16,823 research outputs found

    A survey on fractional order control techniques for unmanned aerial and ground vehicles

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    In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

    A scalable hardware and software control apparatus for experiments with hybrid quantum systems

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    Modern experiments with fundamental quantum systems - like ultracold atoms, trapped ions, single photons - are managed by a control system formed by a number of input/output electronic channels governed by a computer. In hybrid quantum systems, where two or more quantum systems are combined and made to interact, establishing an efficient control system is particularly challenging due to the higher complexity, especially when each single quantum system is characterized by a different timescale. Here we present a new control apparatus specifically designed to efficiently manage hybrid quantum systems. The apparatus is formed by a network of fast communicating Field Programmable Gate Arrays (FPGAs), the action of which is administrated by a software. Both hardware and software share the same tree-like structure, which ensures a full scalability of the control apparatus. In the hardware, a master board acts on a number of slave boards, each of which is equipped with an FPGA that locally drives analog and digital input/output channels and radiofrequency (RF) outputs up to 400 MHz. The software is designed to be a general platform for managing both commercial and home-made instruments in a user-friendly and intuitive Graphical User Interface (GUI). The architecture ensures that complex control protocols can be carried out, such as performing of concurrent commands loops by acting on different channels, the generation of multi-variable error functions and the implementation of self-optimization procedures. Although designed for managing experiments with hybrid quantum systems, in particular with atom-ion mixtures, this control apparatus can in principle be used in any experiment in atomic, molecular, and optical physics.Comment: 10 pages, 12 figure

    Proportional-Integral-Plus Control Strategy of an Intelligent Excavator

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    This article considers the application of Proportional-Integral-Plus (PIP) control to the Lancaster University Computerised Intelligent Excavator (LUCIE), which is being developed to dig foundation trenches on a building site. Previous work using LUCIE was based on the ubiquitous PI/PID control algorithm, tuned on-line, and implemented in a rather ad hoc manner. By contrast, the present research utilizes new hardware and advanced model-based control system design methods to improve the joint control and so provide smoother, more accurate movement of the excavator arm. In this article, a novel nonlinear simulation model of the system is developed for MATLAB/SIMULINK, allowing for straightforward refinement of the control algorithm and initial evaluation. The PIP controller is compared with a conventionally tuned PID algorithm, with the final designs implemented on-line for the control of dipper angle. The simulated responses and preliminary implementation results demonstrate the feasibility of the approach

    A Hybrid Control Approach for the Swing Free Transportation of a Double Pendulum with a Quadrotor

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    In this article, a control strategy approach is proposed for a system consisting of a quadrotor transporting a double pendulum. In our case, we attempt to achieve a swing free transportation of the pendulum, while the quadrotor closely follows a specific trajectory. This dynamic system is highly nonlinear, therefore, the fulfillment of this complex task represents a demanding challenge. Moreover, achieving dampening of the double pendulum oscillations while following a precise trajectory are conflicting goals. We apply a proportional derivative (PD) and a model predictive control (MPC) controllers for this task. Transportation of a multiple pendulum with an aerial robot is a step forward in the state of art towards the study of the transportation of loads with complex dynamics. We provide the modeling of the quadrotor and the double pendulum. For MPC we define the cost function that has to be minimized to achieve optimal control. We report encouraging positive results on a simulated environmentcomparing the performance of our MPC-PD control circuit against a PD-PD configuration, achieving a three fold reduction of the double pendulum maximum swinging angle.This work has been partially supported by FEDER funds through MINECO project TIN2017-85827-P, and project KK-202000044 of the Elkartek 2020 funding program of the Basque Government. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 777720

    Fuzzy-PID in BLDC Motor Speed Control Using MATLAB/Simulink

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    Brushless DC motors (BLDC) are one of the most widely used types of DC motors, both in the industrial and automotive fields. BLDC motor was chosen because it has many advantages over other types of electric motors. However, in its application in the market, most of the control systems used in BLDC motors still use conventional controls. This conventional method is easy and simple to apply but has many weaknesses, one example is that if the system state changes, then the parameters of the PID must also be changed so that static and dynamic performance will decrease, causing slow response and frequent oscillations. In this study, the design and simulation of a speed control system for BLDC motors using the Fuzzy-PID method were carried out. The research method is performed through simulation with Matlab / Simulink. The simulation is carried out by providing a speed setpoint input of 650 rpm and used 2 methods, namely Fuzzy-PID Logic and Pi conventional method which was carried out for 1 second. The test results show that the Fuzzy-PID control can provide better and more stable performance than the conventional PI control. The use of Fuzzy-PID control can reduce speed fluctuation and torque stability so that the BLDC motor can operate more efficiently and reliably
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