Feedforward System Research Articles

Recurrent ANFIS-Coordinated Controller Design for Multimachine Power System with FACTS Devices

This paper proposes the design of auxiliary-coordinated controller for static VAR compensator (SVC) and thyristor-controlled series capacitor (TCSC) devices by adaptive fuzzy optimized technique for oscillation damping in multimachine power systems. The performance of the coordinated control of SVC and TCSC devices based on feedforward adaptive neuro fuzzy inference system (F-ANFIS) is compared with that of the adaptive neuro fuzzy inference system (ANFIS) structure based on recurrent adaptive neuro fuzzy inference system (R-ANFIS) network architecture. The objective of the coordinated controller design is to tune the parameters of SVC and TCSC fuzzy lead lag compensator simultaneously to minimize the deviation of rotor angle and rotor speed of the generators. The performance of the system is enhanced by optimally tuning the membership functions of fuzzy lead lag controller parameter of the flexible AC transmission system (FACTS) by R-ANFIS controller. The training data for F-ANFIS and R-ANFIS are generated by conventional linear control technique under various operating conditions. The offline trained controller tunes the parameter of lead lag controller in online. The oscillation damping ability of the system is analyzed for three-machine test system by calculating the standard deviation and cost function. The superior performance of R-ANFIS controller is compared with various particle swarm optimization-based feedforward ANFIS controllers available in literature.

A novel predictive semi-physical feed-forward turbocharging system transient control strategy based on mean-value turbocharger model

Variable geometry turbine is a technology that has been proven on diesel engines. However, despite the potential to further improve gasoline engines’ fuel economy and transient response using variable geometry turbine, controlling the variable geometry turbine during transients is challenging due to its highly non-linear behaviours especially on gasoline applications. After comparing three potential turbocharger transient control strategies, the one that predicts the turbine performances for a range of possible variable geometry turbine settings in advance was developed and validated using a high-fidelity engine model. The proposed control strategy is able to capture the complex transient behaviours and achieve the optimum variable geometry turbine trajectories. This improved the turbocharger response time by more than 14% compared with a conventional proportional–integral–derivative controller, which cannot achieve target turbocharge speed in all cases. Furthermore, the calibration effort required can be significantly reduced, offering significant benefits for powertrain developers. It is expected that the structure of this transient control strategy can also be applied to complex air-path systems.

Global output feedback sampled‐data stabilization for upper‐triangular nonlinear systems with improved maximum allowable transmission delay

SummaryThis paper addresses the problem of output feedback sampled‐data stabilization for upper‐triangular nonlinear systems with improved maximum allowable transmission delay. A class of hybrid systems are firstly introduced. The transmission delay may be larger than the sampling period. Then, sufficient conditions are proposed to guarantee global exponential stability of the hybrid systems. Based on these sufficient conditions and a linear continuous‐discrete observer, an output feedback control law is presented to globally exponentially stabilize the feedforward nonlinear system. The improved maximum allowable transmission delay is also given. The results are also extended to output feedback sampled‐data stabilization for lower‐triangular nonlinear systems. Finally, illustrative examples are used to verify the effectiveness of the proposed design methods. Copyright © 2016 John Wiley & Sons, Ltd.

Active control of counter-rotating open rotor interior noise in a Dornier 728 experimental aircraft

The fuel consumption of future civil aircraft needs to be reduced because of the CO2 restrictions declared by the European Union. A consequent lightweight design and a new engine concept called counter-rotating open rotor are seen as key technologies in the attempt to reach this ambitious goals. Bearing in mind that counter-rotating open rotor engines emit very high sound pressures at low frequencies and that lightweight structures have a poor transmission loss in the lower frequency range, these key technologies raise new questions in regard to acoustic passenger comfort. One of the promising solutions for the reduction of sound pressure levels inside the aircraft cabin are active sound and vibration systems. So far, active concepts have rarely been investigated for a counter-rotating open rotor pressure excitation on complex airframe structures.Hence, the state of the art is augmented by the preliminary study presented in this paper. The study shows how an active vibration control system can influence the sound transmission of counter-rotating open rotor noise through a complex airframe structure into the cabin. Furthermore, open questions on the way towards the realisation of an active control system are addressed. In this phase, an active feedforward control system is investigated in a fully equipped Dornier 728 experimental prototype aircraft. In particular, the sound transmission through the airframe, the coupling of classical actuators (inertial and piezoelectric patch actuators) into the structure and the performance of the active vibration control system with different error sensors are investigated. It can be shown that the active control system achieves a reduction up to 5dB at several counter-rotating open rotor frequencies but also that a better performance could be achieved through further optimisations.

Central- and autonomic nervous system coupling in schizophrenia.

The autonomic nervous system (ANS) dysfunction has been well described in schizophrenia (SZ), a severe mental disorder. Nevertheless, the coupling between the ANS and central brain activity has been not addressed until now in SZ. The interactions between the central nervous system (CNS) and ANS need to be considered as a feedback-feed-forward system that supports flexible and adaptive responses to specific demands. For the first time, to the best of our knowledge, this study investigates central-autonomic couplings (CAC) studying heart rate, blood pressure and electroencephalogram in paranoid schizophrenic patients, comparing them with age-gender-matched healthy subjects (CO). The emphasis is to determine how these couplings are composed by the different regulatory aspects of the CNS-ANS. We found that CAC were bidirectional, and that the causal influence of central activity towards systolic blood pressure was more strongly pronounced than such causal influence towards heart rate in paranoid schizophrenic patients when compared with CO. In paranoid schizophrenic patients, the central activity was a much stronger variable, being more random and having fewer rhythmic oscillatory components. This study provides a more in-depth understanding of the interplay of neuronal and autonomic regulatory processes in SZ and most likely greater insights into the complex relationship between psychotic stages and autonomic activity.

EMG analysis and control of artificial arm

Robotic hand for prosthetic applications is a unique structure intended to be driven by electro myographic (EMG) signals captured from human body. The main characteristic of this robotic hand is its actuation system, which is based on the behaviour of EMG signals. The direct relation between signal and actuation system lends itself well to interpreting the EMG signals from the muscles into effective task execution, with the goal of helping the user to achieve a good approximation of the full capabilities associated with the human hand, without compromising strength, dexterity, appearance, or weight; which are common issues associated with prosthetic hands. EMG signal capturing capability was added to control the DC motors. The emg signal was then filtered and scaled using MAT lab to a value representing the amplitude of the EMG signal, which was then used to control the direction of the motors. The controller is a simple feed forward system in the project but provides the appropriate framework to integrate more elaborate control schemes and EMG signal conditioning. The goal is to create a direct relation between the EMG signals.

Sensory feedback control in speech: Neural circuits and individual differences

Speech production involves a combination of feedforward and sensory feedback-based control mechanisms. The latter have been characterized in experiments involving real-time perturbations during speech. Unexpected perturbations of auditory feedback result in corrective motor responses with a minimum latency of approximately 100 ms after perturbation onset. These responses have been shown for both pitch and formant frequency perturbations, and the responsible neural circuitry includes portions of the superior temporal gyrus and ventral premotor cortex (vPMC). Corrective responses to somatosensory perturbations (such as a downward force applied to the jaw) occur approximately 50 ms after perturbation onset and are mediated by ventral somatosensory cortex and vPMC. The degree to which an individual weights auditory versus somatosensory feedback varies substantially. Such differences rely in part on differences in sensory acuity, e.g., a speaker with relatively poor hearing is likely to rely more heavily on somatosensory feedback control mechanisms than auditory feedback control mechanisms. Additionally, reliance on feedback control may be modulated to compensate for impairments in the feedforward system for speech, e.g., adults who stutter show a reduced reliance on auditory feedback control compared to fluent speakers, perhaps because auditory feedback can have a deleterious effect on speech initiation in stuttering.

A Study on the Feedforward Control Algorithm for Dynamic Positioning System Using Ship Motion Prediction

In the present study we verified performance of feed-forward control algorithm using short term prediction of ship motion information by taking advantage of developed numerical simulation model of FPSO motion. Up until now, various studies have been conducted about thrust control and allocation for dynamic positioning systems maintaining positions of ships or marine structures in diverse sea environmental conditions. In the existing studies, however, the dynamic positioning systems consist of only feedback control gains using a motion of vessel derived from environmental loads such as current, wind and wave. This study addresses dynamic positioning systems which have feedforward control gain derived from forecasted value of a motion of vessel occurred by current, wind and wave force. In this study, the future motion of vessel is forecasted via Brown`s Exponential Smoothing after calculating the vessel motion via a selected mathematical model, and the control force for maintaining the position and heading angle of a vessel is decided by the feedback controller and the feedforward controller using PID theory and forecasted vessel motion respectively. For the allocation of thrusts, the Lagrange Multiplier Method is exploited. By constructing a simulation code for a dynamic positioning system of FPSO, the performance of feedforward control system which has feedback controller and feedforward controller was assessed. According to the result of this study, in case of using feedforward control system, it shows smaller maximum thrust power than using conventional feedback control system.

A temporal predictive code for voice motor control: Evidence from ERP and behavioral responses to pitch-shifted auditory feedback

The predictive coding model suggests that voice motor control is regulated by a process in which the mismatch (error) between feedforward predictions and sensory feedback is detected and used to correct vocal motor behavior. In this study, we investigated how predictions about timing of pitch perturbations in voice auditory feedback would modulate ERP and behavioral responses during vocal production. We designed six counterbalanced blocks in which a +100cents pitch-shift stimulus perturbed voice auditory feedback during vowel sound vocalizations. In three blocks, there was a fixed delay (500, 750 or 1000ms) between voice and pitch-shift stimulus onset (predictable), whereas in the other three blocks, stimulus onset delay was randomized between 500, 750 and 1000ms (unpredictable). We found that subjects produced compensatory (opposing) vocal responses that started at 80ms after the onset of the unpredictable stimuli. However, for predictable stimuli, subjects initiated vocal responses at 20ms before and followed the direction of pitch shifts in voice feedback. Analysis of ERPs showed that the amplitudes of the N1 and P2 components were significantly reduced in response to predictable compared with unpredictable stimuli. These findings indicate that predictions about temporal features of sensory feedback can modulate vocal motor behavior. In the context of the predictive coding model, temporally-predictable stimuli are learned and reinforced by the internal feedforward system, and as indexed by the ERP suppression, the sensory feedback contribution is reduced for their processing. These findings provide new insights into the neural mechanisms of vocal production and motor control.

A Novel Feed-Forward Modeling System Leads to Sustained Improvements in Attention and Academic Performance

Objective: This study tested a novel feed-forward modeling (FFM) system as a nonpharmacological intervention for the treatment of ADHD children and the training of cognitive skills that improve academic performance. Method: This study implemented a randomized, controlled, parallel design comparing this FFM with a nonpharmacological community care intervention. Improvements were measured on parent- and clinician-rated scales of ADHD symptomatology and on academic performance tests completed by the participant. Participants were followed for 3 months after training. Results: Participants in the FFM training group showed significant improvements in ADHD symptomatology and academic performance, while the control group did not. Improvements from FFM were sustained 3 months later. Conclusion: The FFM appeared to be an effective intervention for the treatment of ADHD and improving academic performance. This FFM training intervention shows promise as a first-line treatment for ADHD while improving academic performance.

Feedback Regulation and Its Efficiency in Biochemical Networks

Intracellular biochemical networks fluctuate dynamically due to various internal and external sources of fluctuation. Dissecting the fluctuation into biologically relevant components is important for understanding how a cell controls and harnesses noise and how information is transferred over apparently noisy intracellular networks. While substantial theoretical and experimental advancement on the decomposition of fluctuation was achieved for feedforward networks without any loop, we still lack a theoretical basis that can consistently extend such advancement to feedback networks. The main obstacle that hampers is the circulative propagation of fluctuation by feedback loops. In order to define the relevant quantity for the impact of feedback loops for fluctuation, disentanglement of the causally interlocked influence between the components is required. In addition, we also lack an approach that enables us to infer non-perturbatively the influence of the feedback to fluctuation as the dual reporter system does in the feedforward network. In this work, we resolve these problems by extending the work on the fluctuation decomposition and the dual reporter system. For a single-loop feedback network with two components, we define feedback loop gain as the feedback efficiency that is consistent with the fluctuation decomposition for feedforward networks. Then, we clarify the relation of the feedback efficiency with the fluctuation propagation in an open-looped FF network. Finally, by extending the dual reporter system, we propose a conjugate feedback and feedforward system for estimating the feedback efficiency only from the statistics of the system non-perturbatively.

Understanding the role of speech production in reading: Evidence for a print-to-speech neural network using graphical analysis.

The neural circuitry associated with language processing is complex and dynamic. Graphical models are useful for studying complex neural networks as this method provides information about unique connectivity between regions within the context of the entire network of interest. Here, the authors explored the neural networks during covert reading to determine the role of feedforward and feedback loops in covert speech production. Brain activity of skilled adult readers was assessed in real word and pseudoword reading tasks with functional MRI (fMRI). The authors provide evidence for activity coherence in the feedforward system (inferior frontal gyrus-supplementary motor area) during real word reading and in the feedback system (supramarginal gyrus-precentral gyrus) during pseudoword reading. Graphical models provided evidence of an extensive, highly connected, neural network when individuals read real words that relied on coordination of the feedforward system. In contrast, when individuals read pseudowords the authors found a limited/restricted network that relied on coordination of the feedback system. Together, these results underscore the importance of considering multiple pathways and articulatory loops during language tasks and provide evidence for a print-to-speech neural network. (PsycINFO Database Record

Adaptive active noise control with online secondary path modelling and variable step-size learning

The performance of conventional filtered-X least mean squares (FXLMS)-based active noise control (ANC) systems may degrade owing to uncertainties in the secondary path model and constant learning gains (step-size parameters) used in the FXLMS algorithms. In this paper, a new ANC feedforward system design with online secondary path modelling and variable step-size parameters (VSSPs) is proposed. To improve the convergence performance of FXLMS algorithms, an online tuning scheme of step-size parameters (or learning gains) for the adaptive learning is developed based on the residual errors. In particular, this paper shows how to analyse the stability of the proposed closed-loop ANC systems and to study the convergence of the presented adaptations. Moreover, a modified online modelling strategy is introduced to address the modelling of secondary path dynamics. The modelling and adaptive control are all online implemented without any offline learning phase; faster convergence and better noise elimination can be achieved. Appropriate comparisons to other methods and their computational complexities are also investigated. Comparative simulation results illustrate the improved performance of the proposed methods.

Cognitive Radar Framework for Target Detection and Tracking

Most radar systems employ a feed-forward processing chain in which they first perform some low-level processing of received sensor data to obtain target detections and then pass the processed data on to some higher-level processor such as a tracker, which extracts information to achieve a system objective. System performance can be improved using adaptation between the information extracted from the sensor/processor and the design and transmission of subsequent illuminating waveforms. As such, cognitive radar systems offer much promise. In this paper, we develop a general cognitive radar framework for a radar system engaged in target tracking. The model includes the higher-level tracking processor and specifies the feedback mechanism and optimization criterion used to obtain the next set of sensor data. Both target detection (track initiation/termination) and tracking (state estimation) are addressed. By separating the general principles from the specific application and implementation details, our formulation provides a flexible framework applicable to the general tracking problem. We demonstrate how the general framework may be specialized for a particular problem using a distributed sensor model in which system resources (observation time on each sensor) are allocated to optimize tracking performance. The cognitive radar system is shown to offer significant performance gains over a standard feed-forward system.

High intensity single bunch operation with heavy periodic transient beam loading in wide band rf cavities

The rapid cycling synchrotron (RCS) in the Japan Proton Accelerator Research Complex (J-PARC) was originally designed to accelerate two high intensity bunches, while some of neutron experiments in the materials and life science experimental facility and a muon experiment using main ring beams require a single bunch operation mode, in which one of the two rf buckets is filled and the other is empty. The beam intensity in the single bunch operation has been limited by longitudinal beam losses due to the rf bucket distortions by the wake voltage of the odd harmonics ($h=1,3,5$) in the wide band magnetic alloy cavities. We installed an additional rf feedforward system to compensate the wake voltages of the odd harmonics ($h=1,3,5$). The additional system has a similar structure as the existing feedforward system for the even harmonics ($h=2,4,6$). We describe the function of the feedforward system for the odd harmonics, the commissioning methodology, and the commissioning results. The longitudinal beam losses during the single bunch acceleration disappeared with feedforward for the odd harmonics. We also confirmed that the beam quality in the single bunch acceleration are similar to that of the normal operation with two bunches. Thus, high intensity single bunch acceleration at the intensity of $2.3\ifmmode\times\else\texttimes\fi{}{10}^{13}$ protons per bunch has been achieved in the J-PARC RCS. This article is a follow-up of our previous article, Phys. Rev. ST Accel. Beams 14, 051004 (2011). The feedforward system extension for single bunch operation was successful.

Multichannel active noise control system using variable step size algorithms

This paper presents the feed-forward multichannel active noise control which was simulated on LabVIEW and experimented on two channel feed-forward active noise control in real-time. The simulation of feed-forward multichannel active noise control system was built on LabVIEW by using FxLMS algorithm and other algorithms such as Variable Step-size (VSS) and saturation compensation. Moreover, LMS and VSS LMS algorithm were used to train the secondary path in order to improve the convergence speed and stabilization of ANC system in the real-time. The experimental results show that the ANC system in real-time using variable step-size and without using variable step-size algorithm work effectively with noise sources which were synthesized from one to three frequencies. The noise level in these cases decreased around 12 dB - 35 dB and the noise reduction radius measured is about 3 cm around the microphone.

Single-rate two-dimensional feedforward control system for optical disk systems in consideration of the phase delay

The size of digital content has been on the increasing in recent times, and this has been led to the need for correspondingly scaling up the capacity of digital storage media. Therefore, a high-precision focusing and tracking control system are required for an optical disk. A pickup system for optical disks operates in the horizontal and vertical directions for tracking and focusing, respectively. Thus, this paper proposes a new single-rate two-dimensional feedforward control system, which is the concurrent control of focusing and tracking. The feedforward controller is based on a zero phase error tracking (ZPET) control. Experimental results show the effectiveness of the proposed control system.

Partial consensus of identical feedforward dynamic systems with input saturations

SummaryThis paper studies the partial consensus problem for identical feedforward dynamic systems with input saturations. We construct two consensus protocols using the partial‐state information and full‐state information, respectively. Applying a change of coordinates, feedforward system is transformed into the block diagonal form. Then, by utilizing the bounded real lemma and small gain theorem, we solve the partial consensus problem, and the existence of each protocol is derived. Copyright © 2015 John Wiley & Sons, Ltd.

Design of 16 bit 200kHz Feedforward Sigma-Delta ADC Applied in Silicon Gyroscope

Due to the huge potential applications in military and civil fields, silicon micro mechanical gyro has become the most popular research direction in MEMS field today. Therefore, the corresponding interface circuit of silicon gyroscope has also become a hot topic at home and abroad. Now, integration, digitalization and intelligence has become the focus of future research directions of silicon gyroscope, so the research of analog to digital conversion circuit for gyroscope has become a research priority. Therefore, the conduct of Sigma Delta ADCs research for silicon gyro interface circuit has a very important significance and application prospects.This topic briefly introduces the working principle of Sigma Delta ADC. Based on the requirements of the modulator design, Sigma Delta modulator structures are carefully analyzed and also carried on the comparison and optimization. Hereby, a three order three bits quantization in single-loop with partial feedback of feed-forward summation system structure for modulator is designed in this paper, and then the ideal model of modulator system in Matlab is simulated. In addition, the focus of this topic is mainly on the nonlinear factors analysis and modeling, and the Data Weighted Average (DWA) technique used in multi-bit quantization is introduced as well as modeling in system level. Then, the non-ideal modeling of system is simulated in Matlab.In system level design, this paper adopts feed-forward summation and multi-bit quantization structure to reduce the output of the integrator, increase the noise performance of the modulator, and make it easier for the system stability. Furthermore, the use of partial feedback in the structure for zero-point optimization improves the noise shaping ability in signal bandwidth of modulator. This topic employs the single-loop third-order three-bit quantization structure, with the sampling rate 64, signal bandwidth 200 K Hz and the sampling clock frequency 25.6 MHz. For the ideal modeling, the Signal-to-Noise Ratio (SNR) is 125dB, and the Effective Number of Bits (ENOB) is 20.48. When in consideration of modulator’s nonlinear factors, the nonlinear systems Simulink simulation results obtained SNR of 104dB, and the ENOB is 16.98.In order to reduce the harmonic distortion of the modulator, transistor level is implemented by fully-differential switch capacitor circuit. The structure at all levels of the integrator was optimized. To reduce the influence of flicker noise, the integrator adopts Correlated Double Sampling (CDS) technology, and is improved by the partial feedback circuit. The fully-differential operational amplifier with high slew-rate and high bandwidth is designed, and uses switch capacitor circuit as common-mode feedback. Dynamic comparator and multi-bit quantizer are designed to improve the speed of the quantizer and reduce power consumption. The design the nonlinear compensation feedback DAC module--DWA module circuit--realizes noise shaping of capacitance matching error. The overall circuit was simulated in Cadence by 0.6um process. Transistor-level simulation result shows that the SNR is 101.3dB, and the effective number of bits is 16.54bits. The simulation results are consistent with the established non-ideal model of modulator, which verifies the correction of system level design method.

Speed Measurement Error Suppression for PMSM Control System Using Self-Adaption Kalman Observer

This paper proposes a self-adaption Kalman observer (SAKO) used in a permanent-magnet synchronous motor (PMSM) servo system. The proposed SAKO can make up measurement noise of the absolute encoder with limited resolution ratio and avoid differentiating process and filter delay of the traditional speed measuring methods. To be different from the traditional Kalman observer, the proposed observer updates the gain matrix by calculating the measurement noise at the current time. The variable gain matrix is used to estimate and correct the observed position, speed, and load torque to solve the problem that the motor speed calculated by the traditional methods is prone to large speed error and time delay when PMSM runs at low speeds. The state variables observed by the proposed observer are used as the speed feedback signals and compensation signal of the load torque disturbance in PMSM servo system. The simulations and experiments prove that the SAKO can observe speed and load torque precisely and timely and that the feedforward and feedback control system of PMSM can improve the speed tracking ability.