Adaptive Feedback Control System Research Articles

Self-Adaptive Intelligent Metasurface Cloak System with Integrated Sensing Units.

Metasurfaces, which are ultrathin planar metamaterials arranged in certain global sequences, interact uniquely with the surrounding light field and exhibit unusual effects of light modulation. Many interesting applications have been discovered based on metasurfaces, particularly in invisibility cloaks. However, most invisibility cloaks are limited to working in specific directions. Achieving effectiveness in multiple directions requires the metasurface to be designed with both perception and modulation capabilities. Current multi-directional metasurface cloak systems are implemented with discrete components rather than an integrated sensing component. Here, we propose an intelligent metasurface cloak system that integrates sensing units, resulting in the cloaking effect with the help of a real-time direction sensor and an adaptive feedback control system. A reconfigurable reflective meta-atom based on phase modulation is presented. Sensing units replace parts of the meta-atoms in the designed tunable metasurface, integrating with an FPGA responsible for measuring the direction and frequency of the incident wave, constituting a closed-loop system together with the feedback parts. Experimental results demonstrate that the metasurface cloak system can recognize the different directions of the incoming wave, and can adaptively manipulate the reflected phase of EM waves to conceal objects without any human participation.

饲草收获机动力特性分割优化控制算法研究

In order to improve the level of forage harvester automation and reduce damage, blockage and efficiency, based on the principle of minimum energy, fuzzy prediction theory and external characteristics of power, the mathematical model of the whole machine and each operating unit is established, and a set of forage harvester operating load adaptive feedback control system is designed; in order to make the power more scientifically and effectively distributed in real-time, the system adopts the simplified algorithm of operating unit efficacy threshold load splitting optimization control, with constant power and high efficiency. In order to make the power distribution more scientific and effective in real-time, the system adopts the simplified algorithm of operating unit efficacy threshold load splitting control to increase the load threshold of cutting and other operating units under constant power conditions, so that the operating efficiency of the whole machine can be improved. In the simulation test, the efficacy chopping load threshold ratio is about 1.08:1.01:1 for the three operation control methods of optimized control, fuzzy predictive control and PID control of the forage harvester, with 40% of the original feeding amount perturbation applied respectively. production efficiency was significantly improved.

Research on Signal Transmission Device of Multi Adaptive Coiled Tube Measurement and Control System

As an important technology for oilfield development and oil and gas reservoir reconstruction, the demand for coiled tubing logging, perforating, fracturing and acidizing and other process operations has increased dramatically, and downhole testing and control operations must be completed through downhole data acquisition and transmission and control signals. However, at present, the special cable coiled tubing roller device and logging roller operating machine mainly used at home and abroad have problems such as single function, high cost, complex structure, and poor versatility. Therefore, based on the structural characteristics of the conventional coiled tubing machine, through the analysis of the existing coiled tubing testing and control data signal transmission system, the research and design of the signal transmission device for the multi adaptive coiled tubing measurement and control system was completed, and a kind of signal transmission device for the multi adaptive coiled tubing signal testing, acquisition, transmission and feedback control system with strong versatility and high transmission efficiency was studied and designed, It eliminates the high cost of traditional equipment customized processing and manufacturing and the high labor intensity of operation and maintenance operations caused by the single adaptability of operation process, which are caused by complicated structures. It is of great significance for realizing the transformation and upgrading of the multi-function of intelligent measurement and control integration of coiled tubing machine, and is extremely important for the innovation of the digital network real-time monitoring system for future oilfield development.

The effect of an adaptive feedback-control system in the structural vibration control

In this work, a novel frequency adaptive optimal control algorithm has been developed that aims to provide the desired response of the structural system with an ideal control effort, appropriate to every excitation frequency range. To achieve this objective, one part of the control gain has been developed to provide frequency response characteristics similar to the structural system. The modified system under the proposed control is verified for stability and the optimal gain constants are obtained by minimizing the H2 norm of the structural output. A thorough investigation of the system shows that the algorithm, at a certain excitation frequency, influences the appropriate dynamic properties of the system, sensitive in that region. This behavior is found to persist in case of a perturbation in the structural system. Next, a theoretical assessment of the proposed control is conducted considering an existing and popular linear–quadratic Gaussian (LQG) control algorithm. The comparative assessment is extended through a numerical illustration considering a simple structural system exposed to earthquake excitations of a varying range of frequencies. A huge reduction in the control force is observed for the proposed control as compared to the LQG control for the same response characteristics of the structure and the efficiency is retained in the case of a perturbation in the initial structural system.

Distributed Adaptive Control for Nonlinear Heterogeneous Multi-agent Systems with Different Dimensions and Time Delay

A distributed neural network adaptive feedback control system is designed for a class of nonlinear multi-agent systems with time delay and nonidentical dimensions. In contrast to previous works on nonlinear heterogeneous multi-agent with the same dimension, particular features are proposed for each agent with different dimensions, and similar parameters are defined, which will be combined parameters of the controller. Second, a novel distributed control based on similarity parameters is proposed using linear matrix inequality (LMI) and Lyapunov stability theory, establishing that all signals in a closed loop system are eventually ultimately bounded. The consistency tracking error steadily decreases to a field with a small number of zeros. Finally, simulated examples with different time delays are utilized to test the effectiveness of the proposed control technique.

Intelligent metasurface with frequency recognition for adaptive manipulation of electromagnetic wave

AbstractDue to the strong ability of recognizing electromagnetic (EM) environment and adaptively control of EM waves, the intelligent metasurfaces have received great attention recently. However, the intelligent metasurface with frequency recognition for adaptive manipulation of the EM waves has not been studied. Here, we propose a frequency-recognition intelligent metasurface to precisely control the spatial EM waves under the agile frequencies with the help of a real-time radio-frequency sensor and an adaptive feedback control system. An active meta-atom is presented to reach 2 bit phase coding and 1 bit amplitude coding capacities to control the amplitude and phase independently. Experimental results demonstrate that the metasurface can recognize different frequency of the incoming wave with very high resolution, and can adaptively realize the self-defined multiple frequency agilities to manipulate the reflected EM waves without any human participation. As example, the intelligent metasurface with frequency recognition can adaptively operate wave absorption at 5.36 GHz, reflection to normal direction at 5.38 GHz, deflection to −30° at 5.40 GHz, random diffusion at 5.42 GHz, and deflection to +33° at 5.44 GHz by detecting the incoming frequency at the resolution of 0.02 GHz.

Stability analysis in machining process by using adaptive closed-loop feedback control system in turning process

The study presents model-based mechanism of nonlinear cutting tool vibration in turning process and the strategy of improving cutting process stability by suppressing machine tool vibration. The approach used is based on the closed-loop feedback control system with the help of electro–magneto–rheological damper. A machine tool vibration signal generated by an accelerometer is fed back to the coil of a damper after suitable amplification. The damper, attached under the tool holder, generates counter forces to suppress the vibration after being excited by the signal in terms of current. The study also discusses the use of transfer function approach for the development of a mathematical model and adaptively controlling the process dynamics of the turning process. The purpose of developing such mechanism is to stabilize the machining process with respect to the dynamic uncut chip thickness responsible for the type-II regenerative effect. The state-space model used in this study successfully checked the adequacy of the model through controllability and observability matrices. The eigenvalue and eigenvector have confirmed the stability of the system more accurately. The characteristic of the stability lobe chart is discussed for the present model-based mechanism.

Adaptive Anti-Windup Control System Design for ASPR-based Adaptive Output Feedback Control

ASPR-based adaptive output feedback control is considered as one of the simple and robust adaptive control method. However, in the case where there is an input saturation, windup phenomena might occur in the ASPR- based adaptive output feedback control and it may degrade the control performance significantly. In this paper, we propose an anti-windup control strategy for the ASPR-based adaptive output feedback control system. An adaptive anti-windup control based on a model recovery anti-windup control technique is proposed to improve the control performance of ASPR-based adaptive output feedback control systems with an input saturation. The stability of the obtained adaptive anti-windup control system will also be analyzed.

An on-line adaptive glucose feeding system incorporating patterns recognition for glucose concentration control in glutamate fermentations

In glutamate fermentation, intermittent feeding is the most widely used glucose feed strategy. This feeding strategy causes severe fluctuations of glucose concentration and osmotic pressure in fermentation broth, which deteriorates the viability of the cell and reduces glutamate production in turn. In order to maintain glucose concentration at stable and constant levels, an on-line prediction and feedback control system based an empiric mass balance model was developed. However, the control system did not work properly and sometimes glucose concentration could even decline to 0 level (glucose exhaustion), as the model parameter varies in different runs. As a result, a novel model-based adaptive feedback control system incoporating with an artificial neural network (ANN) based pattern reconition unit for on-line diagnosizing the fault of glucose exhaustion was proposed and applied for glutamate fermentation. This adaptive control system could accurately detect glucose exhaustion when it occurs, and then immediately updates the control parameter based on some pre-defined rule. With the proposed control system, glucose was automatically fed, and its concentration could be maintained at desired levels constantly. As a result, glutamate concentration was 17 ~ 30% higher than that of the traditional fermentations using the intermittent glucose feed strategy.

Adaptive robust control of multivariable static plants with possibly singular transfer matrix

A new problem of the adaptive robust control of linear discrete-time multivariable static plants with the singular transfer matrices in the presence of bounded disturbances is stated and solved. The asymptotical properties of the adaptive robust feedback control systems designed via the proposed method are established

Control Spatial Load Allocation and Resource Usage in Optical Communication Network

In this paper, a new design for the network traffic balance method is presented. In optical network, the wavelength is one of the most important resources, and wavelength assignment is one of the main factors that affect the efficiency of the network utilization. The performance optimization of networks is actually a control problem. Traffic engineering should provide sufficient control in an adaptive feedback control system. The tasks of a controller consist of the modification of traffic management parameters, the modification of routing parameters, and modifications of resource attributes and constraints. With the traffic balance, the network operation will be more efficient and the network blocking may decrease.<b></b>

Computational modeling and real-time control of patient-specific laser treatment of cancer.

An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.

Fusion of multiple classifiers for motor unit potential sorting

To achieve improved classification performance, a multiclassifier fusion approach for motor unit potential (MUP) sorting during electromyographic (EMG) signal decomposition was investigated. A classifier fusion system was developed that aggregates, at the abstract and measurement levels, the outputs of an ensemble of heterogeneous base classifiers to reach a collective decision, and then uses an adaptive feedback control system that detects and processes classification errors by using motor unit firing pattern consistency statistics. Three types of base classifiers were used: certainty, adaptive certainty, and adaptive fuzzy k-NN. Performance of the developed system was evaluated using real and synthetic simulated EMG signals with known properties and compared with the performance of the constituent base classifiers. Across the sets of EMG signal data sets studied, the classifier fusion schemes had better average classification performance, especially in terms of improving correct classification rates. Relative to the average performance of base classifiers and based on the difference between correct classification rate CC r and error rate E r , the adaptive average rule classifier fusion scheme shows on average: for the set of real signals an improvement of 9.2%; for the set of simulated signals of varying intensity an improvement of 6%; and for the set of simulated signals of varying amounts of shape and/or firing pattern variability an improvement of 7.7%.

Design of a near‐optimal adaptive filter in digital signal processor for active noise control

AbstractAdaptive filter has been applied in adaptive feedback and feedforward control systems, where the filter dimension is often determined by trial‐and‐error. The controller design based on a near‐optimal adaptive filter in digital signal processor (DSP) is developed in this paper for real‐time applications. The design integrates the adaptive filter and the experimental design such that their advantages in stability and robustness can be combined. The near‐optimal set of controller parameters, including the sampling rate, the dimension of system identification model, the dimension (order) of adaptive controller in the form of an FIR filter, and the convergence rate of adaptation is shown to achieve the best possible system performance. In addition, the sensitivity of each design parameter can be determined by analysis of means and analysis of variance. Effectiveness of the adaptive controller on a DSP is validated by an active noise control experiment. Copyright © 2007 John Wiley & Sons, Ltd.

AN ADAPTIVE FEEDBACK CONTROLLER WITH OBSERVER FOR LINEARIZABLE CHAOTIC SYSTEMS

In this paper, an adaptive feedback controller with observer is developed for a class of chaotic systems. This controller does not need the availability of state variables. It can be used for tracking a smooth orbit that can be a limit cycle or a chaotic orbit of another system. This adaptive feedback controller is constructed with H∞ control technique. Based on Lyapunov stability theorem, the proposed adaptive feedback control system can guarantee the stability of whole closed-loop system and achieve the H∞ tracking performance as well. To demonstrate the efficiency of the proposed scheme, two well-known chaotic systems namely Duffing-Holmes system and Lur'e-like system are considered as illustrative examples.

OBSERVER-BASED ADAPTIVE FEEDBACK CONTROLLER OF A CLASS OF CHAOTIC SYSTEMS

In this paper, an observer-based adaptive feedback controller is developed for a class of chaotic systems. This controller does not need the availability of state variables. It can be used for tracking a smooth orbit that can be a limit cycle or a chaotic orbit of another system. This adaptive feedback controller is constructed with the aid of its H∞ control technique to achieve the H∞ tracking performance. Based on Lyapunov stability theorem, the proposed adaptive feedback control system can guarantee the stability of whole closed-loop system and obtain good tracking performance as well. To demonstrate the efficiency of the proposed scheme, two well-known chaotic systems, namely Chua's circuit and Lur'e system are considered as illustrative examples.

A Switching Adaptive Output Feedback Control System Based on Almost Strictly Positive Real-ness

In this paper, a new design method for adaptive output feedback control systems with a switching function for sets of compensators is proposed. The proposed switching function can automatically select an appropriate parallel feedforward compensator and pre-compensator so that the resulting augmented plant is almost strictly positive real (or stabilizable). This paper also shows that all of the signals in the switching adaptive control system are bounded and that the switching action ceases after a finite number of switches.

A spatial light modulator based on fused-silica plates for adaptive feedback control of intense femtosecond laser pulses

A novel spatial light modulator (SLM) made of an array of fused-silica plates was developed for the purpose of feedback control for intense femtosecond laser pulses over a wide spectral range. Dispersion compensation for 20-fs pulses from a Ti:sapphire oscillator was successfully demonstrated using the SLM with an adaptive feedback control system. The SLM was also applied to the output pulses from a Ti:sapphire amplifier for compensation of material.

Adaptive Yaw Rate Feedback 4WS with Tire/Road Friction Coefficient Estimator

SUMMARY This paper proposes an adaptive yaw rate feedback control system for a four-wheel-steering (4WS) vehicle which involves a tire/road friction coefficient estimator. The adaptive 4WS system has been developed so that the vehicle possesses desirable lateral characteristics even on slippery roads and in critical driving situations. The friction coefficient is estimated on real time from the yaw rate response of the controlled vehicle with the least squares. The control system adopts a two degree of freedom structure which consists of a feedforward compensator and a feedback control subsystem. The feedforward compensator is determined with the estimated friction coefficient to minimize the steady-state and transient vehicle slip angle in spite of changes in tire/road conditions. The feedback subsystem adopts the Internal Model Control (IMC) structure in order to compensate for nonlinearities and to realize robustness against modelling and estimation errors.

Adaptive feedforward and feedback control system

An active control system for multiple interacting channels to control a constant noise or vibration consisting of first (3) and second (8) sensor means adapted to provide reference and residual signals respectively, a first and second filter means and first (12) and second (18) subtraction means to provide first and second output control signals and means for combining said output signals.