This paper presents position and vibration control of a flexible robot composed of two rigid and one flexible links. Position is controlled by the current applied to the DC motor armature. To control vibrations of the flexible structure, Shape Memory Alloys (SMA) are used. Due to phase transformations, the SMA can change its stiffness through temperature variation, considering and taking advantage of this characteristic the vibration control is done. Control is achieved via the State Dependent Ricatti Equations (SDRE) technique, which uses suboptimal control and system local stability search. The simulation results show the feasibility of the proposed control for the considered system.
This paper presents a two-degree-of-freedom robotic arm design with flexible joints driven by a DC Motor and controlled by a Magnetorheological (MR) Brake, considering a feedback control. The MR Brake is used to provide adjustable constraints in motion of the manipulator and compensate overshoot by interactions between the robot’s links and flexible joints of the motor drive mechanism. The torque of the MR Brake is obtained by the Radial Basis Function Neural Networks (RBFNN), which is a widely used class of neural networks for prediction or approximation of function. The RBFNN provides the nonlinear curve of hysteresis of MR brake to use torque. Two controllers were proposed to control the manipulator. The first one is obtained by feedback linearization control with the objective to remove the non-dependent terms of the state space equation. The second one is the feedback control obtained using the State-Dependent Riccati Equation (SDRE) with the objective of controlling the position of the manipulator and the torque applied on the MR brake. The numerical simulation results showed that the proposed control using both signal feedback linearization control and a feedback control signal by a DC Motor and MR Brake is effective to control the flexible joint manipulators.
In this work, the nonlinear dynamics of an Atomic Force Microscope (AFM) operating in tapping mode is investigated, considering the influence of squeeze film damping in fractional-order. Its influence plays an important role because the dynamics of the AFM can be led to different responses, e.g., periodic and chaotic motions, specially the influence of the derivative order when in fractional-order. In a way to characterize the type of behavior, the 0–1 test was used once this is a good tool to characterize fractional-order differential systems. In addition, the linear feedback control technique for fractional-order systems is applied to control the chaotic behaviors. Therefore, the results showed a nonlinear behavior presented by the AFM system. In addition, the feedback control technique was efficient to control the chaotic motion of the micro cantilever beam of the AFM, whose results included variation of parameters of the fractional derivative of the squeeze film damping.
This work proposes a pixel-classification approach for vessel segmentation in x-ray angiograms. The proposal uses textural features such as anisotropic diffusion, features based on the Hessian matrix, mathematical morphology and statistics. These features are extracted from the neighborhood of each pixel. The approach also uses the ELEMENT methodology, which consists of creating a pixelclassification controlled by region-growing where the result of the classification affects further classifications of pixels. The Random Forests classifier is used to predict whether the pixel belongs to the vessel structure. The approach achieved the best accuracy in the literature (95.48%) outperforming unsupervised state-of-the-art approaches.
Flexible links undergoing a slewing motion are widely found in aerospace structures such as satellites and robotic manipulators. In this kind of systems, the lighter the structure the better is its performance and more cost effective is the system. However, the positioning control of flexible structures is challenging because the flexibility may lead the system to vibrate in larger amplitudes, which makes the need of using actuators to control and reduce vibrations. An alternative for those actuators is the use of smart materials, as SMA (Shape Memory Alloys) to control vibrations of such structures. This work will present the angular positioning and vibration control of a flexible link. The angular position control is a torque driven by a DC motor controlled through a sliding modes control method. The system is considered as non-ideal, it means that the vibration of the flexible link accomplishes to the DC motor shaft. SMA actuators are coupled to the flexible link with the objective to reduce the vibration amplitudes and reducing so the settling time of the system. The SMA actuators are controlled through an electric voltage applied to its terminals by applying the Sliding modes control method. The dynamical equations of motion for the system are developed considering a dead zone nonlinearity of the DC motor and a phenomenological model for the SMA. The flexible link is modeled as a continuous structure and just the first vibration mode is analyzed. Numerical simulations results are presented to demonstrate the effectiveness of the sliding modes strategy for the positioning control of the DC motor and for the vibration suppression of the flexible link by using SMA actuators.
Renewable energy sources for vehicles have been the motivation of many researches around the world. The reduction of fossil fuels deposits and increase of the pollution in cities bring the need of more efficient and cleaner energy sources. In this way, this work will present the application of a compressed air engine applied to a bicycle. The engine is composed of two pneumatic cylinders connected to the bicycle wheel through a crank-connecting-rod mechanism. In order to control the velocity of the bicycle, a strategy of control composed of two controls was implemented: a feedback and a feedforward control. For feedback control, the StateDependent Riccati Equation (SDRE) control and also a proportional-derivative (PD) control are considered, considering three cases for velocity bicycle variation: 10 km/h, 20 km/h, and 30 km/h. The equations of motion of the system were obtained through the Lagrangian energy method. Numerical simulations were performed in order to analyze the dynamics of the system and the efficiency of the controllers.
This work presents an analysis of an ocean wave energy harvesting system. This system is composed of a direct current (DC) power generator attached at the middle-top of a floating platform. A pendulum is connected to the generator's shaft. It is considered that the ocean waves motion swings the platform in the vertical direction, which transfers energy to the pendulum, making possible to convert mechanical energy, induced by the ocean wave, into a rotational motion due the pendulum and after in electric energy due the generator. With the objective to optimize the harvested power, several analyses of the pendulum parameters, ocean wave amplitude and frequency were carried out. This work was based on the Brazilian's coast characteristics. Numerical and experimental results were performed which shows the efficiency of the conversion of mechanical energy provided by the pendulum into electric power.
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