Self-tuning Algorithm Research Articles

Self-Tuning Adaptive Speed Controller for Permanent Magnet Synchronous Motor

This paper presents a self-tuning speed control scheme for the surface-mounted permanent magnet synchronous motor (SPMSM) against parameter variations with the traditional vector control strategy. The proposed control strategy has three novelties; the first one is to design the inner- and outer-loop controllers to stabilize the current and speed dynamics with the self-tuning algorithm for a better transient performance, the second one is to give a systematic way to constitute a robust optimal control gain by solving an optimization problem, and the third one is to show that the proposed inner-loop controller also stabilizes the closed-loop system, including the first-order internal dynamics caused by the SPMSM speed. The efficacy of the proposed method was verified through experiments using a 3-kW SPMSM.

Fuzzy Self-tuning PID Control Algorithm for Belt Conveyor Driven by Multi-motor

Fuzzy Self-tuning PID Control Algorithm for Belt Conveyor Driven by Multi-motor

Tuning a Kalman filter carrier tracking algorithm in the presence of ionospheric scintillation

Strong ionospheric electron content gradients may lead to fast and unpredictable fluctuations in the phase and amplitude of the signals from Global Navigation Satellite Systems (GNSS). This phenomenon, known as ionospheric scintillation, is capable of deteriorating the tracking performance of a GNSS receiver, leading to increased phase and Doppler errors, cycle slips and also to complete losses of signal lock. In order to mitigate scintillation effects at receiver level, the robustness of the carrier tracking loop, the receiver weakest link under scintillation, must be enhanced. Kalman filter (KF)-based tracking algorithms are particularly suitable to cope with the variable working conditions imposed by scintillation. However, the effectiveness of this tracking approach strongly depends on the accuracy of the assumed dynamic model, which can quickly become inaccurate under randomly variable situations. This study first shows how inaccurate dynamic models can lead to a KF suboptimum solution or divergence, when both strong phase and amplitude scintillation are present. Then, to overcome this issue, it proposes two self-tuning KF-based carrier tracking algorithms, which self-tune their dynamic models by exploiting the knowledge about scintillation that can be achieved through scintillation monitoring. The algorithms have been assessed with live equatorial data affected by strong scintillation. Results show that the algorithms are able to maintain the signal lock and provide reliable scintillation indices when classical architectures and commercial ionospheric scintillation monitoring receivers fail.

Hardware implementation of Predictive Torque Controlled Open-end winding induction motor drive with self-tuning algorithm

Predictive Torque Control (PTC) is an acceptable alternate to Direct Torque Control (DTC) of induction motors. The limitation of classical PTC is selection of weighting factor, improper selection o...

Tide-tree: A self-tuning indexing scheme for hybrid storage system

Main memory index is built with the assumption that the RAM is sufficiently large to hold data. Due to the volatility and high unit price of main memory, indices under secondary memory such as SSD and HDD are widely used. However, the I/O operation with main memory is still the bottleneck for query efficiency. In this paper, we propose a self-tuning indexing scheme called Tide-tree for RAM/Disk-based hybrid storage system. Tide-tree aims to overcome the obstacles main memory and disk-based indices face, and performs like the tide to achieve a double-win in space and performance, which is self-adaptive with respect to the running environment. Particularly, Tide-tree delaminates the tree structure adaptively with high efficiency based on storage sense, and applies an effective self-tuning algorithm to dynamically load various nodes into main memory. We employ memory mapping technology to solve the persistent problem of main memory index, and improves the efficiency of data synchronism and pointer translation. To further enhance the independence of Tide-tree, we employ the index head and the level address table to manage the whole index. With the index head, three efficient operations are proposed, namely index rebuild, index load and range search. We have conducted extensive experiments to compare the Tide-tree with several state-of-the-art indices, and the results have validated the high efficiency, reusability and stability of Tide-tree.

Auto-OBSD: Automatic parameter selection for reliable Oscillatory Behavior-based Signal Decomposition with an application to bearing fault signature extraction

Bearing signals are often contaminated by in-band interferences and random noise. Oscillatory Behavior-based Signal Decomposition (OBSD) is a new technique which decomposes a signal according to its oscillatory behavior, rather than frequency or scale. Due to the low oscillatory transients of bearing fault-induced signals, the OBSD can be used to effectively extract bearing fault signatures from a blurred signal. However, the quality of the result highly relies on the selection of method-related parameters. Such parameters are often subjectively selected and a systematic approach has not been reported in the literature. As such, this paper proposes a systematic approach to automatic selection of OBSD parameters for reliable extraction of bearing fault signatures. The OBSD utilizes the idea of Morphological Component Analysis (MCA) that optimally projects the original signal to low oscillatory wavelets and high oscillatory wavelets established via the Tunable Q-factor Wavelet Transform (TQWT). In this paper, the effects of the selection of each parameter on the performance of the OBSD for bearing fault signature extraction are investigated. It is found that some method-related parameters can be fixed at certain values due to the nature of bearing fault-induced impulses. To adaptively tune the remaining parameters, index-guided parameter selection algorithms are proposed. A Convergence Index (CI) is proposed and a CI-guided self-tuning algorithm is developed to tune the convergence-related parameters, namely, penalty factor and number of iterations. Furthermore, a Smoothness Index (SI) is employed to measure the effectiveness of the extracted low oscillatory component (i.e. bearing fault signature). It is shown that a minimum SI implies an optimal result with respect to the adjustment of relevant parameters. Thus, two SI-guided automatic parameter selection algorithms are also developed to specify two other parameters, i.e., Q-factor of high-oscillatory wavelets and regularization parameter. Based on the index-guided parameter selection algorithms, an automatic parameter selection method is then proposed for the application of OBSD to bearing fault signature extraction. The proposed method is then validated with simulated signals and experimental data.

Guiding mechanism design and precision pressure control in composites filament winding system

During the composite winding process, pressure fluctuation will affect the density and homogeneity of the products and will make the interfacial strength disaccord with the fiber volume fraction. In order to improve the guiding precision and stability of the winding pressure, the bearing guide is replaced by the rolling guide in designing the pressure guiding mechanism, and parametric model of the guiding mechanism is established based on dynamics experiment of the joint surfaces. By analyzing the modal and harmonic response, the corresponding measures for improvement are proposed. Experimental results show that the designed guiding mechanism based on the rolling guide has high precision and perfect stability. Additionally, roundness error and installation error of the mandrel can cause the winding pressure to fluctuate and the gas compressibility, nonlinear flow, dead zone, cylinder friction, measurement noise and other nonlinear disturbances have significant impact on the pneumatic pressure control system. Considering the above circumstance, an adaptive fuzzy proportional–integral–derivative (PID) controller based on the grey prediction is proposed. By predicting the output pressure, trend of the pressure signal can be reflected accurately, which provides a reliable basis for the decision-making of the fuzzy PID controller. Simultaneously, two separate fuzzy inference systems are employed to adjust the step length of the predictive control and the scale factor of the step self-tuning algorithm. Simulation and experimental results show that the fuzzy PID controller based on grey prediction has shorter settling time, smaller overshoot and error, stronger robustness and interference immunity. The designed guiding mechanism and control algorithm have effectively improved the precision and stability of the pressure control system for the composite materials winding formation.

BLDC Motor Torque Ripple Control Using Self-Tuning PID Fuzzy Control System

In order to suppress the torque ripple of the BLDC motor, at the same time considering the nonlinear and uncertainty of the BLDC motor, this paper mainly proposes a self-tuning PID fuzzy algorithm to control the torque ripple. Self-tuning PID fuzzy control is integrating the advantages of PID control system and fuzzy control system, using the error and change of error as inputs, and adjustment of PID parameter on-line by fuzzy control rules. Self-tuning PID fuzzy has the advantages of flexible and adaptable, and also have the characteristics of traditional PID control system such as broad applicability and high control precision. The results of simulation show that the self-tuning PID fuzzy control can suppress the torque ripple of BLDC motor effectively, the optimization of the dynamic and static characteristic of the system, satisfying the requirements of system performance, the superiority and reliability of the control strategy was verified.

Adaptive finite‐time tracking control of uncertain non‐linear n ‐order systems with unmatched uncertainties

This study focuses on the adaptive finite-time tracking problem for uncertain non-linear n-order systems subjected to unmatched uncertainties. Using a novel form of fast terminal sliding mode (FTSM) control method with self-tuning algorithm, a robust controller is obtained to drive the tracking error to origin in finite time in spite of the unmatched uncertainties. Indeed, the adaptive FTSM is combined with a global SMC approach to eliminate the reaching phase which improves the performance and robustness of the system. To alleviate chattering phenomenon and get rid of knowing the exact value of upper bound of the uncertainties, a bipolar sigmoid function with adjustable gains is presented to replace signum function. The Lyapunov stability theory is utilised to establish the stability and robustness features of the suggested law. The proposed controller provides an appropriate performance as well as finite-time convergence of tracking error to zero and this issue is verified through simulation results.

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

ABSTRACTThe main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.

Abnormal Activity Detection Using Pyroelectric Infrared Sensors.

Healthy aging is one of the most important social issues. In this paper, we propose a method for abnormal activity detection without any manual labeling of the training samples. By leveraging the Field of View (FOV) modulation, the spatio-temporal characteristic of human activity is encoded into low-dimension data stream generated by the ceiling-mounted Pyroelectric Infrared (PIR) sensors. The similarity between normal training samples are measured based on Kullback-Leibler (KL) divergence of each pair of them. The natural clustering of normal activities is discovered through a self-tuning spectral clustering algorithm with unsupervised model selection on the eigenvectors of a modified similarity matrix. Hidden Markov Models (HMMs) are employed to model each cluster of normal activities and form feature vectors. One-Class Support Vector Machines (OSVMs) are used to profile the normal activities and detect abnormal activities. To validate the efficacy of our method, we conducted experiments in real indoor environments. The encouraging results show that our method is able to detect abnormal activities given only the normal training samples, which aims to avoid the laborious and inconsistent data labeling process.

A Self-Tuning Buffer-Flushing Algorithm for OLTP Workloads

These days, huge amounts of data are created by not only humans but also the Internet of Things (IoT). As databases increase in size, their buffer pool is becoming more crucial to the overall performance. Buffer flushing, i.e., writing dirty pages, is a key factor in buffer pool management. Tuning the buffer-flushing activity in a real system is often difficult because it depends on the workload and system configuration. It is usually done through trial and error. In this paper, we propose a self-tuning algorithm for automatically controlling the buffer-flushing activity. Our algorithm not only avoids synchronous writes, which block other operations, but also preserves the effectiveness of the buffer pool. Experimental results using TPC-C and TPC-H show that our algorithm gives up to a 2.1-fold higher throughput compared with the original buffer-flushing algorithm of MySQL and 1.5-fold compared with that of Percona Server, which is a variant of MySQL.

Điều khiển tự thích nghi hệ động lực tuyến tính có cấu trúc và thông số không thay đổi

A self-tuning adaptive control algorithm based on the modified variational method and the choosing an appropriate regulator is proposed for system with unknown order and coeeficient.

Coordinated parameter design of power system stabilizers and static synchronous compensator using gradual hybrid differential evaluation

In this study, the damping scale function is used as an objective function to coordinate power system stabilizers and a static synchronous compensator with damping stabilizer parameters under various power system operating conditions to address high-frequency oscillation problems. The gradual hybrid differential evaluation algorithm developed in this study employs the gradual search method on the hybrid differential evaluation to enhance the probability of finding an optimal solution. A 16-machine power system is used to estimate the feasibility of the proposed objective function and algorithm. In the test system, all machines have stabilizers installed, and a static synchronous compensator with a damping stabilizer is placed on bus 17. The input signals of the damping stabilizer and power system stabilizers include local and remote voltage or speed deviation signals, respectively. The proposed objective function and the objective function of the combined damping factor and damping ratio are used to search for optimal power system stabilizers, and a static synchronous compensator with damping stabilizer parameters with the gradual hybrid differential evaluation algorithm and previous gradual self-tuning hybrid differential evaluation algorithms are tested under various operating conditions. The results in the frequency and time-domains reciprocally demonstrate the reliability of the simulation results. Analysis of the results indicates that the damping scale and the gradual hybrid differential evaluation algorithm can effectively coordinate power system stabilizers and the static synchronous compensator with damping stabilizer parameters to increase the transient stability of a power system.

New hybrid active power filter for harmonic current suppression and reactive power compensation

ABSTRACTIn the case of undistorted and balanced grid voltages, low ratio shunt active power filters (APFs) can give unity power factors and achieve current harmonic cancellation. However, this is not possible when source voltages are distorted and unbalanced. In this study, the cost-effective hybrid active power filter (HAPF) topology for satisfying the requirements of harmonic current suppression and non-active power compensation for industry is presented. An effective strategy is developed to observe the effect of the placement of power capacitors and LC filters with the shunt APF. A new method for alleviating the negative effects of a nonideal grid voltage is proposed that uses a self-tuning filter algorithm with instantaneous reactive power theory. The real-time control of the studied system was achieved with a field-programmable gate array (FPGA) architecture, which was developed using the OPAL-RT system. The performance result of the proposed HAPF system is tested and presented under nonideal supply voltage conditions.

Vibration mitigation of nonlinear crane system against earthquake excitations with the self-tuning fuzzy logic PID controller

This study aims to reduce the earthquake-induced vibrations of the container crane structures using an active vibration control. Vibration control using intelligent controllers such as fuzzy logic has attracted the attention of structural control engineers during the last decade. Fuzzy logic can handle uncertainties and heuristic knowledge and even nonlinearities effectively and easily. The improved seismic control performance can be performed by converting a simply designed static gain into a real time variable dynamic gain through a self-tuning mechanism. Because of the several advantages, the self-tuning fuzzy logic control algorithm is used in this study. Furthermore, with the aim of the increasing the performance of the designed controller, derivative and integral controller which are independent from the fuzzy logic controller are added to the architectural structure of the controller. This structure is called as self-tuning fuzzy logic PID controller (STFLPIDC). In this study, a six-degrees-of-freedom nonlinear mathematical model of the container crane structure is defined. Then, the controller is developed. Performance of designed controller is evaluated by numerical simulations. In the simulations, the ground motion of the Kobe earthquake \((M_w=7.2)\) in Japan on January 17, 1995, is used as earthquake excitation. The time history of displacements and accelerations and frequency responses of the both uncontrolled and controlled cases of the crane structure and control force are obtained. Performance of the designed controller is compared with the classical fuzzy logic controller (FLC). Comparison of the STFLPIDC and FLC in frequency and time domain is presented to evaluate the effect of performance of the controllers. Simulations with the STFLPIDC show better seismic performance than classical FLC. Besides, the robustness of the STFLPIDC was checked through the change in rigidity parameters. It is revealed that using designed controller and active vibration control system causes suppression of the earthquake-induced vibration.

Self-tuning of scheduling parameters for balancing the quality of experience among services in LTE

Improving the Quality of Experience (QoE) offered to subscribers has become a major issue for mobile network operators. In this paper, a self-tuning algorithm for adjusting parameters in a multi-service packet scheduler of a radio base station based on network statistics is proposed to balance QoE across services in Long Term Evolution (LTE). The aim of the algorithm is to ensure that all users achieve the same average QoE regardless of the type of service. For this purpose, the proposed heuristic algorithm iteratively changes service priority parameters to re-prioritize services so that those services with the lowest QoE increase their priority. Unlike previous approaches, the proposed algorithm takes QoE (and not Quality of Service) into account. Method assessment is carried out in a dynamic system-level LTE simulator. Simulation results in a typical scenario show that tuning service priority parameters can significantly increase the QoE of the worst service without affecting the overall network QoE.

Self-tuning of remote electrical tilts based on call traces for coverage and capacity optimization in LTE

Adjusting antenna tilts is one of the most powerful techniques to solve coverage and capacity problems in cellular networks. In this paper, a novel self-tuning algorithm for adjusting antenna tilts in a Long-Term Evolution (LTE) system on a cell-by-cell basis is presented. The aim of the algorithm is to improve both network coverage and overall spectral efficiency, while eliminating cell overshooting problems. For this purpose, several new indicators are computed to detect insufficient cell coverage, cell overshooting, and abnormal cell overlapping from information available in connection traces. Algorithm assessment is carried out over a static system-level simulator implementing different real macrocellular scenarios. During the analysis, the proposed algorithm is compared with classical self-tuning algorithms that modify other base station parameters, such as transmission power or antenna tilt. Results show that the proposed algorithm can solve overshooting and overlapping problems more effectively than previous algorithms, regardless of the scenario.

Design for Control of Wheeled Inverted Pendulum Platforms

In this paper, we study five aspects of design for wheeled inverted pendulum (WIP) platforms with the aim of understanding the effect of design choices on the balancing performance. First, we demonstrate analytically and experimentally the effect of soft visco-elastic tires on a WIP showing that the use of soft tires enhances balancing performance. Next, we study the effect of pitch rate and wheel velocity filters on WIP performance and make suggestions for design of filters. We then describe a self-tuning limit cycle compensation algorithm and experimentally verify its operation. Subsequently, we present an analytical simulation to study the effects of torque and velocity control of WIP motors and describe the tradeoffs between the control methodologies in various application scenarios. Finally, to understand if motor gearing can be an efficient alternative to bigger and more expensive direct drive motors, we analyze the effect of motor gearing on WIP dynamics. Our aim is to describe electromechanical design tradeoffs appropriately, so a WIP can be designed and constructed with minimal iterative experimentation.

Real-Time Self-Tuning Speed Controller: Performance Comparison between Engine Fuelled with Palm Methyl Esters and Petroleum Diesel

This paper investigates the performance of a real-time self-tuning speed controller designed to track and regulate at various engine speeds. The controller was tested with an automotive engine fuelled with petroleum diesel and and palm oil biodiesel (Palm Methyl Esters) within speed range of 1800 rpm to 2400 rpm. A self-tuning control algorithm based on pole assignment method together with on-line model parameters estimation strategy based on the recursive least squares method are adopted. The ability of the controller to track, regulate at various engine speed and also to reject disturbances applied for both type of fuel are compared and presented. The results confirmed that the controller performed very satisfactorily.