921 research outputs found

    The generation of dual wavelength pulse fiber laser using fiber bragg grating

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    A stable simple generation of dual wavelength pulse fiber laser on experimental method is proposed and demonstrated by using Figure eight circuit diagram. The generation of dual wavelength pulse fiber laser was proposed using fiber Bragg gratings (FBGs) with two different central wavelengths which are 1550 nm and 1560 nm. At 600 mA (27.78 dBm) of laser diode, the stability of dual wavelength pulse fiber laser appears on 1550 nm and 1560 nm with the respective peak powers of -54.03 dBm and -58.00 dBm. The wavelength spacing of the spectrum is about 10 nm while the signal noise to ratio (SNR) for both peaks are about 8.23 dBm and 9.67 dBm. In addition, the repetition rate is 2.878 MHz with corresponding pulse spacing of about 0.5 μs, is recorded

    Cascaded control for balancing an inverted pendulum on a flying quadrotor

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    SUMMARYThis paper is focused on the flying inverted pendulum problem, i.e., how to balance a pendulum on a flying quadrotor. After analyzing the system dynamics, a three loop cascade control strategy is proposed based on active disturbance rejection control (ADRC). Both the pendulum balancing and the trajectory tracking of the flying quadrotor are implemented by using the proposed control strategy. A simulation platform of 3D mechanical systems is deployed to verify the control performance and robustness of the proposed strategy, including a comparison with a Linear Quadratic Controller (LQR). Finally, a real quadrotor is flying with a pendulum to demonstrate the proposed method that can keep the system at equilibrium and show strong robustness against disturbances.</jats:p

    Decentralized adaptive partitioned approximation control of high degrees-of-freedom robotic manipulators considering three actuator control modes

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    International audiencePartitioned approximation control is avoided in most decentralized control algorithms; however, it is essential to design a feedforward control term for improving the tracking accuracy of the desired references. In addition, consideration of actuator dynamics is important for a robot with high-velocity movement and highly varying loads. As a result, this work is focused on decentralized adaptive partitioned approximation control for complex robotic systems using the orthogonal basis functions as strong approximators. In essence, the partitioned approximation technique is intrinsically decentralized with some modifications. Three actuator control modes are considered in this study: (i) a torque control mode in which the armature current is well controlled by a current servo amplifier and the motor torque/current constant is known, (ii) a current control mode in which the torque/current constant is unknown, and (iii) a voltage control mode with no current servo control being available. The proposed decentralized control law consists of three terms: the partitioned approximation-based feedforward term that is necessary for precise tracking, the high gain-based feedback term, and the adaptive sliding gain-based term for compensation of modeling error. The passivity property is essential to prove the stability of local stability of the individual subsystem with guaranteed global stability. Two case studies are used to prove the validity of the proposed controller: a two-link manipulator and a six-link biped robot

    Inverse model based control for a twin rotor system

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    The use of active control technique has intensified in various control applications, particularly in the field of aircraft systems. A laboratory set-up system which resembles the behaviour of a helicopter, namely twin rotor multi-input multioutput system (TRMS) is used as an experimental rig in this research. This paper presents an investigation using inverse model control for the TRMS. The control techniques embraced in this work are direct inverse-model control, augmented PID with feedforward inverse-model control and augmented PID with feedback inverse-model control. Particle swarm optimization (PSO) method is used to tune the parameter of PID controller. To demonstrate the applicability of the methods, a simulated hovering motion of the TRMS, derived from experimental data is considered. The proposed inverse model based controller is shown to be capable of handling both systems dynamic as well as rigid body motion of the system, providing good overall system performance

    Virtual Inertia Emulation to Improve Dynamic Frequency Stability of Low Inertia Microgrids

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    Due to low inertia and the intermittent nature of photovoltaic systems, dynamic frequency stability issues arise in microgrids with large photovoltaic systems. This limits the maximum amount of photovoltaic systems that can be penetrated in the microgrid. In order to increase the penetration of photovoltaic systems, the dynamic frequency controller, that is faster than the primary frequency controller (governor control) needs to be added in the microgrid system. For dynamic frequency control, inertial response can be provided from the energy storage system (such as battery, ultra-capacitor, photovoltaic system, etc.), which is termed as virtual inertia. A virtual inertia can be defined as the combination of an energy storage system, a power electronics converter and a proper control algorithm that improves the dynamic frequency stability of the microgrid. A virtual inertia supplies or absorbs the active power to and from the energy storage system to improve the dynamic frequency stability. This thesis presents the design and implementation of a hardware prototype of 1 kW virtual inertia in a microgrid with a real diesel generator and a load. For a step change in load, the virtual inertia improved the frequency response of the system from 57.39 Hz to 58.03 Hz. This improvement in frequency response proves the concept of existing proportional derivative based virtual inertia experimentally. With the addition of virtual inertia, the frequency of the system returns to the nominal frequency slower. Once the primary controller (governor control) of the system takes the action to regulate the frequency, virtual inertia no longer needs to add inertia to the system. So the dynamics of the VI needs to be improved so that the frequency returns to nominal frequency faster. This thesis also proposes an online learning controller based virtual inertia using adaptive dynamic programming that learns online and improves the dynamics of the controller of existing VI. The output of this controller supplements the output of the existing proportional derivative controller of virtual inertia. The supplementary controller is trained to increase the dynamics of the outer controller and to bring the system frequency to nominal frequency faster. Due to faster dynamics, the net energy delivered by the VI can be reduced significantly and improve the total possible discharge cycles from the battery. For performance evaluation, the proposed controller was implemented in a microgrid with a photovoltaic system, a diesel generator and a variable load. With the proposed controller, the frequency of the system returned to nominal frequency faster. The net energy delivered by the proposed controller in a photovoltaic diesel generator microgrid was 46.14% of the net energy delivered by the existing virtual inertia. Due to the decrement in the total energy delivered, the total number of possible battery discharge cycles with ADP based VI was 2.17 times of the total number of possible battery discharge cycles from VI

    Dynamic nonlinear inverse-model based control of a twin rotor system using adaptive neuro-fuzzy inference system

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    A dynamic control system design has been a great demand in the control engineering community, with many applications particularly in the field of flight control. This paper presents investigations into the development of a dynamic nonlinear inverse-model based control of a twin rotor multi-input multi-output system (TRMS). The TRMS is an aerodynamic test rig representing the control challenges of modern air vehicle. A model inversion control with the developed adaptive model is applied to the system. An adaptive neuro-fuzzy inference system (ANFIS) is augmented with the control system to improve the control response. To demonstrate the applicability of the methods, a simulated hovering motion of the TRMS, derived from experimental data is considered in order to evaluate the tracking properties and robustness capacities of the inverse- model control technique

    A Hybrid Controller for Stability Robustness, Performance Robustness, and Disturbance Attenuation of a Maglev System

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    Devices using magnetic levitation (maglev) offer the potential for friction-free, high-speed, and high-precision operation. Applications include frictionless bearings, high-speed ground transportation systems, wafer distribution systems, high-precision positioning stages, and vibration isolation tables. Maglev systems rely on feedback controllers to maintain stable levitation. Designing such feedback controllers is challenging since mathematically the electromagnetic force is nonlinear and there is no local minimum point on the levitating force function. As a result, maglev systems are open-loop unstable. Additionally, maglev systems experience disturbances and system parameter variations (uncertainties) during operation. A successful controller design for maglev system guarantees stability during levitating despite system nonlinearity, and desirable system performance despite disturbances and system uncertainties. This research investigates five controllers that can achieve stable levitation: PD, PID, lead, model reference control, and LQR/LQG. It proposes an acceleration feedback controller (AFC) design that attenuates disturbance on a maglev system with a PD controller. This research proposes three robust controllers, QFT, Hinf , and QFT/Hinf , followed by a novel AFC-enhanced QFT/Hinf (AQH) controller. The AQH controller allows system robustness and disturbance attenuation to be achieved in one controller design. The controller designs are validated through simulations and experiments. In this research, the disturbances are represented by force disturbances on the levitated object, and the system uncertainties are represented by parameter variations. The experiments are conducted on a 1 DOF maglev testbed, with system performance including stability, disturbance rejection, and robustness being evaluated. Experiments show that the tested controllers can maintain stable levitation. Disturbance attenuation is achieved with the AFC. The robust controllers, QFT, Hinf , QFT/ Hinf, and AQH successfully guarantee system robustness. In addition, AQH controller provides the maglev system with a disturbance attenuation feature. The contributions of this research are the design and implementation of the acceleration feedback controller, the QFT/ Hinf , and the AQH controller. Disturbance attenuation and system robustness are achieved with these controllers. The controllers developed in this research are applicable to similar maglev systems
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