1,720,998 research outputs found
A UGAS Sensorless Observer for Permanent Magnets Synchronous Machines including Estimation and Compensation of Dead-Times Effects
No full textIn this work, a novel sensorless observer is proposed for Permanent Magnet Synchronous Machines, formally dealing with stator voltage actuation non-idealities. Rotor speed, position and stator fluxes, as well as the unknown parameters of the voltage perturbations are reconstructed considering a fixed reference frame for both the machine and the voltage actuator non-linear effects. Stator currents and commands for the voltage actuator are assumed to be the only known signals. The estimation scheme is proven to be Uniformly Globally Asymptotically Stable by means of rigorous results from adaptive systems theory. The effectiveness of this solution is validated by realistic simulation tests, including a detailed model of the power converter. Discretization of the presented solution is addressed accurately. A comparison is provided to show the advantages of the proposed observer against a solution which does not adopt any mechanism to compensate for the mismatch between ideal and actuated stator voltages
A Hybrid Sensorless Observer for the Robust Global Asymptotic Flux Reconstruction of Permanent Magnet Synchronous Machines
Full text linkWe propose a hybrid sensorless observer for permanent magnet synchronous machines with global asymptotic stability guarantees. Exploiting the constraint of the rotor flux on a circle of unknown radius, we design an integrator system with periodic jumps triggered by a clock to generate a linear regression containing the flux estimation error. Then, a normalized projected gradient descent identifier provides the observer estimates. For the closed-loop system, it is shown that there exists a robustly globally asymptotically stable compact attractor, which, additionally, ensures zero estimation error if appropriate Persistency of Excitation (PE) conditions are satisfied. In this respect, sufficient conditions ensuring PE are provided for the angular speed and the clock period
Condition monitoring of ball bearings using estimated ar models as logistic regression features
No full textBearings are one of the most common components in automatic machines. Diagnosis and prognosis of their working condition is crucial for minimization of downtime and maintenance costs. Different approaches may be adopted to either solve or mitigate the problem of identifying incipient faults during machinery operations. In this paper, we propose a simple and efficient yet effective method to solve this problem by exploiting the edge-computing capabilities of PLCs. Accelerometer signals are modeled as AutoRegressive (AR) processes whose coefficient are used as features for machine learning, based on logistic regression algorithm (LR), to perform Fault Detection and Isolation (FDI). Estimation and prediction are both implementable on-board the PLC, while machine learning can be carried out remotely, in a cloud computing perspective. The exploitation of AR modelling gives a simple and inherent methodology for feature selection. We apply the procedure to the Case Western Reserve University database, a widely known and used benchmark, to highlight its performance with respect to similar fault recognition techniques
A novel control solution for improved trajectory tracking and LVRT performance in DFIG-based wind turbines
Full text linkThis paper presents a new control strategy for the rotor side converter of Doubly-Fed Induction Generator based Wind Turbine systems, under severe voltage dips. The main goal is to fulfill the Low Voltage Ride Through performance, required by modern grid codes. In this respect, the key point is to limit oscillations (particularly on rotor currents) triggered by line faults, so that the system keeps operating with graceful behavior. To this aim, a suitable feedforward-feedback control solution is proposed for the DFIG rotor side. The feedforward part exploits oscillation-free reference trajectories, analytically derived for the system internal dynamics. State feedback, designed accounting for control voltage limits, endows the system with robustness and further tame oscillations during faults. Moreover, improved torque and stator reactive power tracking during faults is achieved, proposing an exact mapping between such quantities and rotor-side currents, which are conventionally used as controlled outputs. Numerical simulations are provided to validate the capability of the proposed approach to effectively cope with harsh faults
Taming Edge Computing for Hard Real-Time Advanced Control of Mechatronic Systems
No full textIn novel mechatronics enabled by smart structures and materials, servomechanisms are becoming increasingly complex, requiring computationally intensive advanced control algorithms and diagnostic tools to fully exploit their potential. This calls for a significant increase in computational power while guaranteeing hard real-time features. In this work, we propose to address such an issue by adopting recently-emerged edge-computing solutions exploiting low-cost multicore that combine microcontrollers and microprocessors to boost the computational capability. However, such platforms are usually endowed with nonreal-time software infrastructure, assigning a dominant role to microprocessors and leading to large overheads and unpredictability. Therefore, to tame them for hard real time, we first lighten the infrastructure to enable one or more microprocessors to handle computations with minimal overhead and jitter. Then, we designate a microcontroller as the platform master of time and tasks, off-loading the heavy computations to the "relieved" microprocessor cores, acting now as computational slaves. We assess the potentials of this approach with a basic test using a demanding control algorithm as a benchmark, choosing the STM32MP157 as the reference platform and using the Jailhouse hypervisor to adapt one of its microprocessor cores for hard real-time tasks
Robust control of a throttle body for drive by wire operation of automotive engines
No full textIn recent years, ever more stringent requirements in terms of emissions control, driveability, and safety of automobiles have led to the development of the drive by wire (DBW) concept, a new architecture for engine control systems, with the purpose of managing air, fuel and ignition in an integrated way. The throttle control plays an important role in the development of DBW systems. Despite its apparent simplicity, the position control of the throttle valve is quite a complex problem, due to application constraints and system characteristics. Very high robustness must be linked with limited cost, as required by a mass production device. A cascaded control structure including a nonlinear trajectory generator filter is adopted, allowing each different control problem to be solved with the most suitable control algorithm and implementation technology. In this regard, the use of variable structure control techniques is the key element to reaching the solution. Extensive simulation tests are reported to show the performance of the proposed control algorithm. A throttle step from 0.5° to 89.5° indicates good position tracking under realistic operating conditions, with a position error smaller than 1°. The same simulation is performed at a battery voltage of 9 V to check the controller robustness. A prototype controller is presented. The experimental implementation of the controller for a step from 2.5° to 85.5° indicates a very smooth position trajectory with a maximum dynamic position error of 7°. A small throttle step from 1° to 7° (which contains the nonlinearity of the limp home mode spring) was also tested and resulted in very good position response with the maximum position error of 2°. Application specifications are fully satisfied both in terms of control performance and controller cost
Periodic motion optimization for an underactuated mechanical system through synergistic structure-control design
No full textIn this work, we present the integrated structure-control design of a 2-DOF underactuated mechanical system, aiming to achieve a periodic motion of the end-effector. The desired behavior is generated via input-output feedback linearization, followed by structural optimization of the zero dynamics. Inspired by recent works on the control-oriented design of multibody systems, we define a simulation-based optimization problem where the response of the mechanism is shaped through relevant structural parameters. In particular, adjusting the stiffness and the mass distribution of the system, we match the periodic reference with a specific orbit of the zero dynamics, while also penalizing the linearizing input. With the adoption of the proposed strategy, we show that it is possible to reach a desirable trade-off between input energy reduction and periodic motion accuracy. Once an optimal trajectory of the zero dynamics is found, the control design is completed with established orbital stabilization techniques, ensuring a robust oscillatory behavior
Low-input accurate periodic motion of an underactuated mechanism: Mass distribution and nonlinear spring shaping
No full textThis work presents a control-oriented structural design approach for a 2-DOF underactuated mechanical system, with the purpose of generating an optimal oscillatory behavior of the end-effector. To achieve the desired periodic motion, we propose to adjust the dynamic response of the mechanism by selecting its mass distribution and the characteristic of a nonlinear spring. In particular, we introduce a two-step optimization strategy to shape the system's zero dynamics, obtained via input-output linearization. The first part of the procedure aims to minimize the root-mean-square value of the input torque by optimizing the mechanism's mass distribution. In this context, we show that a perfect matching with the desired trajectory can be reached by assuming the ability to design an arbitrary shape of the system's elastic properties. Then, in order to favor a simpler physical implementation of the structure, we dedicate the second optimization step to the piecewise linear approximation of the previously defined stiffness characteristic. The proposed procedure is finally tested in detailed numerical simulations, confirming its effectiveness in generating a complex and efficient periodic motion
Robust Global Asymptotic Stabilization of Linear Cascaded Systems With Hysteretic Interconnection
Full text linkWe address the problem of setpoint regulation for cascaded minimum-phase linear systems interconnected through a scalar hysteresis, modeled as a Prandtl-Ishlinskii operator. Employing well-posed constrained differential inclusions to represent the hysteretic dynamics, we formulate the control problem in terms of stabilization of a compact set of equilibria depending on the hysteresis states. For our design, we firstly consider a proportional-integral controller for linear systems with hysteretic input, and provide model-free sufficient conditions based on high-gain arguments for closed-loop stability. Then, the controller is dynamically extended to obtain an inversion-free stabilizer of the overall cascade. For the presented schemes, we prove robust global asymptotic stability of a compact set that ensures setpoint regulation, regardless of the hysteresis states
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