High-frequency Measurement Noise Research Articles

A phase-locked loop using ESO-based loop filter for grid-connected converter: performance analysis

An extended state observer (ESO)-based loop filter is designed for the phase-locked loop (PLL) involved in a disturbed grid-connected converter (GcC). This ESO-based design enhances the performances and robustness of the PLL, and, therefore, improves control performances of the disturbed GcCs. Besides, the ESO-based LF can be applied to PLLs with extra filters for abnormal grid conditions. The unbalanced grid is particularly taken into account for the performance analysis. A tuning approach based on the well-designed PI controller is discussed, which results in a fair comparison with conventional PI-type PLLs. The frequency domain properties are quantitatively analysed with respect to the control stability and the noises rejection. The frequency domain analysis and simulation results suggest that the performances of the generated ESO-based controllers are comparable to those of the PI control at low frequency, while have better ability to attenuate high-frequency measurement noises. The phase margin decreases slightly, but remains acceptable. Finally, experimental tests are conducted with a hybrid power hardware-in-the-loop benchmark, in which balanced/unbalanced cases are both explored. The obtained results prove the effectiveness of ESO-based PLLs when applied to the disturbed GcC.

Reduction of Influence of the High-Frequency Noise on the Results of Surface Topography Measurements.

The influence of errors in the processes of detection and then reduction of surface topography measurement noise is of great importance; many research papers are concerned with the definition of this type of measurement error. This paper presents the influence of high-frequency measurement noise, defined for various types of surface textures, e.g., two-process plateau-honed, turned, ground, or isotropic. Procedures for the processing of raw measured data as a detection of the high-frequency errors from the results of surface topography measurements were proposed and verified (compared) according to the commonly used (available in the commercial software of the measuring equipment) algorithms. It was assumed that commonly used noise-separation algorithms did not always provide consistent results for two process textures with the valley-extraction analysis; as a result, some free-of-dimple (part of the analyzed detail where dimples do not exist) areas were not carefully considered. Moreover, the influence of measured data processing errors on surface topography parameter calculation was not comprehensively studied with high-frequency measurement noise assessments. It was assumed that the application of the Wavelet Noise Extraction Procedure (WNEP) might be exceedingly valuable when the reduction of a disparate range of measured frequencies (measurement noise) was carefully considered.

Fast Fourier Transform detection and reduction of high-frequency errors from the results of surface topography profile measurements of honed textures

In this paper, various type of noise detection procedures with surface topography profile analysis were proposed, compared (studied) and suggested. The honed cylinder liner surface textures with additionally burnished oil pockets were measured with a stylus or optical approaches. Measurement errors, defined as high-frequency measurement noise, were taken into sufficient consideration. It was proposed to select the noise detection methods more with profile (2D) than areal (3D) assessments; some-frequency noise was much easier to observe in profile than surface analysis. Moreover, applications of various type of regular filtration methods, mostly based on Gaussian functions, were compared with Fast Fourier Transform filtration for detection or reduction of some (high) frequency-defined measurement errors.

Detection of measurement noise in surface topography analysis

Various types of measurement noise detection from the results of surface topography measurements are presented and compared. The types of considered surface textures are: honed, turned, ground, laser-melted, milled, composite, ceramic and isotropic topographies. The measurements are carried out using the stylus (Talyscan 150) or non-contact – optical (white light interferometer Talysurf CCI Lite) equipment. It was assumed that for certain stratified textures, power spectral density assessment would be sufficient, otherwise, the multi-threaded analysis was required. It was also found that certain frequency errors in measurement can be readily detected with profile analysis. Nonetheless, when measurement noise amplitudes are relatively small, e.g. root mean square height (Sq) < 10%, then the isometric view detection is nearly impossible. For the detection of high-frequency measurement noise, the power spectral density analysis is required; for this type of texture, the high-frequency measurement noise surface (HFNS) is described using the regular spline filter. It is indicated that the HFNS should be observed if the machining marks are visible in the isometric view. Secondly, accurately defined HFNS should contain only the high-frequency rather than low-frequency details.

Synchronization of the Electric Power Network in the Conditions of High-Frequency Measurement Noises

The problem of robust synchronization of the electrical power network with unknown parameters is considered in the present paper. The load angles of each generator with superimposed additive high frequency noises are available for measurement. An algorithm has been synthesized to reduce the influence of noises on measurement signals and to ensure synchronization of the network in normal mode and in emergency situations associated with a sudden change in the conuctivity of power lines. To synthesize the control algorithm, the new approach is used which makes it possible to independently control the quality of noise filtering and the quality of the stabilization error of the output variable. The conditions guaranteeing the stability of the system are obtained. The simulation results have shown that the designed control system of a network of electric generators, when only noisy indications of load angles are available for measurement, provides better transient quality indicators compared to schemes of R. Ortega (France) and D. Hill (Australia), where the entire state vector is available to measurements and the parameters of the generator model are partially known. Modeling also showed that the proposed algorithm ensures the stability of a closed-loop system if there are unmodeled dynamics in network model. We also note that under conditions of random measurement noises, the control goal cannot be guaranteed due to the unlimited nature of the noises, however, the simulation results illustrate the satisfactory quality of transients with nonzero random signals in noises.

Filter-backstepping based neural adaptive formation control of leader-following multiple AUVs in three dimensional space

This paper addresses a filter-backstepping based neural adaptive formation control of leader-following AUVs with model uncertainties and external disturbances in three dimensional space. For this purpose, a formation control strategy is proposed by employing filter backstepping technique to avoid the explosion of complexity in the standard backstepping design. This technique can not only significantly simplify the design process of the backstepping controller, but also reduce the influence of high-frequency measurement noise. Then, multi-layer neural networks are incorporated with an adaptive robust technique to deal with the uncertain dynamics, approximation errors and nonlinear disturbances induced by the waves and ocean currents. A Lyapunov-based stability analysis is provided to guarantee that the tracking errors for all the AUVs are uniformly ultimately bounded (UUB). Finally, simulation results for a group of AUVs are provided to demonstrate the tracking performance of the designed formation controller.

A Kinematic Error Observer for Robot End Effector Estimation

Industrial robots were initially designed to be low cost and highly repeatable for pick-and-place and assembly operations. As a result, their construction does not support the high-precision accuracy and bandwidth needed for more advanced industrial automation. Due to the growing interest in replacing high precision manufacturing equipment with industrial robots for some applications, external high-precision feedback sensors (e.g., laser trackers), are needed to improve robot position and orientation accuracy. Before external sensors can be combined with control methodologies to improve robot accuracy, it is important to properly condition the measurement signals. In this paper, a Kinematic Error Observer (KEO) is derived and used to estimate a robot’s slowly changing kinematic errors in real-time. An analysis of the KEO is first conducted to demonstrate its stability properties, transient response characteristics, noise sensitivity, and performance in non-deterministic measurement systems. Next, an implementation of the KEO was used in conjunction with a laser tracker and 6DoF sensor to dynamically estimate the kinematic errors of a Yaskawa/Motoman MH180 industrial robot. The results show that the KEO is capable of estimating the robot’s quasi-static kinematic errors in both static and dynamic environments. It was also found that the KEO, with small enough observer gain, attenuates high frequency measurement noise and produces a smooth estimation of the robot’s kinematic error.

A New Extended State Observer with Low Sensitivity to High Frequency Noise and Low Gain Power

Linear Extended State Observer (LESO) with a large gain wo leads to faster estimation error convergence. But a high gain LESO is sensitive to high frequency measurement noise and its digital implementation is rather complex. To address the above issues, for a given n-th order plant, a new 2n-th order extended state observer is proposed. The proposed observer, while preserving the fast convergence property of LESO, has a lower gain power of 2 and is less sensitive to high frequency measurement noise. And the new observer can be easily tuned with gain ωo.

Explicit Model-Based Real PID Tuning for Efficient Load Disturbance Rejection

In the process control, many PID loops are primarily devoted to rejecting load disturbances, and some of them are crucial for the quality of the overall plant operation. In such a scenario, automatic tuning is highly desired. However, load disturbance rejection calls for strong feedback up to quite high frequencies with respect to the dominant plant dynamics, on which most tuning rules are centered. As such it is difficult for a rule to yield good and, above all, uniform results in the face of all the various process structures it can be confronted with. In this paper, we propose an explicit model-based PID tuning rule specifically targeted at the problem just evidenced. The rule minimizes the magnitude of the nominal disturbance-to-output frequency response, at the same time preventing that magnitude to exhibit a peak or a plateau around its maximum. This characteristic, together with tuning the PID derivative filter, leads to sharp disturbance rejection without incurring in an excessive control sensitivity to high-frequency measurement noise and mitigates the problems caused by heterogeneous process dynamics. The proposed approach is assessed by comparing the rule with selected counterparts, on a literature benchmark with different process structures. A laboratory experiment is finally presented to show that our rule can withstand real-world operating conditions.

A New PID Controller Design with Constraints on Relative Delay Margin for First-Order Plus Dead-Time Systems

The maximum sensitivity function as the conventional robustness index is often used to test the robustness and cannot be used to tune the controller parameters directly. To reduce analytical difficulties in dealing with the maximum sensitivity function and improve the control performance of the proportional-integral-derivative controller, the relative delay margin as a good alternative is proposed to offer a simple robust analysis for the proportional-integral-derivative controller and the first-order plus dead-time systems. The relationship between the parameters of the proportional-integral-derivative controller and the new pair, e.g., the phase margin and the corresponding gain crossover frequency, is derived. Based on this work, the stability regions of the proportional-integral-derivative controller parameters, the proportional gain and the integral gain with a given derivative gain, are obtained in a simple way. The tuning of the proportional-integral-derivative controller with constraints on the relative delay margin is simplified into an optimal disturbance rejection problem and the tuning procedure is summarized. For convenience, the recommended parameters are also offered. Simulation results demonstrate that the proposed methodology has better tracking and disturbance rejection performance than other comparative design methodologies of the proportional-integral/proportional-integral-derivative controller. For example, the integrated absolute errors of the proposed proportional-integral-derivative controller for the tracking performance and disturbance rejection performance are less than 91.3% and 91.7% of the integrated absolute errors of other comparative controllers in Example 3, respectively. The proposed methodology shows great potential in industrial applications. Besides, the proposed method can be applied to the design of the proportional-integral-derivative controller with filtered derivative which is recommended for practical applications to weaken the adverse influence of the high-frequency measurement noise.

On the fuzzy-adaptive command filtered backstepping control of an underactuated autonomous underwater vehicle in the three-dimensional space

This paper studies the three-dimensional path following control problem for an underactuated autonomous underwater vehicle in the presence of parameter uncertainties and external disturbances. Firstly, an appropriate model for the error dynamics was established to solve the path following problem in a moving Serret-Frenet frame. Secondly, an adaptive robust control scheme is proposed through fuzzy logic theory, command filtered backstepping method and an adaptation mechanism. Finally, a suitable Lyapunov candidate function is utilized to verify the stability of the overall control system and demonstrate uniform ultimate boundedness of path following errors. Following novelties are highlighted in this study: (i) The fuzzy method is adopted to solve the problems of model uncertainties, which makes the controller more practical; (ii) to calculate the virtual control derivative, a second-order filter is designed. This reduces the computational effort of the standard backstepping technique. Moreover, the effect of high frequency measurement noise is considerably attenuated via an appropriate filter to attain a more robust control system. (iii) To attain a desired approximation accuracy between the virtual control and the filtered signals, a compensation loop containing the filtered error is established. (iv) An anti-windup design is proposed to solve the problem of integral saturation in control input signals. Finally, comparative simulations are performed to ensure that the presented control scheme has excellent following accuracy and good robustness under multiple uncertainties and external disturbances.

Command filter based adaptive neural trajectory tracking control of an underactuated underwater vehicle in three-dimensional space

This study focuses on the three-dimensional trajectory tracking control problem of an underactuated underwater vehicle subject to parameter uncertainties and external disturbances. Firstly, the five degrees freedom dynamic model of an underactuated AUV is constructed, and the trajectory tracking error dynamic model is established. Secondly, a nonlinear robust control scheme is presented based on the command filtered backstepping method, which not only greatly reduces the computational complexities in the traditional backstepping approach, but also filters out the high frequency measurement noise in the trajectory tracking. Moreover, the neural networks and adaptive control techniques are employed to estimate and compensate the effect of parameter uncertainties in the control system. Thirdly, in order to guarantee the approximation precision between the virtual control vaules and the filtered signals, a Lyapunov-based filtered error compensation loop is designed, and an anti-windup design is also developed to deal with the problem of integral saturation in control input signals. After that, the stability of the control scheme proposed in this paper is proved in the sense of Lyapunov stability theory. Finally, comparative simulations were carried out to illustrate the effectiveness and good robustness of the proposed tracking controller.

Event-Triggered Based State Estimation for Autonomous Operation of an Aerial Robotic Vehicle

In this article the problem of event-triggered (ET) state estimation for autonomous navigation of an aerial vehicle is investigated numerically. The aerial vehicle is considered as a general example of a nonlinear non-Gaussian system for state estimation under process and measurement noise. The motivation behind the problem is the conditions that the aerial vehicles are facing in extreme and hazardous environments due to constant exposure of the sensors and actuators to the high frequency process and measurement noises. Here we consider autonomous operation of a quadcopter for mapping of a radioactive environment, where the quadcopter may subject to radiations and non-Gaussian noises. Autonomous operation of the aerial vehicle with a limited available energy and for a longer period of time, demands an efficient management of the energy sources. Therefore, in this study we take the first step towards this goal by studying an event triggering strategy in which the data measured by the sensors is transmitted to the processing unit only if certain events happen. The sensor employed for navigation purpose is the inertial measurement unit, including accelerometers and gyroscopes, used to estimate the quadcopter states only when their measurements are informative. An event-triggered particle filtering (PF) state estimation technique is adopted for this application. The choice of particle filter as state-estimator is inevitable not only because of nonlinear and non-Gaussian nature of the system, but also because of non-Gaussianity of the conditional distribution of the posteriori probability density function resulting from the event triggering. In the proposed method, it is proved that particles are weighted differently in the case of event triggering and no triggering. The numerical results for robust nonlinear attitude stabilization of the quadcopter in the presence of event-triggered particle filter state estimation confirm the efficiency of the proposed method.

A new PID&lt;SUB align="right"&gt;F controller structure for delayed process

A new proportional-integral-derivative (PID) control structure (PIDF) for delayed processes is proposed in this paper. It consists of a derivative controller (D) in feedback with a standard proportional-integral (PI) controller. The proposed PIDF controller improves the robustness with respect to time delay and de-noising capability. The proposed controller is similar to a PI controller with a low pass filter in series, which minimises the effect of high-frequency measurement noise. The robustness of the proposed PIDF controller, with respect to the process-delay variation, is verified through simulation of four different processes and results are compared with standard PID controller. The parameters of PID and PIDF controller are tuned by minimising the integral time square error (ITSE) objective function with the help of genetic algorithm.

A new PID&lt;SUB align="right"&gt;F controller structure for delayed process

A new proportional-integral-derivative (PID) control structure (PIDF) for delayed processes is proposed in this paper. It consists of a derivative controller (D) in feedback with a standard proportional-integral (PI) controller. The proposed PIDF controller improves the robustness with respect to time delay and de-noising capability. The proposed controller is similar to a PI controller with a low pass filter in series, which minimises the effect of high-frequency measurement noise. The robustness of the proposed PIDF controller, with respect to the process-delay variation, is verified through simulation of four different processes and results are compared with standard PID controller. The parameters of PID and PIDF controller are tuned by minimising the integral time square error (ITSE) objective function with the help of genetic algorithm.

Investigation of electric generator robust algorithm under measurement noises

The paper considers the investigation of a novel robust control algorithm of an electric generator with unknown parameters under bounded disturbances and high-frequency measurement noises. It is assumed that only the load angle is available for measurement, but not the rotor speed. The electric generator model is described by a system of third-order nonlinear differential equations with algebraic coupling ones. The proposed algorithm consisting of static and dynamical terms is based on the separation of the filtering and estimating properties. Differently from existing results the proposed scheme provides the opportunity to control independently the quality of filtering and stabilization. Investigations show that the proposed algorithm attenuates parametric uncertainties and disturbances with accuracy that can be reduced by tuning algorithm parameters.

Demodulation of Angular Position and Velocity from Resolver Signals via Chebyshev Filter-Based Type III Phase Locked Loop

A high-accuracy demodulation algorithm is required to estimate angular position and angular velocity from resolver signals. In order to improve the estimation accuracy of conventional phase-locked loop (PLL) based demodulation method, a Chebyshev filter-based type III PLL method is proposed in this paper. The proposed method makes PLL become a system of type III tracking loop, which could greatly reduce the theoretical constant deviation in the estimation results of conventional type II PLL in case of variable speed. Meanwhile, the eigenvalues of type III PLL are placed to be the same position as those of a Chebyshev low-pass filter. In this way, demodulation parameters with stronger filter properties can be obtained to effectively suppress the high-frequency measurement noise in resolver signals. Thus, the proposed method can achieve higher demodulation precision compared with the conventional ones. Simulations and experiments are performed to validate the proposed demodulation method.

Characteristics of BeiDou Navigation Satellite System (BDS) Code Observations for Different Receiver Types and Their Influence on Wide-Lane Ambiguity Resolution.

The Chinese BeiDou Navigation Satellite System (BDS) has been an important constitute of the Global Navigation Satellite System (GNSS), and the combination of GPS and BDS shows significant improvements when compared with single GPS system for real-time kinematic (RTK) positioning, and improves on availability and fixing rates, especially in the East Asian area. While network RTK might have different types of receivers, both for global and regional networks, different types of receiver may adopt different internal multipath mitigation methods and other techniques that result in different pseudorange characteristics, especially for a multipath. Then, the performance of wide-lane ambiguity resolution (WL AR) is affected. In this study, we first analyze and compare the characteristics of BDS dual-frequency observations for different types of receivers, including Trimble, Leica, Javad, and Septentrio, based on multipath (MP) observables, and then we assess their influence on double-differenced (DD) WL AR. The numerical results show that an obvious low-frequency component exists in MP observables of BDS geostationary earth-orbit satellites (GEOs) for Leica receivers, while its high-frequency measurement noise is very small. For geosynchronous orbit satellites (IGSOs) and medium earth-orbit satellites (MEOs), a slight fluctuation can also be observed that is similar to that of GPS satellites, except for the satellite-included code bias. In Trimble, Javad, and Septentrio receivers, the MP series are dominated by high-frequency measurement noise, both for GEOs and non-GEOs, except for satellite-included code bias. Furthermore, the characteristic of Leica receivers for BDS GEOs seriously affects WL AR and, even for a short baseline, it takes a long time for WL ambiguities to converge, or not converge for many GEO-related DD WL ambiguities, while Trimble, Javad, and Septentrio receivers perform well for short and medium baselines. Then, a time-difference method is proposed to mitigate the multipath of BDS GEOs for a Leica receiver. After applying the proposed method, WL ambiguity fixing rates of GEO-related satellite pairs are improved significantly and the convergence time is shortened from several hours to ten minutes.

Low-power peaking-free high-gain observers

We propose a peaking-free low-power high-gain observer that preserves the main feature of standard high-gain observers in terms of arbitrarily fast convergence to zero of the estimation error, while overtaking their main drawbacks, namely the “peaking phenomenon” during the transient and the numerical implementation issue deriving from the high-gain parameter that is powered up to the order of the system. Moreover, the new observer is proved to have superior features in terms of sensitivity of the estimation error to high-frequency measurement noise when compared with standard high-gain observers. The proposed observer structure has a high-gain parameter that is powered just up to two regardless the dimension of the observed system and adopts saturations to prevent the peaking of the estimates during the transient. As for the classical solution, the new observer is robust with respect to uncertainties in the observed system dynamics in the sense that practical estimation in the high-gain parameter can be proved.

Electric generator control under high-frequency measurement noises

The paper considers the problem of robust control of an electric generator with unknown parameters under the effect of external bounded disturbances and the presence of high-frequency measurement noises. It is assumed that only the load angle is available for measurement, but not the rotor speed. The electric generator model is described by a system of third-order differential equations with algebraic coupling equations. The proposed approach based on the separation of the filtering and estimating properties of the control system is used to solve the problem. Unlike existing analogs this scheme gives the possibility to control independently the quality of filtering and the quality of output stabilization. Also it compensates parametric uncertainties and external disturbances with required accuracy that can be reduced by selecting algorithm parameters. The proposed algorithm is easy in implementation and selection of design parameters.