S. M. Radaideh

Modified extended Kalman filtering

In this paper we compare the performance of the extended Kalman filter (EKF) with that of a proposed filter called modified extended Kalman filter (MEKF), in terms of the actual state and the estimated state as a function of time and the integral-squared error as a function of noise intensity both for dynamics and measurement noise. All the simulation results indicate that the performance of the MEKF is better than EKF. For illustration, numerical examples are presented using both EKF and MEKF. >

Fuzzy logic controller for overhead cranes

Purpose – To propose a new method for controlling the overhead crane systems based on the theory of fuzzy logic with a reduced number of rules than has appeared before in the literature. The proposed fuzzy logic controller (FLC) can be implemented to move the overhead crane along a desired path while ensuring that the payload is swing free at the end of the motion.Design/methodology/approach – In this study, a FLC that includes two rule bases, one for displacement control, the other for swing control, was designed and successfully implemented to move the overhead crane along a desired path while ensuring that the payload is swing free at the end of the motion.Findings – Control simulation results demonstrate that by using the proposed FLC, the overhead traveling crane smoothly moves to the destination in short time with small swing angle and almost no overshoot.Originality/value – This paper offers practical help to whom are working in controlling the transporting the payloads to the required position as ...

Modeling Surface Finish in End Milling Using Fuzzy Subtractive Clustering-Based System Identification Method

Abstract In this article, fuzzy subtractive clustering-based system identification and a Sugeno-type fuzzy inference system are used to model the surface finish of the machined surfaces in end milling and to develop a better understanding of the effect of process parameters on surface quality. Such an understanding can provide insight into the problems of controlling the quality of the machined surface when the process parameters are adjusted to obtain certain characteristics. The surface finish model is identified by using spindle speed, feed rate; and depth of cut as input data. Surface finish of the machined part is the output of the process. The model building process is carried out by using fuzzy subtracting clustering-based system identification in both input and output space. Minimum error is obtained through numerous searches of clustering parameters. The fuzzy logic model is capable of predicting the surface finish for a given set of inputs (spindle speed, feed rate, and depth of cut). As such, the machinist may predict the quality of the surface for a given set of working parameters and may also set the process parameters to achieve a certain surface finish. The model is verified experimentally by employing different sets of inputs. This study deals with the experimental results obtained during end milling on aluminum alloy 390.

A modified PID controller (PIIσβD)

Abstract The purpose of this study is to modify the traditional PID controller in order to improve its performance (stability and tracking) by changing the length of integration interval. The performance of the traditional PID controller was improved by changing the length of integration interval to make the most of the returns of the PID and PI σ D controllers. The asymptotic stability domain, in terms of the feedback gains, is derived for systems of second order using the modified controller which will be identified as PII σ β D . Comparing this controller with the traditional PID controller and PI σ D controller proposed in [1] , it proves that it is more accurate and more stable. For illustration and comparison, two examples have been simulated to evaluate the performance of the modified controller. All simulation results indicate that the modified controller is better than the traditional PID controller and the PI σ D controller from the accuracy and stability point of view.

LQR-based control of parallel-connected boost dc-dc converters: a comparison with classical current-mode control

This work investigates the application of the Linear Quadratic Regulator (LQR) technique to a two-module parallel-connected Current-Mode-Controlled (CMC) Pulse-Width-Modulated (PWM) dc-dc boost converter operating in the continuous conduction mode. New feedback controllers are designed for the modular step-up converter under two different control schemes. The dynamic responses are compared with those obtained using the classical control approach. The role of LQR-based control in providing equal-current sharing among the constituent modules is addressed. Cycle-by-cycle simulations are carried out to validate the analysis.

Adaptive Neuro-Fuzzy Technique for Tuning Power System Stabilizer

This paper presents an adaptive neuro-fuzzy technique based on Sugeno first-order fuzzy model for tuning the parameters of a conventional phase lead-lag PSS from on online measurements of the generator loading conditions using adaptive neuro-fuzzy inference system (ANFIS) architecture. Input patterns, of the proposed ANFIS, comprising the generator real power Pe and reactive power Qe are associated with the corresponding output patterns of the desired PSS parameters Kc and T1(T3) over a wide range of operating conditions. Once trained the proposed ANFIS-PSS is capable of providing the PSS parameters Kc and T1 in real time for any generator loading conditions. Simulation results under small disturbances at different loading conditions have been carried out to assess the effectiveness and robustness of the proposed ANF-PSS in enhancing enhance the small signal stability of the power system

Monitoring Hole Quality in a Drilling Process Using a Fuzzy Subtractive Clustering-based qa System Identification Method

In this study, a subtractive clustering fuzzy identification method and a Sugeno-type fuzzy inference system are used to monitor the hole quality in a drilling. The model for the hole quality is identified by using the hardness of the workpiece, the cutting speed, and the cutting feed as input data and the hole quality features of hole roughness, roundness error, and oversize error as the output data. The process of model building is carried out by using subtractive clustering in both the input and output spaces. A minimum error model is obtained through exhaustive search of the clustering parameters. The fuzzy model obtained is capable of predicting the hole quality for a given set of inputs (hardness of the workpiece, the cutting speed, and the cutting feed). Therefore, one can predict the quality of the drilled hole for a given set of working parameters. The fuzzy model is verified experimentally using different sets of inputs. This study deals with the experimental results obtained during drilling on medium carbon steel (AISI 1060), aluminum, and brass.

Reductions of pendulations of overhead cranes under the effect of air resistance by a cable manipulation manner

Reduction of pendulations of the payloads in overhead cranes is carried out. The air resistance effect is taken into considerations. The reduction of oscillations based on the continuous unreeling method. The equations of motion of the overhead crane considered the system as a combination of a trolley and a pendulum. Different combinations of payload, hoisting cable lengths with different unreeling speeds and trolley mass are simulated. Results showed that significant reduction in pendulations was achieved.

Series Resistance Compensation in PTAT Temperature Sensors and Bandgap Reference Circuits

A general compensation technique for the extrinsic series resistor in the pn diode has been proposed in this paper. Proportional-to-absolute-temperature (PTAT) temperature sensors and bandgap reference circuits using diodes have been also proposed. In the design of bandgap reference circuits, the most common method used to produce an output voltage that is independent of temperature variations is the curvature correction method. The series resistance compensation technique represents part of this curvature. Several designs of PTAT temperature and bandgap circuits have been proposed in this work. For illustration, the PTAT sensor and bandgap circuits are numerically simulated, using the proposed algorithm.

A New Fuzzy Gain Scheduling Scheme for the PID Controllers

Abstract In this paper, a new fuzzy gain scheduling scheme for the PID controller have been proposed. Fuzzy IF-THEN rules aze used on-line to adjust the parameters of the PID controller based on the system error and its derivative. In terms of settling time, one percent peak overshoot and the integral of the time multiplied by the absolute error, the simulation results clearly indicate that the performance of the proposed scheme is better than the Ziegler-Nichols PID controller [1] and the fuzzy gain scheduling scheme of PID controller [2]. For illustration and compazison, numerical examples, using third and fourth order plants, are presented.