Effective Compensation Method Research Articles

Phase Noise Effects on OFDM Chirp Communication Systems: Characteristics and Compensation

Orthogonal frequency-division multiplexing (OFDM) chirp waveforms are an attractive candidate to be a dual-function signal scheme for the joint radar and communication systems. OFDM chirp signals can not only be employed to transmit communication data through classic phase modulation, but also can perform radar detection by applying linear frequency modulation for subcarriers. However, the performance of the OFDM chirp communication system under the phase noise environment still remains uninvestigated. This paper tries to discuss the influence of phase noise on OFDM chirp communication systems and proposes effective phase noise estimation and compensation methods. We find that the phase noise effect on OFDM chirp communication systems consists of a common phase error (CPE) and an inter-carrier interference (ICI). If not compensated, the performance of the dual-function systems can be seriously degraded. In particular, an exact expression for the signal-plus-interference to noise ratio (SINR) for the OFDM chirp communication system is derived and some critical parameters are analyzed to exhibit the phase noise effects on system performance. Moreover, two low-complexity estimation approaches, maximum likelihood (ML) and linear minimum mean square error (LMMSE), as well as two compensation approaches, the de-correlation and cancellation algorithms, are respectively utilized to eliminate the phase noise impairment. Finally, the phase noise effects and the effectiveness of the compensation approach are verified by extensive numerical results.

Final state control-based active compensation for backlash in vibration suppression of automobile powertrain

This paper proposes an effective backlash compensation method based on the final state control (FSC) for active vibration control of an automobile powertrain. Transient vibration of the powertrain caused by sudden changes in the engine torque significantly degrades the driving performance and driver comfort. In addition, the nonlinear characteristics owing to the backlash increase the adverse effects of these oscillations. To suppress the transient vibration of the powertrain, a controller is designed based on the mixed H2/H∞ control theory. Subsequently, to adjust for the vibration amplification owing to the backlash, we propose the application of a shock-reducing controller based on the FSC. Linearly decreasing the inertia weight in particle swarm optimisation (LDWPSO) was applied to the design of this controller and parameters were optimised. Finally, simulations were conducted using the control method; the controller could prevent the occurrence of shocks owing to the gear collisions and achieved smooth an acceleration.

A Inverter Dead-time Compensation Method Based on Phase current Polarity Determination and Voltage Partitioning

The introduction of the dead time of the inverter solves the straight-arm conduction problem of the upper and lower power devices of the inverter, but also leads to the deviation of the actual output voltage of the inverter from the given voltage. Dead time increases the harmonic components of phase voltage and phase current, which is also an important factor leading to motor torque ripple. In this paper, the mechanism of the deviation of phase voltage and phase current caused by the dead time of voltage space vector modulation is analyzed, and the effect of dead time on phase voltage and phase current harmonic components is studied. A simple and effective dead time compensation method based on phase voltage division and phase current polarity determination is proposed to directly compensate the dead time. This method can suppress the current harmonic and torque ripple in the running state of the motor, and can greatly simplify the calculation process of the traditional dead time compensation method. Through the system modeling and simulation, it is verified that the method can significantly improve the current waveform distortion, and has good practical value.

A Sensor Drift Compensation Method with a Masked Autoencoder Module

Deep learning algorithms are widely used for pattern recognition in electronic noses, which are sensor arrays for gas mixtures. One of the challenges of using electronic noses is sensor drift, which can degrade the accuracy of the system over time, even if it is initially trained to accurately estimate concentrations from sensor data. In this paper, an effective drift compensation method is introduced that adds sensor drift information during training of a neural network that estimates gas concentrations. This is achieved by concatenating a calibration feature vector with sensor data and using this as an input to the neural network. The calibration feature vector is generated via a masked-autoencoder-based feature extractor trained with transfer samples, and acts as a prompt to convey sensor drift information. Our method is tested on a 3-year gas sensor array drift dataset, showing that a neural network using our method performs better than other models, including a network with additional fine tuning, demonstrating that our method is efficient at compensating for sensor drift. In this study, the effectiveness of using prompts for network training is confirmed, which better compensates for drifts in new sensor signals than network fine-tuning.

Research on dynamic calibration and compensation method of strain-gauge type force sensor

Purpose This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals. Design/methodology/approach The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals. Findings The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%. Originality/value An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.

Hysteresis Compensation-Based Intelligent Control for Pneumatic Artificial Muscle-Driven Humanoid Robot Manipulators With Experiments Verification

Pneumatic artificial muscles (PAMs), as a kind of soft actuators, can overcome compliance limitations of traditional rigid actuators to improve the adaptability of robots. However, some inherent strong nonlinearities and time-varying properties of PAMs, e.g., complex hysteresis and creep, may lead to a lot of control problems. In addition, PAM-driven systems are also faced with input constraints (e.g., deadzones, saturations, and unidirectional inputs), unknown/unmodeled dynamics and external disturbances, which badly degrade the control performance and even cause accidents. Therefore, this paper proposes a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">new</i> hysteresis compensation-based immersion and invariance (I&I) adaptive fuzzy control method for PAM-driven humanoid robot manipulators, which can approximate the unknown functions and estimate the unknown parameters. To our knowledge, this is the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">first</i> method for PAM-driven systems that compensates for system nonlinearities ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">not only</i> complex hysteresis, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">but also</i> input deadzones) by utilizing the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">prior</i> information in inverse hysteresis models, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">simultaneously</i> estimates the unknown functions and parameters by designing a fuzzy update law and a parameter update law based on I&I methodology, respectively, which increases the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">control frequency</i> of systems and improves tracking performance during high-speed motions. Finally, we apply the proposed approach on a self-built PAM-driven humanoid robot manipulator to validate its effectiveness and robustness. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Faced with the practical requirements of robots that interact closely with humans, improving the adaptability and compliance of robots by utilizing soft actuators, such as PAMs, can satisfy current demands. Moreover, PAMs also have many expective characteristics (e.g., high power density, light material, low costs, clean power, etc.), which makes PAMs occupy an important status in the field of soft robotics. However, unknown parameters/structures, strong nonlinearities, and input constraints, may badly degrade the control performance of PAMs. Based on the above characteristics, this paper proposes a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">new</i> hysteresis compensation-based adaptive fuzzy controller for PAM-driven humanoid robot manipulators, which realizes <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">accurate tracking</i> control during high-speed motions by using inverse hysteresis models to compensate for strong nonlinearities in PAMs, and a fuzzy update law and a parameter update law based on I&I methodology are utilized to estimate unknown parameters/structures. In addition, the proposed controller can <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">simultaneously</i> compensate for input deadzones by utilizing the hysteresis information, which improves the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">control frequency</i> of the manipulators, and can rapidly suppress tracking errors. Experimental results are provided to validate the effectiveness of the presented method. In the future, more effective compensation methods, such as rate-dependent hysteresis models, will further be carried out to compensate for system nonlinearities.

A Two-Layer Trajectory Tracking Control Scheme of Manipulator Based on ELM-SMC for Autonomous Robotic Vehicle

With the development of autonomous driving technology, some special vehicles should also be developed into autonomous driving vehicles. The robotic vehicles are widely used in engineering operations, and the robotic manipulator is a common tool mounted on robotic vehicles. The autonomous driving of robotic vehicles requires not only automatic movement, but also the automation of the robotic manipulator drive system. Therefore, this paper proposes an adaptive trajectory tracking control of manipulator based on sliding mode control (SMC), which can more accurately describe the joint space movement of the manipulator system under multi task coupling and external interference. Considering the multi-tasking situation, the influence of obstacle avoidance and base tilt on the trajectory of manipulator is investigated by using extreme learning machine (ELM), and the framework of machine learning is established. The output based on ELM-SMC is used as the bottom-layer control. Then an effective trajectory compensation method is proposed as the top-level control to avoid the error accumulation in the periodic repeated operation of the manipulator. Finally, the application effect of trajectory error tracking and compensation of manipulator in complex tasks of dynamic environment is verified by simulation and experiments, which lays a foundation for the stability control of manipulator in practical complex engineering applications. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation of this paper is to solve the problem of poor trajectory tracking control accuracy of the manipulator caused by the change of the direction of the manipulator base. It is suitable for the high-precision position control of the manipulator assembled on the mobile robotic vehicle. Nowadays, the autonomous driving technology is developing rapidly, and the automation of traffic will be widely popularized in the future. Therefore, we should not only pay attention to the autonomous driving function of passenger vehicles, but also give consideration to the autonomous driving technology of robotic vehicles applied in engineering. It not only needs to complete the driving function, but also needs to ensure the reliable operation of the manipulator. In this paper, we mathematically deduce the control model of the manipulator. Then, we use SMC as the trajectory tracking control method of the manipulator, and use ELM to estimate the trajectory error caused by the end trajectory of the manipulator in the non-horizontal state of the base. Furthermore, we propose an optimization algorithm to optimize the compensation coefficient of cubic spline and give a reasonable compensation scheme. Through simulation and experiments, it is preliminarily verified that the schemes proposed in this paper are feasible, but they lack the application verification in the actual robotic vehicles, and the model fitting part of machine learning is completed with the help of the host computer, and the calculation ability of the controller of the actual manipulator may also be the limitation of completing this scheme.

The temperature effects on embedded PZT signals in structural health monitoring for composite structures with different thicknesses

Ultrasonics guided waves (GWs) are established as an effective structural health monitoring technique for detecting damage in composite structures. However, for GWs to be applied reliably in service, the effect of temperature needs to be accounted for baseline damage detection approaches. Previous studies have focused on developing temperature compensation methods for surface-mounted transducers. In this paper, an extensive investigation has been carried out to develop an effective temperature compensation method for GWs generated by embedded transducers in different thickness composites. To accomplish this, Laser Doppler Vibrometer experiments were carried out to obtain wavenumbers generated by embedded transducers and to compare them against surface mounted cases. The consistent trend observation of dispersion curves between surface-mounted and embedded PZTs serves as a foundation for conducting analysis of the embedded signals with the effect of temperature. Following that, GW propagation has been studied in three quasi-isotropic composites of 2 mm, 4 mm and 9 mm thicknesses. Based on the established temperature database with measurements from − 50 °C to 70 °C, a temperature compensation methodology has been developed and validated with the temperature difference of 30 °C. It demonstrates that the temperature effect on the embedded PZTs is lower in comparison to surface mounted PZTs, and the temperature compensation of a single thickness composite is scalable to other panels thickness. This novel methodology proves beneficial in reducing the scale of the experimental campaign required, which holds significant value for actual aeronautical structures characterized by variable composite thicknesses across different sections, such as in fuselage panels or wing boxes.

Features of spontaneous ferroelectric domain nucleation in Ti:LiNbO3 modulators

Integrated optical modulators based on lithium niobate Ti-indiffused waveguides (Ti:LiNbO3) are used extensively for broadband devices that have a high coupling efficiency with optical fibers at a 1.5 μm wavelength window. However, the ferroelectric nature of lithium niobate crystal results in some undesirable effects causing parameters fluctuations. For example, the pyroelectric effect leads to thermal dependent DC-drift and excess optical losses. Therefore, to develop effective compensation methods, it is important to understand the origin of instability. In the interelectrode gap of phase modulators we found needle-like domain defects with switched polarization along a surface layer of the monodomain X-cut lithium niobate substrate. Based on domain nucleation theory and polarization switching behavior, the spontaneous nature of domain nucleation caused by the pyroelectric field was shown and described for the interelectrode gap of the modulator along electrode edges. Considering the corona effect, models of domain nucleation and growth are proposed, and the morphology of needle-like domains is describes based on numerical simulation of the pyroelectric field distribution in the crystal volume. Experimental studies of industrial optical phase modulators characterize the shape and size of domains not only in the interelectrode gap, but also along the boundary of external electrodes proving the pyroelectric type of domain nucleation. Several methods were used for domain visualization-selective chemical etching, piezoresponse force microscopy, and electron scanning microscopy. The present work provides a theoretical and practical basis for future research on stabilization of the parameters for optical phase modulators.

A Generic and Effective System Dispersion Compensation Method: Development and Validation in Visible-Light OCT

Compared with optical coherence tomography (OCT) in the near-infrared domain, the visible-light OCT (vis-OCT) system affords a higher axial resolution for discerning subtle pathological changes associated with early diseases. However, the significant material dispersion at the visible-light range leads to a severe problem for dispersion management in vis-OCT systems, which results in a compromised axial resolution. While dispersion compensators (such as prism pairs) are commonly used, a digital method is still highly desirable and has been widely used to compensate for the residual dispersion imbalance between the reference and sample arms in an OCT system. In this paper, we develop a generic approach to effectively compensate for the system dispersion, especially the higher-order dispersion in the vis-OCT system, by using a single arbitrary measurement of the mirror-reflection (SAMMR) method and its resulting phase information. Compared with the previous methods, including the method based on the Taylor series iterative fitting and differential method, the proposed method does not need to extract the dispersion coefficients or use the metric functions and affords a better performance for axial resolution and the signal-to-noise ratio in vis-OCT systems. Its effectiveness is further validated in an OCT system operating in the near-infrared domain.

Compensation of scale factor nonlinear error introduced by harmonic distortion for open-loop fiber optic gyroscopes.

The scale factor (SF) of a gyroscope is the ratio of the detection output rotational rate and the input, and is expected to be a constant. However, for open-loop interferometric fiber optic gyroscopes (IFOGs) with sinusoidal modulation, harmonic amplitudes are inevitably affected by detection defects, such as nonuniform frequency response of the photodetector or unequal gain of amplification circuits. As a result, harmonic distortion leads to SF nonlinearity, which seriously hinders the accuracy of high-precision gyroscopes. In this Letter, the theoretical form of the SF error introduced by harmonic distortion of open-loop gyroscopes is analyzed, and an effective and simple compensation method is proposed. Instead of traversing the whole dynamic range, the proposed method simplifies the calibration pretest, where only a section of the dynamic range needs to be tested. Experimental results on an open-loop IFOG prototype show that, with our proposed method, the SF nonlinear error is suppressed to 2.5 ppm within the range -300 to +300∘/s, which is 33 times less than that before compensation.

A novel method for measuring radial and axial errors in a cylindrical coordinate system using a combined double ball bar

Multiaxis machine tools are widely used in manufacturing. The measurement of motion error is important to improve the machining accuracy of machine tools. A double ball bar (DBB), as a high-precision single-dimensional position reading device, is widely used to measure the motion error of the circular path of machine tools. However, the motion errors contain the cylindrical radial and axial errors with respect to the circular path plane. Therefore, the measurement results of the DBB are incomplete because they do not contain axial errors. To measure the motion error of the circular path accurately, completely and concisely, a novel measurement method based on the combined DBB (C-DBB) is proposed in this paper, which can directly measure the radius and axial motion error of the circular path in one measurement. First, the measuring principle of the C-DBB method is introduced, and the measurement model of the radius and axial motion error of the circular path is established. Then, a measuring device using the C-DBB method was designed based on the lever principle, and the error parameters of the designed device were analyzed. According to the error analysis results, the measurement results of the C-DBB method were compensated and corrected. Finally, the C-DBB method is used to measure the circular path on the vertical CNC milling machine, and the results are compared with the measurement results using the DBB method. It is shown that the proposed C-DBB method can obtain high-precision multidimensional motion error in a single measurement, and the designed measuring device based on the C-DBB method has high repeatability and good circular path measuring ability. The proposed method provides an effective method for machine tool multidimensional motion error measurement and compensation.

Modeling and Control of Electromagnetic Coil System Using Model Order Reduction-Based LSSVM Method*

Magnetic micro/nanorobot (MM) is promising for in-body therapy due to its advantage of untethered controllability. Since the motion of MMs can be directly manipulated by the magnetic field (MF) created by electromagnetic coil systems, it is essential to study the MF generation control methods. In this study, iron core-based solenoids are employed in an electromagnetic coil system that can produce a stronger MF than regular coil systems. However, the coil system presents hysteretic nonlinearity due to the iron core's coercivity, which degrades closed-loop control performances. To tackle this challenge, an effective hysteresis compensation method is developed to linearize the solenoid system. Specifically, the least squares support vector machine (LSSVM) is adopted to model the hysteretic behavior of the solenoid system, and the discrete empirical interpolation method (DEIM) is applied to reduce the complexity of the model for improving the calculation efficiency. Based on the LSSVM and DEIM approaches, a highly efficient LSSVM-DEIM hysteresis compensator is developed. In order to generate precise dynamic MF effectively, the LSSVM-DEIM hysteresis compensator is combined with prevalent feedback controllers to form composite control schemes. Experiments show that the control system with the LSSVM-DEIM hysteresis compensator can produce a more accurate MF compared with that of the benchmark control methods.

Compensation method for spatial phase distortion based on autocorrelation in laser heterodyne detection

The signal-to-noise ratio (SNR) of heterodyne detection is seriously reduced by the spatial phase distortion, so the compensation method of the phase distortion is of great significance for improving the performance of the heterodyne system. By replacing the single detector with an array detector in the system, the previous compensation method based on sequence shift and optimization algorithm has a certain effect. However, the method also has various shortcomings, such as long processing time, poor search stability, and possible false alarm, which severely limits its practical application. To solve the above-mentioned problems, the autocorrelation operation is used to achieve the equiphase superposition of the signals output by the elements of the array detector, thereby realizing the phase compensation. In comparison to the previous method, our method does not need an optimization algorithm, which avoids the long iterative operations and considerably improves the processing efficiency. Besides, this method avoids the false alarm caused by the optimization algorithm. The numerical calculation indicates that in case of severe phase distortion, the proposed method can increase the SNR by dozens of dB compared with the single-point detector system, thus proving the effectiveness of this method. The study results may provide a feasible and effective phase compensation method for improving and promoting the laser heterodyne detection performance.

Deep learning-guided weighted averaging for signal dropout compensation in DWI of the liver.

To develop an algorithm for the retrospective correction of signal dropout artifacts in abdominal DWI resulting from cardiac motion. Given a set of image repetitions for a slice, a locally adaptive weighted averaging is proposed that aims to suppress the contribution of image regions affected by signal dropouts. Corresponding weight maps were estimated by a sliding-window algorithm, which analyzed signal deviations from a patch-wise reference. In order to ensure the computation of a robust reference, repetitions were filtered by a classifier that was trained to detect images corrupted by signal dropouts. The proposed method, named Deep Learning-guided Adaptive Weighted Averaging (DLAWA), was evaluated in terms of dropout suppression capability, bias reduction in the ADC, and noise characteristics. In the case of uniform averaging, motion-related dropouts caused signal attenuation and ADC overestimation in parts of the liver, with the left lobe being affected particularly. Both effects could be substantially mitigated by DLAWA while preventing global penalties with respect to SNR due to local signal suppression. Performing evaluations on patient data, the capability to recover lesions concealed by signal dropouts was demonstrated as well. Further, DLAWA allowed for transparent control of the trade-off between SNR and signal dropout suppression by means of a few hyperparameters. This work presents an effective and flexible method for the local compensation of signal dropouts resulting from motion and pulsation. Because DLAWA follows a retrospective approach, no changes to the acquisition are required.

Parasitic Effect Compensation Method for IGBT ON-State Voltage Measurement in Traction Inverter Application

Parasitic Effect Compensation Method for IGBT ON-State Voltage Measurement in Traction Inverter Application

Experimental Demonstration and Simulation of Bandwidth-Limited Underwater Wireless Optical Communication with MLSE

Underwater wireless optical communication (UWOC) is able to provide large bandwidth, low latency, and high security. However, there still exist bandwidth limitations in UWOC systems, with a lack of effective compensation methods. In this paper, we systematically study the bandwidth limitation due to the transceiver and underwater channel through experiments and simulations, respectively. Experimental results show that by using the 7-tap maximum likelihood sequence estimation (MLSE) detection, the maximum bitrate of the simple rectangular shape on–off-keying (OOK) signaling is increased from 2.4 Gb/s to 4 Gb/s over 1 GHz transceiver bandwidth, compared to the conventional symbol-by-symbol detection. For the bandwidth limitation caused by the underwater channel, we simulate the temporal dispersion in the UWOC by adopting a Monte Carlo method with a Fournier–Forand phase function. With MLSE adopted at the receiver, the maximum available bitrate is improved from 0.4 to 0.8 Gb/s in 12 m of harbor water at the threshold of hard-decision forward-error-correction (HD-FEC, 3.8 × 10−3). Moreover, when the bitrate for 0.4 Gb/s 12 m and 0.8 Gb/s 10 m OOK transmission remains unchanged, the power budget can be reduced from 33.8 dBm to 30 dBm and from 27.8 dBm to 23.6 dBm, respectively. The results of both experiments and simulations indicate that MLSE has great potential for improving the performance of bandwidth-limited communication systems.

Improved Cross-coupling Effect Compensation Method for Sensorless Control of IPMSM With High Frequency Voltage Injection

In this paper, the conventional cross-coupling effect compensation method that uses offline measured cross-coupling factor by current compensation in high frequency pulsating voltage injection based sensorless control is firstly extended for use in high frequency rotating voltage injection based sensorless control by angle compensation. Compared with the current compensation method, the angle compensation method has better dynamic performance as confirmed by experiments. To enable direct angle compensation, a novel method for offline measuring the cross-coupling induced errors is proposed by injecting HF voltages in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis, respectively. The measured errors can be used for online cross-coupling effect angle compensation irrespective of the injected signal that is used for position estimation. Experiments have verified the effectiveness of the proposed methods. In addition, stability and convergence of sensorless operation with the proposed cross-coupling effect compensation methods at highly saturated conditions are also analyzed and experimentally evaluated.

Amplitude compensation using homodyne detection for inverse synthetic aperture LADAR.

Inverse synthetic aperture LADAR (ISAL), based on an electro-optic in-phase and quadrature (I/Q) modulator, and homodyne detection, has high pulse repetition frequency, simple structure, and minimum intra-pulse phase errors. Homodyne detection can implement the de-chirp operation in the optical domain, while the output amplitude is susceptible to light intensity. However, the modulated optical signal amplitude fading, induced by radio frequency devices and the I/Q modulator, is quite tricky to measure and be compensated for. In this work, the effect of amplitude distortion on the ISAL system is analyzed. A simple and effective compensation method (based on homodyne detection) is proposed, followed by some experiments. The improvement of homodyne signal power to the compensated signal compared with non-compensated signal was about 1 dB (26%), and the image quality of our ISAL system along range direction was also improved by using the proposed method. Moreover, the image of an extended target was acquired via our ISAL system with 500 mW transmitting power at a distance of 1.1 km.

An Effective Reactive Power Compensation Method and a Modern Metaheuristic Algorithm for Loss Reduction in Distribution Power Networks

In this paper, a new method of reactive power compensation is proposed for reducing power loss of distribution power networks. The new method is the combination of local compensation at each load and distribution line compensation. In the method, local capacitors at each load are determined to increase power factor of load to an expected value first and then a number of capacitors are placed in distribution lines with two factors, location and capacity by using the three applied methods. Particle swarm optimization (PSO), parasitism predation algorithm (PPA), and tunicate swarm algorithm (TSA) are applied for the proposed method on four distribution systems with 15, 33, 69, and 85 buses. The comparisons of results with previous methods indicate that the three applied methods can reach higher loss reduction for all study cases. TSA can reach loss reduction more effectively than others by 19.4%, 0.5%, 7.9%, and 10.76% for the four distribution systems, respectively. The most important emphasis is that PSO, which was considered to be of low effectiveness in previous studies, can reach much better loss than approximately all previous methods thank to the proposed compensation method. PSO also reached better loss reduction than others by 18.97%, 0.4%, 7.73%, and 10.21%, respectively. Consequently, it is recommended that the proposed compensation method is useful for distribution systems in minimizing total power loss and TSA can be selected a new and powerful method for the problem.