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Shear wave ultrasound elastography is a quantitative imaging approach in soft tissues based on viscosity-elastic properties. Complex shear modulus (CSM) estimation is an effective solution to analyze tissues' physical properties for elasticity and viscosity based on the wavenumber and attenuation coefficient. CSM offers a way to detect and classify some types of soft tissues. However, CSM-based elastography inherits some obstacles, such as estimation precision and calculation complexity. This work proposes an approach for two-dimensional CSM estimation and soft tissue classification using the Extended Kalman Filter (EKF) and Decision Tree (DT) algorithm, named the EKF-DT approach. CSM estimation is obtained by applying EKF to exploit shear wave propagation at each spatial point. Afterward, the classification of tissues is done by a direct and efficient decision tree algorithm categorizing three types of normal, cirrhosis, and fibrosis liver tissues. Numerical simulation scenarios have been employed to illustrate the recovered quality and practicality of the proposed method's liver tissue classification. With the EKF, the estimated wave number and attenuation coefficient are close to the ideal values, especially the estimated wave number. The states of three liver tissue types were automatically classified by applying the DT coupled with two proposed thresholds of elasticity and viscosity: (2.310 kPa, 1.885 Pa.s) and (3.620 kPa 3.146 Pa.s), respectively. The proposed method shows the feasibility of CSM estimation based on the wavenumber and attenuation coefficient by applying the EKF. Moreover, the DT can automate the classification of liver tissue conditions by proposing two thresholds. The proposed EKF-DT method can be developed by 3D image reconstruction and empirical data before applying it in medical practice.

The diagnostic ultrasound technique uses scattered information appearing limitations as the research models’ motivation to create a new image to supplement quantitative ultrasound information in tomography ultrasound imaging. One promising solution is density imaging, which is capable of detecting diseased tissues. In tomography ultrasound imaging, the DBIM method is commonly used to restore the object to be imaged; this method’s advantage is fast convergence, but easy to be affected by noise. Therefore, a beamforming technique using multiple probe elements transmitting simultaneously to produce a narrow beam capable of minimizing the effect of noise has been proposed for density imaging using DBIM. The numerical simulation results have shown that noise and normalization errors are significantly reduced when using beamforming DBIM.

International audience; This paper proposed an efficient model predictive control strategy for a three-level T-type inverter connected to a doubly fed induction generator. A dynamic model is utilized to track the power reference, preserve the DC-link voltage balancing and reduce the inverter switching frequency and common-mode voltage. Unlike the traditional finite control set model predictive control, the stability of the closed-loop system and computational burden reduction are concurrently accomplished as the main contribution to the proposed strategy. At each sampling period, the proposed algorithm only considers the candidate control inputs which satisfy the stability condition taken from a suitable control Lyapunov function for evaluating the optimization problem. Due to model uncertainties and discrete set control input voltages, an attractivity set is employed to determine the stability and converge of the system. Therefore, the lower computation time of the optimization problem is the potential benefit compared with the conventional method. Simulation investigation with different operating conditions of a 2 MW wind turbine is carried out by MATLAB/Simulink. The achieved results confirm the stability guarantees while reducing the computational burden and obtaining the same control performances in comparison with the conventional method.

In this paper, we introduce a mobile application called CarSafe, in which data from the acceleration sensor integrated on smartphones is exploited to come up with an efficient classification algorithm. Two statuses, "Driving" or "Not driving," are monitored in the real-time manner. It enables automatic actions to help the driver safer. Also, from these data, our software can detect the crash situation. The software will then automatically send messages with the user's location to their emergency departments for timely assistance. The application will also issue the same alert if it detects a driver of a vehicle driving too long. The algorithm's quality is assessed through an average accuracy of 96.5%, which is better than the previous work (i.e., 93%).

This paper is about control of Automated Guided Vehicle for path following using fuzzy logic controller. The Automated Guided Vehicle is a tricycle wheeled mobile robot with three wheels, two fixed passive wheels and one steering driving wheel. First, kinematic and dynamic modeling for Automated Guided Vehicle is presented. Second, a controller that integrates two control loops, kinematic control loop and dynamic control loop, is designed for Automated Guided Vehicle to follow an unknown path. The kinematic control loop based on Fuzzy logic framework and the dynamic control loop based on two PID controllers are proposed. Simulation and experimental results are presented to show the effectiveness of the proposed controllers.

Autonomous Guided Vehicle Systems (AGVs) are used to transport goods and products in manufacturing fields where navigation can be done in a structured environment. In order to track the given trajectory, a tracking control based on Lyapunov stability theory is introduced. The use of the nonlinear Lyapunov technique provides robustness for load disturbance and sensor noise. To apply Lyapunov's theorem, the kinematic model of AGV is given. To recognize its position in indoor environment, in this paper, a laser sensor device NAV200 is used to detect the AGV position in real-time. For simulation and experiment, software and hardware are described. The AGV consists of 4 wheels with two passive wheels and two driving wheels. A controller is developed based on industrial computer. The effectiveness of the proposed controller is proved by simulation and experimental results. [AGV Trajectory Control, Laser Sensor Navigation]

This paper proposes a servo controller design method for speed control of AC induction motors using polynomial differential operator. To do this task, the followings are done. First, nonlinear modeling for an induction motor is introduced and is linearized at equilibrium points using Taylor’s series. Second, an observer is designed to estimate flux, and an extended system incorporating the internal model principle to construct the extended system is shown using polynomial differential operator in case that the types of reference inputs are differential polynomials. Third, a state feedback control law for the extended system to track the given reference input is designed by a regulator design method. A control system is constructed for speed control of the 1.5 KW AC induction motor. The simulation and experimental results are shown to verify the applicability of the proposed controller compared to conventional PI controller for the AC induction motor with a step type of disturbance to track its speed of 3 types of the references such as step, ramp and parabola.

In this paper, stabilization of a 2-degrees-of-freedom (2-DOF) omnidirectional mobile inverted pendulum (OM-IP) is studied. The OM-IP consists of the rod that rotates around a rotary point of a universal joint which is connected at the center of the omnidirectional mobile platform (OMP). For ease of analysis, the OM-IP is decoupled into two subsystems: a 2-DOF inverted pendulum (IP) and an OMP. The IP is a rod that rotates around a universal joint with 2-DOF. The OMP is a body consisting of disk and three omnidirectional wheels that moves on plane and keeps the rod in balance. Dynamic modeling of the 2-DOF OM-IP is presented. From the dynamic equa- tion, an adaptive backstepping control method is proposed to keep the rod in balance. Update law is presented as differential equation of an unknown parameter when the distance from the center of gravity of the rod to the rotary point on the OMP is unknown. Stability of the adaptive controller is proven by using Lyapunov function. Simulation and experimental results show the effectiveness of the proposed controller.

This paper proposes a tracking control method for a three-wheeled omnidirectional manipulator system (OMMS) with disturbance and friction. The OMMS is separated into two subsystems, a three-wheeled omnidirectional mobile platform (OMP) and a selective compliant articulated robot for assembly (SCARA) type of manipulator. Therefore, two controllers are designed to control the OMP and the manipulator system. Firstly, based on a kinematic modeling of the manipulator, a kinematic controller (KC), combined with an integral sliding mode controller (ISMC), is designed for the end-effector of the manipulator to track a desired trajectory with the desired angular velocity vector of links. Secondly, a differential sliding mode controller (DSMC) based on a dynamic modeling of the OMP with force external disturbances is proposed to obtain control inputs moving the OMP so that the manipulator tracks the desired posture without singularity. The system stability is proven using Lyapunov stability theory. The simulation and experimental results are presented to illustrate the effectiveness of the proposed controllers in the presence of disturbance and friction.

In this paper, stabilization of a 2-degrees-of-freedom (2-DOF) inverted pendulum using an omnidirectional mobile platform (OMP) is studied. The inverted pendulum is a rod that rotating around a universal joint structure with 2-DOF. The OMP consists of platform and three omnidirectional wheels that are moving on x y  plane and keeping the rod balance. The dynamic modeling of the 2-DOF inverted pendulum and the OMP are presented. From the dynamic equation, an adaptive backstepping control method is proposed to keep the rod balance with an assumption that the distance from the center of gravity of the rod to the rotary point on the OMP is unknown. Stability of the adaptive controller is proven by using Lyapunov function. Simulation and experimental results show the effectiveness of the proposed controller.

This paper proposes a controller design for an omnidirectional mobile platform (OMP) with three wheels using adaptive backstepping control. A kinematic modeling and a dynamic modeling of the system with disturbance and friction are presented. Based on the dynamic modeling, an adaptive backstepping controller (ABC) is designed to stabilize the OMP with parameter variations and uncertainties caused by friction and slip to follow a desired path. The controller and update laws are designed based on an adaptive backstepping control theory. It includes two steps: firstly, a virtual state and a stability function are introduced. Secondly, Lyapunov functions for the system are chosen and an adaptive backstepping controller to make the system stabilisable and the update laws to estimate the unknown parameters are obtained. The system stability is guaranteed by the Lyapunov stability theory. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed controller and update laws.

This paper describes a new method for a digital gas metal arc welding (GMAW) system. The GMAW system is an arc welding process that incorporates the GMAW power source (PS-GMAW) with a wire feed unit (WFU). The PS-GMAW requires an electric power of constant voltage. A constant magnitude is maintained for the arc current by controlling the wire-feed speed of the WFU. A mathematical model is derived, and a self-tuning fuzzy proportional-integral-derivative (PID) controller is designed and applied to control the welding current. The electrode wire feeding mechanism with this controller is driven by a DC motor, which can compensate for both the molten part of the electrode and undesirable fluctuations in the arc length during the welding process. By accurately maintaining the output welding current and welding voltage at constant values during the welding process, excellent welding results can be obtained. Simulation and experimental results are shown to prove the effectiveness of the proposed controller.

This paper proposes the design and development results of a new quadruped robot. The proposed new quadruped robot has a couple of advantages of flexible locomotion. The quadruped robot is designed and modeled based on a new concept that is the structure model with three segments of quadruped legs. New leg configuration with the simplified operation of four hip actuators is introduced. The posture of the new quadruped robot is more similar to the posture of dog than that of the previous quadruped robots. The objective of this paper is to develop a quadruped robot, which can walk and run in a trot gait with a simple PID controller. Numerical simulation and experimental results are shown to prove the locomotion performance of the proposed controller for the proposed quadruped robot.

Automatic Guided Vehicles (AGVs) are used in many factories. This paper proposes an adaptive tracking controller of omnidirectional AGV (OAGV) with the constant unknown mass and the uncertain bounded friction and slip force vector exerted on the driving wheels. The OAGV consists of 3 wheels with three omnidirectional wheels are equally spaced 1200 from one another. The controller based on the dynamic modeling is designed based on Lyapunov stability theory to stabilize the OAGV to follow a sharp edge trajectory and OAGV doesn’t change heading direction during movement. A laser sensor device NAV200 is used to detect the OAGV position in door environment in real-time. The simulation and experiment results are presented to demonstrate the effectiveness of the proposed controller.

In this paper, a sensorless vector control method is introduced where rotor speed is estimated based on extended Kalman filter (EKF). The EKF is a recursive optimum stochastic state estimator. The proposed EKF is designed to obtain a small estimation speed error in both transient and steady state over a wide speed range. A major challenge at very low and zero speed is the lost coupling effect from the rotor to the stator, which makes the information on rotor variables unobservable on the stator side. To solve this problem, in the proposed EKF, the load torque and the rotor speed with unmeasurable information are estimated simultaneously. The rotor speed is considered via the equation of motion and the estimation of load torque, on the other hand, is performed as a constant parameter. Hardware and software for experiment of the AC induction motor drive are introduced. The experimental results are presented to show the effectiveness of the proposed system.

In this paper, a new tracking controller that integrates a kinematic controller (KC) with a new integral sliding mode dynamic controller (NISMC) is designed for an omnidirectional mobile robot (OMR) to track a desired trajectory at a desired velocity. First, a posture tracking error vector is defined, and kinematic controller (KC) is chosen to make the posture tracking error vector go to zero asymptotically. Second, an integral sliding surface vector is defined based on the angular velocity tracking error vector and its integral term. A new integral sliding mode dynamic controller (NISMC) is designed to make the integral sliding surface vector and the angular velocity tracking error vector go to zero asymptotically. The above controllers are obtained based on Lyapunov stability theory. The simulation results are presented to illustrate effectiveness of the proposed tracking controller.

This paper introduces a tracking controller for Automatic Guided Vehicles (AGV) to track a desired trajectory. The use of the nonlinear Lyapunov technique provides robustness for load disturbance and sensor noise. Based on kinematic model, a trajectory tracking controller of AGV is proposed. System stability is verified by Lyapunov stability. A laser sensor device NAV200 is used to detect the AGV position in door environment in real-time. For simulation and experiment, software and hardware are described. The AGV consists of 4 wheels with two passive wheels and two driving wheels. A controller is developed based on industrial computer. The effectiveness of the proposed controller is proved by simulation and experimental results.

In this paper, a sliding-mode observer is applied to control an AC induction motor. First, the modeling of AC induction motor is presented. After that, a sliding mode observer is proposed to estimate the motor speed, the rotor flux, the angular position of the rotor flux and the motor torque from monitored stator voltages and currents. The proposed sliding mode observer provides very good performance for both low and high speed motor operation. Furthermore, the proposed system is robust in motor losses and load variations. The proposed observer does not uses complicated observer gains and it is easy to setup for different types of motor. The convergence of the proposed observer is obtained using the Lyapunov theory. Hardware and software for experiment of the AC induction motor drive are introduced. The experimental results illustrate that fast torque and speed response with small torque ripples can be achieved. The proposed control scheme is suitable to the application fields that require high performance of torque response such as electric vehicles.