Research on Anti-Fluctuation Control of Winding Tension System Based on Feedforward Compensation

In the fiber winding process,strong disturbance,uncertainty,strong coupling,and fiber friction complicate the winding constant tension control.In order to effectively reduce the influence of these problems on the tension output,this paper proposed a tension fluctuation rejection strategy based on feedforward compensation.In addition to the bias harmonic curve of the unknown state,the tension fluctuation also contains the influence of bounded noise.A tension fluctuation observer(TFO)is designed to cancel the uncertain periodic signal,in which the frequency generator is used to estimate the critical parameter information.Then,the fluctuation signal is reconstructed by a third-order auxiliary filter.The estimated signal feedforward compensates for the actual tension fluctuation.Furthermore,a time-varying parameters fractional-order PID controller(TPFOPID)is realized to attenuate the bounded noise in the fluctuation.Finally,TPFOPID is enhanced by TFO and applied to control a tension control system considering multi-source disturbances.The stability of the method is analyzed by using the Lyapunov theorem.Finally,numerical simulations verify that the proposed scheme improves the tracking ability and robustness of the system in response to tension fluctuations.

Laboratory Implementation of Direct Torque Controller based Speed Loop Pseudo Derivative Feedforward Controller for PMSM Drive

This paper,evaluate the effectiveness of a proposed speed loop pseudo derivative feedforward(PDFF)controller-based direct torque controller(DTC)for a PMSM drive against the performance of existing PI speed controller-based DTC and hysteresis current controller(HCC).The proposed PDFF-based speed regulator effectively reduces oscillation and overshoot associated with rotor angular speed,electromagnetic torque,and stator current.Two case studies,one using forward-to-reverse motoring operation and the other involving reverse-to-forward braking operation,has been validated to show the effectiveness of the proposed control strategy.The proposed controller's superior performance is demonstrated through experimental verification utilizing an FPGA controller for a 1.5 kW PMSM drive laboratory prototype.

Matrix pencil based robust control for feedforward systems with event-triggered communications and sensor/actuator faults

In this paper we address the issue of output-feedback robust control for a class of feedforward nonlinear systems.Essentially different from the related literature,the feedback/input signals are corrupted by additive noises and can only be transmitted intermittently due to the consideration of event-triggered communications,which bring new challenges to the control design.With the aid of matrix pencil based design procedures,regulating the output to near zero is globally solved by a non-conservative dynamic low-gain controller which requires only an a priori information on the upper-bound of the growth rate of nonlinearities.Theoretical analysis shows that the closed-loop system is input-to-state stable with respect to the sampled errors and additive noise.In particular,the observer and controller designs have a dual architecture with a single dynamic scaling parameter whose update law can be obtained by calculating the generalized eigenvalues of matrix pencils offline,which has an advantage in the sense of improving the system convergence rate.

Feedforward and Feedback Optimal Control for Linear Systems with Sinusoidal Disturbances

The linear systems affected by additive external sinusoidal disturbances is studied. The problem is to damp this forced oscillation in an optimal fashion. The main result of this paper is a new design approach is proposed of realizable feedforward and feedback optimal control law for a linear time invariant system with sinusoidal disturbances. The algorithm of solving the optimal control law is given. It is shown that the control law is easily realized and is robust with respect to errors produced by the external sinusoidal disturbances through simulation results.

A New Feedback-feedforward Configuration for the Iterative Learning Control of a Class of Discrete-time Systems

这份报纸为反复的学习控制(ILC ) 论述一种新反馈前馈控制配置与反馈设计，它由反馈和一个前馈控制部件组成。反馈积分控制器稳定系统，并且在操作，和前馈控制 ILC 期间起主导的作用补偿可重复的非线性 / 未知的变化时间的动力学和骚乱，从而提高性能独自由反馈控制完成了。作为这控制策略的最有利的点，没有作努力到前馈控制 / 反馈获得的 reconfigurate 或重新调律，前馈控制 ILC 和反馈控制能独立地或联合工作。与严密分析，建议学习控制计划沿着重复轴保证 asymptotic 得到集中。

Feedback and Feedforward Optimal Control for Offshore Jacket Platforms

The optimal control is investigated for linear systems affected by external harmonic disturbance and applied to vibration control systems of offshore steel jacket platforms. The wave-induced force is the dominant load that offshore structures are subjected to, and it can be taken as harmonic excitation for the system. The linearized Morison equation is employed to estimate the wave loading. The main result concerns the existence and design of a realizable optimal regulator, which is proposed to damp the forced oscillation in an optimal fashion. For demonstration of the effectiveness of the control scheme, the platform performance is investigated for different wave states. The simulations are based on the tuned mass damper and the active mass damper control devices. It is demonstrated that the control scheme is useful in reducing the displacement response of jacket-type offshore platforms.

Development of a Novel Feedforward Neural Network Model Based on Controllable Parameters for Predicting Effluent Total Nitrogen

The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.

Dynamic Feedforward Control of a Novel 3-PSP 3-DOF Parallel Manipulator

Parallel manipulators with less than six degrees of freedom (DOF) have been increasingly used in high-speed hybrid machine tools. The structural features of parallel manipulators are dynamic, a characteristic that is particularly significant when these manipulators are used in high-speed machine tools. However, normal kinematic control method cannot satisfy the requirements of the control system. Many researchers use model-based dynamic control methods, such as the dynamic feedforward control method. However, these methods are rarely used in hybrid machine tools because of the complex dynamic model of the parallel manipulator. In order to study the dynamic control method of parallel manipulators, the dynamic feedforward control method is used in the dynamic control system of a 3-PSP (prismatic-spherical-prismatic) 3-DOF spatial parallel manipulator used as a spindle head in a high-speed hybrid machine tool. Using kinematic analysis as basis and the Newton-Euler method, we derive the dynamic model of the parallel manipulator. Furthermore, a model-based dynamic feedforward control system consisting of both kinematic control and dynamic control subsystems is established. The dynamic control subsystem consists of two modules. One is used to eliminate the influence of the dynamic characteristics of high-speed movement, and the other is used to eliminate the dynamic disturbances in the milling process. Finally, the simulation model of the dynamic feedforward control system of the 3-PSP parallel manipulator is constructed in Matlab/Simulink. The simulations of the control system eliminating the influence of the dynamic characteristics and dynamic disturbances are conducted. A comparative study between the simulations and the normal kinematic control method is also presented.The simulations prove that the dynamic feedforward control method effectively eliminates the influence of the dynamic disturbances and dynamic characteristics of the parallel manipulator on high-speed machine tools, and significantly improves the trajectory accuracy. This is the first attempt to introduce the dynamic feedfordward control method into the 3-PSP spatial parallel manipulator whose dynamic model is complex and provides a study basis for the real-time dynamic control of the high-speed hybrid machine tools.

The application of feedforward control in the nursing emergency management of COVID-19

Objective:To explore the application of feedforward control in the nursing emergency management of COVID-19.Methods:The feedforward control theory was applied to the emergency management of COVID-19 nursing,including grasping the latest epidemic information,preparing for the early stage,formulating nursing workflow,implementing flexible management,standardizing isolation and protection measures,unifying nursing document record format,and implementing humanistic care.Results:During the period of support to Wuhan,the nursing work in the isolated area was orderly,the nursing staff's job satisfaction was high,no nursing errors and hospital infections occurred.Conclusion:Efficient feedforward control in the nursing emergency management that could avoid work blindness to a certain extent and play a guiding role in maintaining the normal operation of treatment and nursing work and protecting the safety of patients and medical staff in the ward during the epidemic period of COVID-19.

FEEDFORWARD CONTROL STRATEGIES FOR TRACKING PERFORMANCE IN MACHINE AXES

Three feedforward (FFD) control techniques for position-servo machine axes are compared. All three FFD controllers are used with two different PID feedback (FBK) controllers. The two different FBK controllers have two different closed-loop bandwidths. They are demonstrated using experimental data from a linear motor test system and from simulations. Laboratory results using the linear motor hardware demonstrate that the velocity & acceleration (V&A) FFD controller improves tracking in all case considered, while the other two FFD controllers actually degrade performance in many cases. Through simulation this degradation is attributed to extreme sensitivity to round off errors. This sensitivity is the result of a complex controller that is implemented outside of the feedback loop.

Feedforward Variable Structural Proportional-Integral-Derivative for Temperature Control of Polymerase Chain Reaction

To track the rapidly changing temperature profiles of thermal cycling of polymerase chain reaction (PCR) accurately, an innovative feedforward variable structural proportional-integral-derivative (FVSPID) control- ler was developed. Based on the step response test data of the heat block, a reduced first order model was estab- lished at different operating points. Based on the reduced model, the FVSPID controller combined a feedforward path with the variable structural proportional-integral-derivative (PID) control. The modified feedforward action provided directly the optimal predictive power for the desired setpoint to speed up the dynamic response. To coop- erate with the feedforward action, a variable structural PID was applied, where the P mode was used in the case of the largest errors to speed up response, whereas the PD mode was used in the case of larger errors to suppress over- shoot, and finally the PID mode was applied for small error conditions to eliminate the steady state offset. Experi- mental results illustrated that compared to the conventional PID controller, the FVSPID controller can not only re- duce the time taken to complete a standard PCR protocol, but also improve the accuracy of gene amplification.

Feedforward and feedback optimal control for linear time-varying systems with persistent disturbances

The optimal control problem for linear time-varying systems affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions is consider and a design procedure of a feedforward and feedback optimal controller is presented. The condition of existence and uniqueness of the control law is given. The disturbance observer is proposed to make the feedforward control law realizable physically. Simulation results demonstrate that the feedforward and feedback optimal control law is more effective and robust than the classical state feedback control law with respect to external disturbances.

Adaptive Zero Phase Error Feedforward Method for Robotic Force Control

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A Variable-Parameter-Model-Based Feedforward Compensation Method for Tracking Control

Base on the accurate inverse of a system, the feedforward compensation method can compensate the tracking error of a linear system dramatically. However, many control systems have complex dynamics and their accurate inverses are difficult to obtain. In the paper, a variable parameter model is proposed to describe a system and a multi-step adaptive seeking approach is used to obtain its parameters in real time. Based on the proposed model, a variable-parameter-model-based feedforward compensation method is proposed, and a disturbance observer is used to overcome the influence of the model uncertainty. Theoretical analysis and simulation results show that the variable-parametermodel-based feedforward compensation method can obtain better performance than the traditional feedforward compensation.

A Feedforward Controller to Regulate the Chemical Composition of Molten Steel in a Continuous Casting Tundish

A feedforward controller for the automatic regulation of chemical composition of molten steel in the tundish of a continuous casting machine is proposed in this work. The flow of molten steel inside the tundish is modeled as a distributed parameter system, and the resulting partial differential equation is transformed into a set of ordinary differential equations by means of the finite differences technique. From the above set and using a proper boundary condition, a feedforward control law is synthesized. No experimental tests are reported, however, the dynamic performance of the controller is illustrated by means of numerical simulations.

Application of Feedforward and Feedback Control Strategy for Wire Rod Hot Rolling Line

The feedforward and feedback control strategy of water flowrate based on the analysis of thermal process in water cooling box was proposed, and the control strategy was applied to wire rod hot rolling at Baosteel Co. The operation has proved that the strategy can control water flowrate in the cooling water box reasonably to ensure the temperature requirement of the wire discharged from the cooling water box.

Multiple models adaptive feedforward decoupling controller

When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one freerunning adaptive model and one reinitialized adaptive model. The fixed models are used to provide initial control to the process. The reinitialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The freerunning adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steadystate error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.

Feedforward and feedback optimal control for linear time-varying systems with persistent disturbances

The optimal control problem was studied for linear time-varying systems,which was affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions. To damp the effect of disturbances in an optimal fashion,we obtained a new feedforward and feedback optimal control law and gave the control algorithm by solving a Riccati differential equation and a matrix differential equation. Simulation results showed that the achieved optimal control law was realizable,efficient and robust to reject the external disturbances.