Adaptive Modified Positive Position Feedback for Active Vibration Control of Structures

The modified positive position feedback controller, an active vibration control method that uses collocated piezoelectric actuator actuators and sensors, is developed using an adaptive controller. The adaptive mechanism consists of two main parts: 1) Frequency adaptation mechanism, and 2) Adaptive controller. Frequency adaptation only tracks the frequency of vibrations using Fast Fourier Transforms. The obtained frequency is then fed to MPPF compensators and the adaptive controller. This provides a unique feature for MPPF, by extending its domain of capabilities from controlling tonal vibrations to broad band disturbances. The adaptive controller mechanism consists of a reference model that is of the same order as the MPPF system and its compensators. The adaptive law provides the additional control force that is needed for controlling frequency changes caused by broad band vibrations. The experimental results show that the frequency tracking method that is derived has worked quite well. The results also indicate that the MPPF can provide significant vibration reduction on a cantilever beam that is used throughout the experiments.

The negative impacts of microgrids (µGs) on the load frequency highlight the importance of implementing a robust, efficient, and adaptable controller to ensure stability. This work introduces an adaptive load frequency control (LFC) for an isolated µG that includes a PV system and electric vehicles (EVs), which have a significant impact on frequency. This control utilizes a combination of sine cosine optimization (SCO) and balloon effect identifier (BEI) algorithms. The controller presented in this work transforms the LFC process into an optimization problem that is highly compatible with various random situations encountered in the control process. The suggested control method is a novel approach by utilizing SCO+BEI for adaptive LFC application, resulting in a highly efficient response. The effectiveness of the proposed adaptive controller is assessed under the conditions of 17 MW variable load, system parameters uncertainties, and installed PV systems of 6 MW. MATLAB / Simulink package is rummage-sale as a digital test environment. According to simulation results, the proposed adaptive controller succeeds in regulating the frequency and power of an islanded µG. To measure the efficiency of the proposed control scheme, a comparison between other control techniques (such as adaptive controller using Jaya+BEI and classical integral controller) is done. The findings of the studied scenarios assured that the not compulsory control method using (SCO+BEI) has an obvious superiority over other control methods in terms of frequency solidity in case of random load instabilities and parameter uncertainties. Finally, it can be said that the proposed controller can better ensure the safe operation of the µGs.

This paper presents a new method of active vibration control (AVC) of flexible composite cantilever beams. A recursive least mean squares (LMS) based filter is used to perform on-line system identification, updating a positive position feedback (PPF) controller in real-time. With conventional time-invariant PPF control the damping ratio and natural frequency are selected based on the structural response, with the feedback path taking the form of a second-order filter; therefore having performed an off-line system identification of the plant dynamics, this controller is relatively straightforward to implement. Some structures undergo parameter changes over time and actuation in the control sequence can contribute to this change in the system dynamics. PPF control is optimized when an accurate estimation of the natural frequency is available. It is demonstrated that the recursive LMS algorithm can be used to provide a continual on-line estimation of the plant dynamics, for robust control of a slender glass fiber beam. The result is an increase in vibration attenuation, which is robust to variations in the beam properties. It is shown that this controller delivers a high performance settling time when compared with the standard PPF controller for free vibration in the first mode. Robustness of the technique is further demonstrated by altering the fundamental frequency of the beam, via the addition of a lumped mass. The adaptive controller re-tunes itself to this parameter variation, ensuring a high level of vibration suppression is upheld.

A fiber laser is easily applied for micro welding owing to the excellent beam quality. Furthermore, a fiber laser is expected to be a promising heat source for adaptive control since the peak power is variable within sub-micro-second period. The objective of the research was to develop a new laser system with inprocess monitoring and adaptive control for the stable production of sound welds in thin sheets. The bead-on–plate welding of 0.1 mm-thick stainless steels was performed with a 75 W fiber laser beam of 1,090 nm wavelength. The stability of bead widths of laser welds made with or without monitoring and adaptive control was investigated in welding the sheet on the plate with a hole which should affect heat conduction and transfer. It was revealed that the heat radiation signal was sensitive to the increase in the bead width according to the change from heat transfer process to heat-insulated process. Moreover, the peak power was adaptively controlled in the minimum 50 ms-short period in order to produce stable weld bead width regardless of the existence or absence of the heat transfer plate. Consequently, it was confirmed that the fiber laser was an excellent oscillator for laser micro welding as well as for adaptive control.

This paper is focused on adaptively controlling a linear infinite-dimensional system to track a finite-dimensional reference model. Given a linear continuous-time infinite-dimensional plant on a Hilbert space with disturbances of known waveform but unknown amplitude and phase, we show that there exists a stabilizing direct model reference adaptive control law with the properties of certain disturbance rejection and robustness. The plant is described by a closed, densely defined linear operator that generates a continuous semigroup of bounded operators on the Hilbert space of states. The central result will show that all errors will converge to a prescribed neighborhood of zero in an infinite-dimensional Hilbert space. The result will not require the use of the standard Barbalat's lemma which requires certain signals to be uniformly continuous. This result is used to determine conditions under which a linear infinite-dimensional system can be directly adaptively controlled to follow a reference model. In particular, we examine conditions for a set of ideal trajectories to exist for the tracking problem. Our results are applied to adaptive control of general linear diffusion systems described by self-adjoint operators with compact resolvent.

This paper investigates new form of a hybrid model reference adaptive speed control (HMRASC) for vector controlled permanent magnet synchronous motor (PMSM) drive. In the proposed scheme, a direct fuzzy logic controller (FLC) is employed as the main controller, and model reference based proportional integral (PI) controller as the adaptation controller. The design and optimization of the FLC and the adaptation mechanism are presented. The efficiency and performance of the HMRASC is examined, by simulation at different operating conditions. The operating conditions studied include various step speed commands from standstill with nominal and changes in motor parameters and load torque. The results obtained are evaluated and compared with direct FLC without the adaptation mechanism. The results achieved show the superior of HMRASC over direct FLC especially for load disturbances and load inertia variations

In this paper, we introduce a direct fractional order adaptive control design based on model reference adaptive control (MRAC) structure for a class of commensurate fractional order linear systems with an arbitrary relative degree, and whose parameters are unknown. By generalising the application of standard direct MRAC strategy to plants described by fractional order models, we develop a fractional adaptive control scheme (FOMRAC) based on the output feedback. We also define an adaptation control law ensuring the stability of the closed-loop system and the good tracking of the reference trajectory. The asymptotic stability of the fractional order control system is proven using an extension of the Lyapunov theorem. Simulation results show the effectiveness of the proposed control method even for plants with model parametric variations and additive noises.

In this paper the problem of adaptively controlling a hydraulic system with uncertainties is considered. An adaptive controller is derived to control actuator force with unknown valve flow coefficients and fluid parameters. This is subsequently cascaded into a position controller which uses RBF networks to compensate for the effects of friction in the system. In contrast to conventional adaptive controllers, the controller is augmented with a further layer that adaptively determines the optimal architecture for the RBF networks using the Minimum Message Length costing criterion. This provides an automated method of determining when it is no longer advantageous to increase the network size. Stability results are presented, and simulation demonstrates the ability of the MML criterion to determine when a suitable fit has been achieved.

An adaptive slip frequency control system is designed for induction motor in order to solve the problem of poor control accuracy under the conditions of low speed in vector control. BP network is used as nonlinear identification to improve identification accuracy of drive system. Position controller and speed controller are realized by single neuron learning algorithms to increase the speed control accuracy of vector control. Furthermore, the stability of adaptive slip frequency control system is improved through self-learning abilities of neural networks. Simulation results have shown that the adaptive slip frequency control system based on neural networks identification is provided with better adaptability and stronger stability compared with PID control system.

Positive position feedback (PPF) control is widely used in active vibration control offlexible structures. To ensure quick vibration suppression, a large PPF scalar gain is oftenapplied. However, PPF control with a large scalar gain causes initial overshoot, which isundesirable in many situations. In this paper, a fuzzy gain tuner is proposed to tune thegain in the positive position feedback control to reduce the initial overshoot while stillmaintaining quick vibration suppression. The fuzzy system is trained by a batch leastsquares algorithm based on desired input–output data so that the trained fuzzysystem can behave like the training data. A 3.35 m long composite I-beam withpiezoceramic patch sensors and actuators is used to demonstrate the fuzzy PPFcontrol. For comparison purposes, three types of control methods are used in theexperiment: a standard PPF control, a standard PPF control with traditionalfuzzy gain tuning, and a PPF control with batch least squares fuzzy gain tuning.Experimental results clearly demonstrate that PPF control with batch least squares fuzzygain tuning behaves much better than the other two control methods in terms ofsuccessfully reducing the initial overshoot and quickly suppressing vibration.

Advanced and innovative materials and structures are increasingly used in civil infrastructure applications. By combining the advantages of composites and smart sensors and actuators, active or smart composite structures can be created and be efficiently adopted in practical structural applications. This paper presents results of active vibration control of a pultruded fiber-reinforced polymer (FRP) composites thin-walled I-beams using smart sensors and actuators. The FRP I-beams are made of E-glass fibers and polyester resins. The FRP I-beam is in a cantilevered configuration. PZT (Lead zirconate titanate) type of piezoelectric ceramic patches are used as smart sensors and actuators. These patches are surface-bonded near the cantilevered end of the I-beam. Utilizing results from modal analyses and experimental modal testing, several active vibration control methods, such as position feedback control, strain rate feedback control and lead compensator, are investigated. Experimental results demonstrate that the proposed methods achieve effective vibration control of FRP I-beams. For instance, the modal damping ratio of the strong direction first bending mode increases by more than 1000 percent with a positive position feedback control.

Autonomous vehicles hold significant promise for enhancing traffic safety, alleviating urban congestion, and reducing energy consumption. This study proposes an adaptive Model Predictive Control (MPC)-based trajectory tracking controller to address the issue of increased tracking errors caused by vehicle kinematic parameter variations due to changing speeds in autonomous driving. The controller employs polynomial fitting to adaptively adjust control parameters within the prediction horizon based on varying vehicle speeds, ensuring high-precision trajectory tracking in diverse and complex environments. Multi-scenario simulation results on the Carsim, MATLAB, Simulink co-simulation platform demonstrate that the proposed controller effectively improves control performance under different speeds and prediction horizons. Compared to traditional MPC methods, the controller exhibits enhanced stability and accuracy in complex driving scenarios. The experimental results validate the effectiveness of the proposed approach, providing a novel perspective for adaptive control strategies in the field of autonomous driving. Furthermore, this research investigates the impact of varying prediction horizons on controller performance, specifically analyzing the trade-off between tracking accuracy and computational load. The adaptive strategy demonstrates a capability to dynamically adjust the prediction horizon in response to real-time driving conditions, ensuring both robust tracking and efficient computational performance. By minimizing lateral and heading errors, the proposed controller enhances overall vehicle stability and responsiveness. This study contributes to the advancement of autonomous driving by offering a practical and adaptable control solution for trajectory tracking.

This paper proposes an adaptive non-linear distortion noise control method for low-priority systems under spectrum sharing environments. The proposed method adaptively controls distortion noise power of a transmitter to improve reception quality of shared bands with transmission power control. The distortion power is reduced to meet a required transmission quality. In this paper, the spectrum property and BER performance with the method are evaluated by computer simulations. The results confirm that the proposed method can effectively reduce the distortion power and adaptively control transmission SNRs according to the required transmission quality.

International Journal of Adaptive Control and Signal ProcessingVolume 35, Issue 11 p. 2328-2328 RETRACTION STATEMENTFree Access Retraction: SCRIM drive system using adaptive backstepping control and mended recurrent Romanovski polynomials neural network with reformed particle swarm optimization This article retracts the following: Retracted: SCRIM drive system using adaptive backstepping control and mended recurrent Romanovski polynomials neural network with reformed particle swarm optimization Chih-Hong Lin, Kuo-Tsai Chang, Volume 33Issue 5International Journal of Adaptive Control and Signal Processing pages: 802-828 First Published online: April 10, 2019 First published: 12 October 2021 https://doi.org/10.1002/acs.3341AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat The above article from the International Journal of Adaptive Control and Signal Processing, published online on 10 April 2019 in Wiley Online Library (wileyonlinelibrary.com) and in Volume 33, pp. 802–828, has been retracted by agreement between the journal Editor in Chief, Mike Grimble, and John Wiley & Sons Ltd. The retraction has been agreed due to major overlap with a previously published article from the same group of authors. REFERENCE 1 Lin C-H, Chang K-T. SCRIM drive system using adaptive backstepping control and mended recurrent Romanovski polynomials neural network with reformed particle swarm optimization. Int J Adapt Control Signal Process. 2019; 33(5): 802- 828. https://doi.org/10.1002/acs.2990Wiley Online LibraryWeb of Science®Google Scholar Volume35, Issue11November 2021Pages 2328-2328 ReferencesRelatedInformation

Wireless communications systems in a tactical environment must be able to function effectively in a channel characterized by multipath fading and interference. Additionally, current and future communications requirements will necessitate the transmission of many different types of information with a wide range of data rates over these wireless links. Adaptive signaling is a powerful way to. design a robust system across such broad range of channel conditions because the system will not have to be designed for the worst-case scenario and system resources can be utilized more efficiently. System parameters such as signaling rate, transmit power, modulation format, coding rate, etc. can all be adaptively controlled to achieve the goal of maximizing network throughput while maintaining the desired quality of service. In this paper, we discuss the processing of Doppler information in a LEO satellite communications system to generate information for the adaptive control of signaling parameters. We analyze the link margin of a LEOS link that is characterized by free space loss, multipath fading and interference. A Doppler based adaptation algorithm is proposed which allows the estimation of the mobile terminal received signal strength and, subsequently, the adaptive control of the system parameters. Implementation issues for combining this adaptive system with various multiple access schemes are presented and it is shown that the desired system performance can be maintained across a large dynamic range of signal strength.