Feedforward Systems Research Articles

Optimal placement of flat piezoceramic actuators for feedforward systems under the influence of real-time hardware delays

Active vibration control (AVC) systems have been investigated for several decades now. Many researchers have shown that an optimal actuator placement results in an improved performance of the AVC system.In the case of a broadband disturbance, feedback systems are very often used to control plate structures. Detailed optimisation routines for feedback systems that incorporate not only the optimisation of the actuator placement but also the controller design (e.g. feedback gains, H∞-controller) can be found in the literature. Yet, in the case of a feedforward control design for a broadband disturbance, special aspects like causality and coherence limit the performance of an AVC system. The linear quadratic optimal control theory (LQOCT) is very often used to calculate the optimal actuator voltages for the placement of actuators in a feedforward control system. However, the LQOCT completely neglects the causality constraint of a real-time applicable feedforward control system.The aim of this work is to study the influence of analogue and digital signal processing delays on the actuator placement in a feedforward control system under broadband excitation and to improve the predicted performance of an AVC system with optimised actuator placements. Therefore, a pre-design tool is used to optimise the actuator placement and it is shown that the actuator placement changes significantly by the integration of the signal processing delays into the pre-design tool. Due to their frequent use in smart structures piezoelectric patch actuators are used in this study. Furthermore, the optimised actuator placement is used for an experiment with a feedforward controller and shows an improved performance of 3.2dB in the averaged error signal spectrum over a frequency range from 22.5Hz up to 600Hz compared to the actuator placed without signal processing delays.

Global output feedback stabilization for a class of stochastic feedforward nonlinear systems with time-varying input delay

This paper investigates the problem of output feedback stabilization for a class of stochastic feedforward nonlinear systems with time-varying input delay. The drift and diffusion terms satisfy the linear growth condition and are dependent on unmeasurable states and the delayed input. First, we use a change of coordinates to introduce a scaling gain into the system. Then, based on the high-gain observer technique, a delay-free output feedback controller with the scaling gain is developed. Based on the Lyapunov–Krasovskii method and the idea of feedback domination, it is shown that the closed-loop system can be rendered globally asymptotically stable in probability via appropriately choosing the scaling gain. Finally, two examples are presented to illustrate the effectiveness of the proposed scheme.

A Dual-Stream Neuroanatomy of Singing.

Singing requires effortless and efficient use of auditory and motor systems that center around the perception and production of the human voice. Although perception and production are usually tightly coupled functions, occasional mismatches between the two systems inform us of dissociable pathways in the brain systems that enable singing. Here I review the literature on perception and production in the auditory modality, and propose a dual-stream neuroanatomical model that subserves singing. I will discuss studies surrounding the neural functions of feedforward, feedback, and efference systems that control vocal monitoring, as well as the white matter pathways that connect frontal and temporal regions that are involved in perception and production. I will also consider disruptions of the perception-production network that are evident in tone-deaf individuals and poor pitch singers. Finally, by comparing expert singers against other musicians and nonmusicians, I will evaluate the possibility that singing training might offer rehabilitation from these disruptions through neuroplasticity of the perception-production network. Taken together, the best available evidence supports a model of dorsal and ventral pathways in auditory-motor integration that enables singing and is shared with language, music, speech, and human interactions in the auditory environment.

Global stabilisation of a class of feedforward systems with distributed delays

In this study, both state feedback control and output feedback control design schemes are considered for a class of feedforward non-linear systems with distributed delays. First, by using the state transformation of non-linear systems, the problem of designing controller can be converted into that of designing a dynamic parameter, which is dynamically regulated by a dynamic equation. Then, the dynamic equation is delicately constructed by appraising the non-linear terms of the given systems. At last, with the help of Lyapunov stability theorem, it is provided the stability analysis for the closed-loop system consisting of the designed controller and the given systems. A simulation example is given to demonstrate the effectiveness of the proposed design procedure.

Effect of operating conditions on salt concentration at the wall of RO membrane

A general layout for two-module feed-forward RO systems which incorporates most functional arrangements has been developed. A simple mathematical model, suitable for all candidate arrangements, has been developed to simulate the systems under a wide range of operating conditions. The model has been employed to study the concentration polarization on membrane walls. The effects of feed specifications, operating conditions and membrane dimensions on the concentration at the wall of each membrane have been examined. Based on the magnitude of wall concentration and the range in which it changes, the arrangements experiencing lower values are pointed out.The results indicated that the value of wall concentration is almost twice the value of feed concentration. The wall concentration increases as the feed concentration and feed pressure increase. This increase is more pronounced in retentate reprocessing arrangements.The wall concentration significantly decreases as the feed temperature increases within the limits recommended for module operation. For module 1, an average decrease in wall concentration of about 23% of its original value takes place when the feed temperature is increased from 25 to 50°C. The corresponding decrease for module 2 is about 21%. These reductions allow about 7% increase in the effective pressure.

State Feedback Stabilization of Stochastic Feedforward Nonlinear Systems with Input Time-delay

In this paper, the problem of state feedback stabilization for stochastic feedforward nonlinear systems with input time-delay is considered for the first time. By introducing a variable transformation, skillfully combining the homogeneous domination method, and constructing an appropriate Lyapunov-Krasovskii functional, a state feedback controller is developed to guarantee the closed-loop system globally asymptotically stable in probability.

Estimating feedforward vs. feedback control of speech production through kinematic analyses of unperturbed articulatory movements.

To estimate the contributions of feedforward vs. feedback control systems in speech articulation, we analyzed the correspondence between initial and final kinematics in unperturbed tongue and jaw movements for consonant-vowel (CV) and vowel-consonant (VC) syllables. If movement extents and endpoints are highly predictable from early kinematic information, then the movements were most likely completed without substantial online corrections (feedforward control); if the correspondence between early kinematics and final amplitude or position is low, online adjustments may have altered the planned trajectory (feedback control) (Messier and Kalaska, 1999). Five adult speakers produced CV and VC syllables with high, mid, or low vowels while movements of the tongue and jaw were tracked electromagnetically. The correspondence between the kinematic parameters peak acceleration or peak velocity and movement extent as well as between the articulators' spatial coordinates at those kinematic landmarks and movement endpoint was examined both for movements across different target distances (i.e., across vowel height) and within target distances (i.e., within vowel height). Taken together, results suggest that jaw and tongue movements for these CV and VC syllables are mostly under feedforward control but with feedback-based contributions. One type of feedback-driven compensatory adjustment appears to regulate movement duration based on variation in peak acceleration. Results from a statistical model based on multiple regression are presented to illustrate how the relative strength of these feedback contributions can be estimated.

Impaired homeostatic regulation of feedback inhibition associated with system deficiency to detect fluctuation in stimulus intensity: a simulation study

Information processing in animals‘ brain requires the balance between excitatory and inhibitory neural circuits. Feedback inhibition is involved in many sensory processes; however, the role of inhibition in system efficiency is not fully understood. Moreover, the regulation of inhibition intensity in response to different stimulus intensity is not fully studied in normal and pathological cases. In this work, a geometrical measure for system efficiency is defined that measures the system ability to discriminate between similar stimulus intensities. For this purpose, we developed a simulation of a two-layer feedforward neural system constrained by electrophysiological data. The effect of inhibition on system efficiency was studied for different feedback inhibition parameter values. The simulations show that inhibition is critically required to detect fluctuations in stimulus intensity, especially for high stimulus intensities. Moreover, simulations demonstrate that incremental change of inhibition parameter value (by a hypothetical homeostatic regulation mechanism) to detect fluctuations in incremental stimulus intensity is critically required to obtain high level of system efficiency. This work assigns a vital role for feedback inhibition in system efficiency of feedforward neural systems.

Locally optimal controllers and globally inverse optimal controllers

In this paper we consider the problem of global asymptotic stabilization with prescribed local behavior. We show that this problem can be formulated in terms of control Lyapunov functions. Moreover, we show that if the local control law has been synthesized employing an LQ approach, then the associated Lyapunov function can be seen as the value function of an optimal problem with some specific local properties. We illustrate these results on two specific classes of systems: backstepping and feedforward systems. Finally, we show how this framework can be employed when considering the orbital transfer problem.

The predictability of frequency-altered auditory feedback changes the weighting of feedback and feedforward input for speech motor control.

Speech production requires the combined effort of a feedback control system driven by sensory feedback, and a feedforward control system driven by internal models. However, the factors that dictate the relative weighting of these feedback and feedforward control systems are unclear. In this event-related potential (ERP) study, participants produced vocalisations while being exposed to blocks of frequency-altered feedback (FAF) perturbations that were either predictable in magnitude (consistently either 50 or 100 cents) or unpredictable in magnitude (50- and 100-cent perturbations varying randomly within each vocalisation). Vocal and P1-N1-P2 ERP responses revealed decreases in the magnitude and trial-to-trial variability of vocal responses, smaller N1 amplitudes, and shorter vocal, P1 and N1 response latencies following predictable FAF perturbation magnitudes. In addition, vocal response magnitudes correlated with N1 amplitudes, vocal response latencies, and P2 latencies. This pattern of results suggests that after repeated exposure to predictable FAF perturbations, the contribution of the feedforward control system increases. Examination of the presentation order of the FAF perturbations revealed smaller compensatory responses, smaller P1 and P2 amplitudes, and shorter N1 latencies when the block of predictable 100-cent perturbations occurred prior to the block of predictable 50-cent perturbations. These results suggest that exposure to large perturbations modulates responses to subsequent perturbations of equal or smaller size. Similarly, exposure to a 100-cent perturbation prior to a 50-cent perturbation within a vocalisation decreased the magnitude of vocal and N1 responses, but increased P1 and P2 latencies. Thus, exposure to a single perturbation can affect responses to subsequent perturbations.

Data-driven realizations of kernel and image representations and their application to fault detection and control system design

This paper deals with the data-driven design of observer-based fault detection and control systems. We first introduce the definitions of the data-driven forms of kernel and image representations. It is followed by the study of their identification. In the context of a fault-tolerant architecture, the design of observer-based fault detection, feed-forward and feedback control systems are addressed based on the data-driven realization of the kernel and image representations. Finally, the main results are demonstrated on the laboratory continuous stirred tank heater (CSTH) system.

Decentralized global stabilization for stochastic high-order feedforward nonlinear systems with time-varying delays

This paper studies the problem of decentralized stabilization for a class of large-scale stochastic high-order time-delay feedforward nonlinear systems. A series of delay-independent state feedback controllers is constructed, which is based on the approach of adding one power integrator. The stochastically global asymptotic stability (GAS) of the closed-loop system under the above-mentioned controllers is proved by Lyapunov–Krasovskii theorem and homogeneous domination approach. A simulation example is given to illustrate the effectiveness of the results of this paper.

Adaptive Algorithms for Active Noise Cancellation Using Time-Varying Convergence Coefficient

— The performance of an ANC system depends on the convergence factor. A suitable value of convergence coefficient is extremely important as it impacts both the speed of convergence and the stability of the adaptive algorithm. Traditionally, in active noise control systems fixed convergence factor is used. In this paper, a novel approach of time-varying convergence factor μ is used and the results are compared with traditional feedforward and feedback noise control systems. This algorithm leads to faster convergence and provides reduced mean-squared error compared to the conventional fixed parameter algorithm.

Observer based output feedback regulation of a class of feedforward nonlinear systems with uncertain input and state delays using adaptive gain

We consider a global regulation problem of a class of feedforward nonlinear systems with uncertain delays by output feedback. The considered system is a generalized feedforward time-delay nonlinear system in the sense that an additional uncertain constant delay exists in the main control input to the system and feedforward nonlinearity includes states and input which have uncertain time-varying delays. Moreover, when feedforward nonlinearity satisfies some restrictive condition, we extend our control problem to the case such that the delay in the main control input is also a time-varying delay. To globally regulate the considered system, we develop an output feedback controller whose gain-scaling factor involves an adaptive dynamic. Two examples are given for illustration.

Saturated Delayed Controls for Feedforward Nonlinear Systems

The saturated delayed feedback is presented to globally stabilize a class of feedforward nonlinear systems whose nominal dynamics is the cascade of multiple oscillators and multiple integrators. Key strategies are stated as follows. 1) To compensate the arbitrarily large input delay and to carry out the recursive analysis, we transform the concerned system into a normal form. 2) In the convergence analysis for multiple oscillators that are relatively difficult to treat, we combine the saturated delayed terms, define the composite Lyapunov functions and use the Cauchy formula. 3) For ease of the analysis on nonlinear terms, we employ saturation levels to restrict them. As applications, the usual feedforward nonlinear systems (with multiple integrators as the nominal dynamics) and the null-controllable linear systems are dealt with in some new manners; and a saturated delayed controller is presented for the well-known TORA system.

State feedback control for a class of stochastic high-order feedforward nonlinear systems with time-varying delays: a homogeneous domination approach

In this paper, the problem of global state feedback stabilization for a class of stochastic high-order feedforward nonlinear systems with different power orders and multiple time delays is investigated. A distinct property of the system to be investigated is that the control coefficients are not restricted to 1. By adding one power integrator technique and homogeneous domination approach, a state feedback controller design is recursively proposed, which ensures the global asymptotical stability in probability of the closed-loop system. Finally, a simulation example is given to illustrate the effectiveness of our results obtained in this paper.

From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0.

This paper presents Integrated Information Theory (IIT) of consciousness 3.0, which incorporates several advances over previous formulations. IIT starts from phenomenological axioms: information says that each experience is specific – it is what it is by how it differs from alternative experiences; integration says that it is unified – irreducible to non-interdependent components; exclusion says that it has unique borders and a particular spatio-temporal grain. These axioms are formalized into postulates that prescribe how physical mechanisms, such as neurons or logic gates, must be configured to generate experience (phenomenology). The postulates are used to define intrinsic information as “differences that make a difference” within a system, and integrated information as information specified by a whole that cannot be reduced to that specified by its parts. By applying the postulates both at the level of individual mechanisms and at the level of systems of mechanisms, IIT arrives at an identity: an experience is a maximally irreducible conceptual structure (MICS, a constellation of concepts in qualia space), and the set of elements that generates it constitutes a complex. According to IIT, a MICS specifies the quality of an experience and integrated information ΦMax its quantity. From the theory follow several results, including: a system of mechanisms may condense into a major complex and non-overlapping minor complexes; the concepts that specify the quality of an experience are always about the complex itself and relate only indirectly to the external environment; anatomical connectivity influences complexes and associated MICS; a complex can generate a MICS even if its elements are inactive; simple systems can be minimally conscious; complicated systems can be unconscious; there can be true “zombies” – unconscious feed-forward systems that are functionally equivalent to conscious complexes.

Global sampled-data output feedback control for a class of feedforward nonlinear systems

This paper investigates the problem of global output feedback stabilization for a class of feedforward nonlinear systems via linear sampled-data control. To solve the problem, we first construct a linear sampled-data observer and controller. Then, a scaling gain is introduced into the proposed observer and controller. Finally, we use the sampled-data output feedback domination approach to find the explicit formula for choosing the scaling gain and the sampling period which renders the closed-loop system globally asymptotically stable. A simulation example is given to demonstrate the effectiveness of the proposed design procedure.

Adaptive and Robust Stabilization of Feedforward Nonlinear Systems Driven by Symmetric and Non‐symmetric Dead‐zone Inputs

AbstractThe stabilization of feedforward nonlinear systems subject to hard‐input nonlinearities is a challenging problem due to the presence of input uncertainties. This paper deals with adaptive control of a class of feedforward nonlinear systems driven by unknown dead‐zone inputs. The unknown dead‐zone input nonlinearity is assumed to be either symmetric or non‐symmetric. The control design is based on the combination of the invariant‐manifold stabilization technique with the classical adaptive and robust compensation methods. Simulation results showed that the presence of the dead‐zone inputs in the system dynamics can be handled even for arbitrary large dead‐zone parameters.

Performance of active feedforward control systems in non-ideal, synthesized diffuse sound fields.

The acoustic performance of passive or active panel structures is usually tested in sound transmission loss facilities. A reverberant sending room, equipped with one or a number of independent sound sources, is used to generate a diffuse sound field excitation which acts as a disturbance source on the structure under investigation. The spatial correlation and coherence of such a synthesized non-ideal diffuse-sound-field excitation, however, might deviate significantly from the ideal case. This has consequences for the operation of an active feedforward control system which heavily relies on the acquisition of coherent disturbance source information. This work, therefore, evaluates the spatial correlation and coherence of ideal and non-ideal diffuse sound fields and considers the implications on the performance of a feedforward control system. The system under consideration is an aircraft-typical double panel system, equipped with an active sidewall panel (lining), which is realized in a transmission loss facility. Experimental results for different numbers of sound sources in the reverberation room are compared to simulation results of a comparable generic double panel system excited by an ideal diffuse sound field. It is shown that the number of statistically independent noise sources acting on the primary structure of the double panel system depends not only on the type of diffuse sound field but also on the sample lengths of the processed signals. The experimental results show that the number of reference sensors required for a defined control performance exhibits an inverse relationship to control filter length.