Iraq, and a sample was chosen that included fifty-one individuals in the accounting departments.

This paper deals with defining Burr-XII, and how to obtain its p.d.f., and CDF, since this distribution is one of failure distribution which is compound distribution from two failure models which are Gamma model and weibull model. Some equipment may have many important parts and the probability distributions representing which may be of different types, so found that Burr by its different compound formulas is the best model to be studied, and estimated its parameter to compute the mean time to failure rate. Here Burr-XII rather than other models is consider  because it is used to model a wide variety of phenomena including crop prices, household income, option market price distributions, risk and travel time. It has two shape-parame

This work is concerned with designing two types of controllers, a PID and a Fuzzy PID, to be used
for flying and stabilizing a quadcopter. The designed controllers have been tuned, tested, and
compared using two performance indices which are the Integral Square Error (ISE) and the Integral
Absolute Error (IAE), and also some response characteristics like the rise time, overshoot, settling
time, and the steady state error. To try and test the controllers, a quadcopter mathematical model has
been developed. The model concentrated on the rotational dynamics of the quadcopter, i.e. the roll,
pitch, and yaw variables. The work has been simulated with “MATLAB”. To make testing the
simulated model and the controllers m

In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.

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 output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl

<p>The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the propo

L1 adaptive controller has proven to provide fast adaptation with guaranteed transients in a large variety of systems. It is commonly used for controlling systems with uncertain time-varying unknown parameters. The effectiveness of  L1 adaptive controller for position control of single axis has been examined and compared with Model Reference Adaptive Controller (MRAC). The Linear servo motor is one of the main constituting elements of the x-y table which is mostly used in automation application. It is characterized by time-varying friction and disturbance.

    The tracking and steady state performances of both controllers have been assessed fo

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue