969 resultados para open loop


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Toward our comprehensive understanding of legged locomotion in animals and machines, the compass gait model has been intensively studied for a systematic investigation of complex biped locomotion dynamics. While most of the previous studies focused only on the locomotion on flat surfaces, in this article, we tackle with the problem of bipedal locomotion in rough terrains by using a minimalistic control architecture for the compass gait walking model. This controller utilizes an open-loop sinusoidal oscillation of hip motor, which induces basic walking stability without sensory feedback. A set of simulation analyses show that the underlying mechanism lies in the "phase locking" mechanism that compensates phase delays between mechanical dynamics and the open-loop motor oscillation resulting in a relatively large basin of attraction in dynamic bipedal walking. By exploiting this mechanism, we also explain how the basin of attraction can be controlled by manipulating the parameters of oscillator not only on a flat terrain but also in various inclined slopes. Based on the simulation analysis, the proposed controller is implemented in a real-world robotic platform to confirm the plausibility of the approach. In addition, by using these basic principles of self-stability and gait variability, we demonstrate how the proposed controller can be extended with a simple sensory feedback such that the robot is able to control gait patterns autonomously for traversing a rough terrain. © 2010 Springer Science+Business Media, LLC.

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Mobility of wheeled or legged machines can be significantly increased if they are able to move from a solid surface into a three-dimensional space. Although that may be achieved by addition of flying mechanisms, the payload fraction will be the limiting factor in such hybrid mobile machines for many applications. Inspired by spiders producing draglines to assist locomotion, the paper proposes an alternative mobile technology where a robot achieves locomotion from a solid surface into a free space. The technology resembles the dragline production pathway in spiders to a technically feasible degree and enables robots to move with thermoplastic spinning of draglines. As an implementation, a mobile robot has been prototyped with thermoplastic adhesives as source material of the draglines. Experimental results show that a dragline diameter range of 1.17-5.27 mm was achievable by the 185 g mobile robot in descending locomotion from the solid surface of a hanging structure with a power consumption of 4.8 W and an average speed of 5.13 cm min(-1). With an open-loop controller consisting of sequences of discrete events, the robot has demonstrated repeatable dragline formation with a relative deviation within -4% and a length close to the metre scale.

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A novel CMOS-based preamplifier for amplifying brain neural signal obtained by scalp electrodes in brain-computer interface (BCI) is presented in this paper. By means of constructing effective equivalent input circuit structure of the preamplifier, two capacitors of 5 pF are included to realize the DC suppression compared to conventional preamplifiers. Then this preamplifier is designed and simulated using the standard 0.6 mu m MOS process technology model parameters with a supply voltage of 5 volts. With differential input structures adopted, simulation results of the preamplifier show that the input impedance amounts to more than 2 Gohm with brain neural signal frequency of 0.5 Hz-100 Hz. The equivalent input noise voltage is 18 nV/Hz(1/2). The common mode rejection ratio (CMRR) of 112 dB and the open-loop differential gain of 90 dB are achieved.

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CoFe2O4 nanoparticles prepared by chemical coprecipitation method in a magnetic field exhibit novel magnetic properties. The average particle diameter was about 2 nm and larger depending on the post annealing temperature. Magnetization measurements indicate that smaller nanoparticles are superparamagnetic above their respective blocking temperatures. In the blocked state, these nanoparticles exhibit interesting behaviors in the magnetic hysteresis measurements. Constricted, or wasp waisted with extremely narrow waist, hysteresis curves have been observed in the magnetization versus field sweeps. For larger nanoparticles, the room temperature hysteresis is typical of a ferromagnet with an open loop, but the loop closes at lower temperature. The novel magnetic behavior is attributed to the directional order of Co ions and vacancies in CoFe2O4 established during the coprecipitation of the nanoparticles under an applied field.

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以利用线加速度传感器实际测量转动关节的加速度为基础 ,分析了机器人关节加速度反馈控制的开环模型 ,以及影响其闭环稳定性的主要因素 ;提出了闭环控制策略的设计准则 .在一台三自由度直接驱动机器人上的实验结果证明了该文分析的正确性 ,与不具备加速度反馈控制时的实验结果相比较 ,显示出这种方法的有效性

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New compensation methods are presented that can greatly reduce the slit errors (i.e. transition location errors) and interval errors induced due to non-idealities in optical incremental encoders (square-wave). An M/T-type, constant sample-time digital tachometer (CSDT) is selected for measuring the velocity of the sensor drives. Using this data, three encoder compensation techniques (two pseudoinverse based methods and an iterative method) are presented that improve velocity measurement accuracy. The methods do not require precise knowledge of shaft velocity. During the initial learning stage of the compensation algorithm (possibly performed in-situ), slit errors/interval errors are calculated through pseudoinversebased solutions of simple approximate linear equations, which can provide fast solutions, or an iterative method that requires very little memory storage. Subsequent operation of the motion system utilizes adjusted slit positions for more accurate velocity calculation. In the theoretical analysis of the compensation of encoder errors, encoder error sources such as random electrical noise and error in estimated reference velocity are considered. Initially, the proposed learning compensation techniques are validated by implementing the algorithms in MATLAB software, showing a 95% to 99% improvement in velocity measurement. However, it is also observed that the efficiency of the algorithm decreases with the higher presence of non-repetitive random noise and/or with the errors in reference velocity calculations. The performance improvement in velocity measurement is also demonstrated experimentally using motor-drive systems, each of which includes a field-programmable gate array (FPGA) for CSDT counting/timing purposes, and a digital-signal-processor (DSP). Results from open-loop velocity measurement and closed-loop servocontrol applications, on three optical incremental square-wave encoders and two motor drives, are compiled. While implementing these algorithms experimentally on different drives (with and without a flywheel) and on encoders of different resolutions, slit error reductions of 60% to 86% are obtained (typically approximately 80%).

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We consider the optimum design of pilot-symbol-assisted modulation (PSAM) schemes with feedback. The received signal is periodically fed back to the transmitter through a noiseless delayed link and the time-varying channel is modeled as a Gauss-Markov process. We optimize a lower bound on the channel capacity which incorporates the PSAM parameters and Kalman-based channel estimation and prediction. The parameters available for the capacity optimization are the data power adaptation strategy, pilot spacing and pilot power ratio, subject to an average power constraint. Compared to the optimized open-loop PSAM (i.e., the case where no feedback is provided from the receiver), our results show that even in the presence of feedback delay, the optimized power adaptation provides higher information rates at low signal-to-noise ratios (SNR) in medium-rate fading channels. However, in fast fading channels, even the presence of modest feedback delay dissipates the advantages of power adaptation.

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A simple approach is proposed for disturbance attenuation in multivariable linear systems via dynamical output compensators based on complete parametric eigenstructure assignment. The basic idea is to minimise the H-2 norm of the disturbance-output transfer function using the design freedom provided by eigenstructure assignment. For robustness, the closed-loop system is restricted to be nondefective. Besides the design parameters, the closed-loop eigenvalues are also optimised within desired regions on the left-half complex plane to ensure both closed-loop stability and dynamical performance. With the proposed approach, additional closed-loop specifications can be easily achieved. As a demonstration, robust pole assignment, in the sense that the closed-loop eigenvalues are as insensitive as possible to open-loop system parameter perturbations, is treated. Application of the proposed approach to robust control of a magnetic bearing with a pair of opposing electromagnets and a rigid rotor is discussed.

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In this paper, gain-bandwidth (GB) trade-off associated with analog device/circuit design due to conflicting requirements for enhancing gain and cutoff frequency is examined. It is demonstrated that the use of a nonclassical source/drain (S/D) profile (also known as underlap channel) can alleviate the GB trade-off associated with analog design. Operational transconductance amplifier (OTA) with 60 nm underlap S/D MOSFETs achieve 15 dB higher open loop voltage gain along with three times higher cutoff frequency as compared to OTA with classical nonunderlap S/D regions. Underlap design provides a methodology for scaling analog devices into the sub-100 nm regime and is advantageous for high temperature applications with OTA, preserving functionality up to 540 K. Advantages of underlap architecture over graded channel (GC) or laterally asymmetric channel (LAC) design in terms of GB behavior are demonstrated. Impact of transistor structural parameters on the performance of OTA is also analyzed. Results show that underlap OTAs designed with spacer-to-straggle ratio of 3.2 and operated below a bias current of 80 microamps demonstrate optimum performance. The present work provides new opportunities for realizing future ultra wide band OTA design with underlap DG MOSFETs in silicon-on-insulator (SOI) technology. Index Terms—Analog/RF, double gate, gain-bandwidth product, .

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The presence of mobile ions complicates the implementation of voltage-modulated scanning probe microscopy techniques such as Kelvin probe force microscopy (KPFM). Overcoming this technical hurdle, however, provides a unique opportunity to probe ion dynamics and electrochemical processes in liquid environments and the possibility to unravel the underlying mechanisms behind important processes at the solid–liquid interface, including adsorption, electron transfer and electrocatalysis. Here we describe the development and implementation of electrochemical force microscopy (EcFM) to probe local bias- and time-resolved ion dynamics and electrochemical processes at the solid–liquid interface. Using EcFM, we demonstrate contact potential difference measurements, consistent with the principles of open-loop KPFM operation. We also demonstrate that EcFM can be used to investigate charge screening mechanisms and electrochemical reactions in the probe–sample junction. We further establish EcFM as a force-based imaging mode, allowing visualization of the spatial variability of sample-dependent local electrochemical properties.

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Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

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This article proposes a closed-loop control scheme based on joint-angle feedback for cable-driven parallel manipulators (CDPMs), which is able to overcome various difficulties resulting from the flexible nature of the driven cables to achieve higher control accuracy. By introducing a unique structure design that accommodates built-in encoders in passive joints, the seven degrees of freedom (7-DOF) CDPM can obtain joint angle values without external sensing devices, and it is used for feedback control together with a proper closed-loop control algorithm. The control algorithm has been derived from the time differential of the kinematic formulation, which relates the joint angular velocities to the time derivative of cable lengths. In addition, the Lyapunov stability theory and Monte Carlo method have been used to mathematically verify the self-feedback control law that has tolerance for parameter errors. With the aid of co-simulation technique, the self-feedback closed-loop control is applied on a 7-DOF CDPM and it shows higher motion accuracy than the one with an open-loop control. The trajectory tracking experiment on the motion control of the 7-DOF CDPM demonstrated a good performance of the self-feedback control method.

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In the production process of polyethylene terephthalate (PET) bottles, the initial temperature of preforms plays a central role on the final thickness, intensity and other structural properties of the bottles. Also, the difference between inside and outside temperature profiles could make a significant impact on the final product quality. The preforms are preheated by infrared heating oven system which is often an open loop system and relies heavily on trial and error approach to adjust the lamp power settings. In this paper, a radial basis function (RBF) neural network model, optimized by a two-stage selection (TSS) algorithm combined with partial swarm optimization (PSO), is developed to model the nonlinear relations between the lamp power settings and the output temperature profile of PET bottles. Then an improved PSO method for lamp setting adjustment using the above model is presented. Simulation results based on experimental data confirm the effectiveness of the modelling and optimization method.

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Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial