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This study presents a novel meta-heuristic optimization method that combines the Henry Gas Solubility Optimization (HGSO) technique with symmetric chaotic systems. By leveraging the randomness of chaotic systems, the parameters of the HGSO algorithm that require random generation are produced through chaotic processes, allowing the algorithm to exhibit chaotic behavior in its pursuit of optimal values. This innovative approach is termed Chaotic Henry Gas Solubility Optimization (CHGSO), with the primary objective of enhancing the performance of the HGSO method. The randomness of the data obtained from chaotic systems was validated using NIST-800-22 tests. The CHGSO method was applied to both 47 benchmark functions and the optimization of parameters for a PID controller utilized in the speed control of a DC motor. To evaluate the effectiveness of the proposed method, it was compared with several widely recognized algorithms in the literature, including PSO, WOA, GWO, EA, SA, and the original HGSO algorithm. The results demonstrate that the proposed method achieved the best performance in 43 of the benchmark functions, outperforming the other algorithms. In the context of controller design, the PID parameters were optimized using the error-based ITSE objective function. According to the controller responses, the proposed method has achieved the best results in the simulation studies, with a settling time of 0.035 and a rise time of 0.014 without overshooting, and in the experimental studies, with a settling time of 0.15 and a settling time of 1.4%. When the results are examined, it is observed that it has achieved successful results in the controller design problem. [ABSTRACT FROM AUTHOR]

This paper presents a continuous approach of sliding-mode current and flux observers for an induction machine. The proposed observer structure both decouples machine equations and makes them completely insensitive to rotor resistance variation. An estimation algorithm based on these observers is proposed to calculate speed and rotor resistance independently. In the proposed algorithm, the speed and rotor resistance are considered to be unknown constants, because the speed and rotor resistance change slowly compared to the electrical variables such as currents and fluxes. The simulation and experimental results demonstrate the good performance of the proposed observer and estimation algorithm and of the overall indirect-field-oriented-controlled system. Index Terms--Current and flux observer, induction machine (IM), speed and rotor resistance estimation.

A new close loop current model flux observer is designed to estimate the rotor flux, position and velocity of an induction machine. The current observer includes carefully designed sliding mode functions which are derivative of the fluxes along the [alpha] and [beta] axes. Therefore, when the estimated current converges to the measured one, the flux estimation is a mere integration of the sliding mode function. The rotor speed can then be derived from the sliding mode functions and the estimated flux. In the current and flux observers all of the terms that contain the rotor time constant and the rotor speed have been replaced by the sliding mode functions, thus making the proposed current and flux estimations completely insensitive to the rotor time constant variation and any error in the estimated speed. Simulations and experiments are performed under a variety of conditions to validate the effectiveness of the proposed algorithm. Index Terms--Current model flux observer, induction machine, sensorless control, sliding mode.

In this letter, a new sliding-mode sensorless control algorithm is proposed for the field-oriented induction machine drive. In the proposed algorithm, the terms containing flux, speed, and rotor time constant, which are common in both current and flux equations, in the current model of the induction machine are estimated by a sliding function. The flux and speed estimation accuracy is guaranteed when the error between the actual current and observed current converges to zero. Hence, the fourth-order system is reduced to two second-order systems, and the speed estimation becomes very simple and robust to the parameter uncertainties. The new approach is verified by simulation and experimental results. Index Terms--Induction motor, field-oriented control, sensorless control, sliding mode.

In this paper, a fractional-order sliding mode controller (FOSMC) is designed and applied to a four-rotor unmanned aerial vehicle (Quadrotor) to perform trajectory tracking for different time-varying references. Because quadrotor's nonlinear system dynamics are effected by external disturbances and parameter variations easily, the FOSMC is used as a nonlinear controller to combine the flexibility of the fractional-order approach and the disturbance rejection characteristics of the integer-order sliding mode controller (IOSMC) to keep quadrotor on desired trajectory, as well as overcome parameter variations. In order to indicate the priority of the FOSMC, the IOSMC is also applied to quadrotor for the same references. The experimental results show that FOSMC is better than IOSMC in terms of error elimination and is good at dealing with parameter variations occurred while tracking the desired trajectory. [ABSTRACT FROM AUTHOR]

In this paper, speed and direction angle of a four wheel skid-steered mobile robot (4 WD SSMR) has been controlled via adaptive-fuzzy fractional-order sliding mode controller (AFFOSMC) under different speed and angle reference signals. The hybrid control method is designed to combine all advantages that controllers have such as flexibility realized by fractional order calculation, robustness to disturbances and parameters variations provided by sliding mode controller (SMC) as well as adaptation of G constant of SMC via fuzzy controller, simultaneously. Also, a fractionalorder SMC is applied to the system for the same reference speed and angle references to show the effects of the changes and adaptation of G constant. Experimental results show that the AFFOSMC has better trajectory tracking performance than the FOSMC. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear Continuous Sliding Mode control (CSMC) application is presented for trajectory tracking control of a four rotor unmanned aerial vehicle (UAV) called the Quadrotor, also known as micro helicopter. The proposed controller is tested with different time-varying reference routes to provide a stable flight for position control. To show the effectiveness of the designed CSMC, well-tuned PI controller is also applied to quadrotor for the same routes. The current position of the quadrotor is taken from accelerometer, gyroscope and ultrasonic sensors. The experimental results show that the CSMC is adequate to dealing with parameter uncertainties occur in the system dynamics while flying and has satisfactory performance in terms of robustness against to disturbances and error elimination when it compared with PI controller. [ABSTRACT FROM AUTHOR]

In this paper, speed and direction angle control of four-wheel drive skid-steered mobile robot (4WD SSMR) is realized by Fractional-Order Proportional Integral (FOPI) controller. Speed and direction angle of the mobile robot are calculated by using angular velocity of each motors. FOPI controller produces the torques of each motor of mobile robot for trajectory tracking and stabilization in the desired position. A well-tuned conventional PI controller is also applied to mobile robot for comparison with the FOPI. Experimental results prove that the FOPI shows better trajectory tracking performance than PI controller in terms of trajectory tracking accuracy and error levels. [ABSTRACT FROM AUTHOR]

In this paper an observer based on measured and estimated currents and a kinematic model is designed to estimate the velocity and direction angle of an unmanned vehicle (UV). The Lyapunov stability theory is used to establish the stability conditions for the observer. It is shown that the observer will converge in a finite time and the observer gains satisfy the constraints of the stability conditions. The observed velocity and direction angle are used in the closed loop instead of measured ones for sensorless control of the UV. The velocity and direction angle control of the UV are carried out by a well-tuned PI controller. The experimental results show that the proposed observer can be perfectly implemented for sensorless control without using a mechanical sensor, and satisfying results are obtained. In the experiment, command voltages are used rather than measured ones, and therefore only current sensors are needed for the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper a fuzzy controller is applied to velocity and direction angle control of a certain type of wheeled mobile robots called Automated Guided Vehicles (AGVs). The velocity and direction angle of the AGV are controlled to keep the vehicle on desired path. A PI controller is also applied to AGV in order to show the robustness of the fuzzy controller. Experimental results prove that the fuzzy controller shows better tracking performance than the PI controller in terms of robustness, smoothness and fast dynamics. Results are also given for sudden disturbance and extra load conditions and satisfied results are obtained. [ABSTRACT FROM AUTHOR]

This paper presents the experimental validation of a robust position control structure of an indirect field oriented (IFO) induction motor (IM) based on chattering free sliding mode (CFSM) controller. The controller has been tested for various command positions through the simulation and experiment. The results verify the control theory and demonstrate the usefulness of the proposed control scheme. The experimental results are given for step position references that change from 1 rad to 30 rad. It is observed that the tracking performance is very good at all references and the resulting control signals are smooth. Finally, the simulation and experimental results are shown to be in a very close agreement. Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved. [ABSTRACT FROM AUTHOR]

In this paper, a novel speed estimation algorithm mathematically derived from current model of an induction motor is presented. The method used here is more advantageous than other techniques due to its simplicity. In this technique, since the speed varies slowly as compared to electrical variables such as currents and fluxes, the speed is assumed to be an unknown constant. Based upon this assumption, a definition of a new speed estimator is reported and its performance is confirmed experimentally. [Copyright &y& Elsevier]