Feedforward Control Structure Research Articles

Active Noise Control for Kitchen Hood

A kitchen hood is an appliance that is powered by a fan motor to suck the exhaust in the kitchen while cooking. When turned on, it produces low-frequency noise that cannot be reduced by only a passive material. There is a direct relationship between the speed settings in the hood and in the amount of noise that is produced. The higher the speed setting, the higher the noise. This broadband noise is reduced using the filtered-x least mean square (FXLMS) method with a feedforward active noise control (ANC) structure. To ensure a good reduction, the microphones must have good coherence and must not be affected by the turbulent wind. The whole ANC system will use one reference microphone, several error microphones connected as one, and two anti-noise speakers connected as one.

Directional Suppression of Monotone Noises with A Parametric Array Loudspeaker

Monotone noises at high decibels have been identified as a main cause of degradation in people’s mental health. This paper proposes a directional monotone noise reduction method to suppress spatially localized single-frequency noises. The system is designed based on a feedforward active noise control (ANC) structure by implementing filtered-x least mean square (FxLMS) algorithms. Compared with traditional ANC methods, our system employs a parametric array loudspeaker (PAL) as the active noise-canceling source with high audio directivity for directional noise suppression. The system monitors the ambient monotone noise and implements the ANC algorithm in real-time through a software-based platform operating on a generic personal computer (PC). Experimental measurements demonstrate an 8dB reduction of different monotone noises at a 260cm distance from the active source. Compared with traditional ANC methods with a voice coil loudspeaker (VCL) as the noise-canceling source, our PAL-based system achieves similar noise suppression performance with a 5.8 times improvement in the source-to-target distance and 64% reduction in the −3dB audio main lobe beam width. The results prove the advantage of introducing PALs as active-noise-canceling sources for monotone noise suppression with a cost-effective enhancement in operating distances and noise control directivities.

A Feedforward Model Predictive Controller for Optimal Hydrocracker Operation

Hydrocracking is an energy-intensive process, and its control system aims at stable product specifications. When the main product is diesel, the quality measure is usually 95% of the true boiling point. Constant diesel quality is hard to achieve when the feed characteristics vary and feedback control has a long response time. This work suggests a feedforward model predictive control structure for an industrial hydrocracker. A state-space model, an autoregressive exogenous model, a support vector machine regression model, and a deep neural network model are tested in this structure. The resulting reactor temperature decisions and final diesel product quality values are compared against each other and against the actual measurements. The results show the importance of the feed character measurements. Significant improvements are shown in terms of product quality as well as energy savings through decreasing the heat duty of the preheating furnace.

Dynamic controllability strategy of reactive-extractive dividing wall column for the separation of water-containing ternary azeotropic mixture

The reactive-extractive dividing wall column (REDWC), which combines conventional reactive distillation, extractive distillation, and dividing wall column, is a highly integrated process with a compact physical space and strong interrelations between variables. It is challenging to design robust control strategies for the REDWC process. However, there are no investigations reported on the control of REDWC. In this study, through analyzing open-loop controllability indicators of the steady-state process, the basic control structure (CS1) is constructed. Subsequently, four proportional-integral control schemes are further established on the CS1: the proportional control structure (CS2), the internal composition control structure (CS3), the feedforward control structure (CS4), and the three-point temperature control structure (CS5) with feedforward loops. The dynamic performance tests are conducted with ± 10 % feed flow rate and ± 10 % feed composition disturbances. The qualitative research demonstrates that the CS5 offers the best dynamic performance in terms of settling time, steady-state deviations, and overshoots without the use of expensive composition controllers. With the integral absolute error (IAE) as an evaluation criterion, it is quantitatively demonstrated that the CS5 has the best robustness and should be the preferred control scheme. Another key finding shows that the vapor split ratio and the stoichiometric ratio of the reactants are two crucial degrees of freedom to guarantee product quality in the REDWC. The major contributions of this work are to provide a meaningful reference for the control of the REDWC and even more complicated distillation.

An Intelligent Feedforward Controller Utilizing a Modified Gorilla Troops Optimization for Nonlinear Systems

This paper presents an intelligent feedforward controller based on the feedback linearization approach to control nonlinear systems. In particular, the nonlinear autoregressive moving average (NARMA-L2) network is trained to reproduce the forward dynamics of the controlled system. Consequently, the trained NARMA-L2 network can be immediately integrated into the inverse feedforward control (IFC) structure. In order to improve the NARMA-L2 structure's ability to approximate nonlinear systems, the NARMA-L2 controller is comprised of two wavelet neural networks (WNNs). In addition, the RASP1 function was used as the mother wavelet function in the structure of the WNN rather than the more common Mexican Hat, Gaussian, and Morlet functions. To prevent the limitations of gradient descent (GD) methods, an artificial gorilla troops optimization (GTO) algorithm is used to determine the optimal settings for the NARMA-L2 inverse controller parameters. In particular, a modified version of the GTO algorithm, which is called the Modified GTO (MGTO) algorithm, is proposed in this work for training the NARMA-L2 inverse controller. This algorithm has demonstrated superior optimization outcomes in comparison to other methods. The effectiveness of the proposed control strategy is demonstrated using two nonlinear dynamical systems. Specifically, several evaluation tests are used to assess the effectiveness of the WNN-based NARMA-L2 in terms of control accuracy and robustness against external disturbances in each of the systems under consideration. These tests clearly demonstrated the effectiveness of the control system. Finally, a comparison study showed that the proposed WNN-based NARMA-L2 controller achieved better control results compared to the multilayer perceptron (MLP) and the radial basis function (RBF)-based NARMA-L2 controllers.

Flexible joint parameters identification method based on improved tracking differentiator and adaptive differential evolution.

The assembly error of flexible joints and the change in joint stiffness during movement make the actual value of joint parameters inconsistent with the given value, which affects the joint control accuracy. In order to suppress the influence of parameters error, a parameters identification method for flexible joint combined offline identification and online compensation is proposed. First, the offline identification model of inertia, mass, and damping and the online identification model of joint stiffness are established, respectively. Then, a hybrid tracking differentiator based on an improved Sigmoid function is designed to track the differential signals of joint motion parameters, and the Lyapunov function is designed to prove its convergence. The adaptive differential evolution is used as the identification algorithm, and the improved adaptive crossover, mutation factor, and Metropolis acceptance criterion are designed to improve the convergence speed. Finally, a feedforward control structure based on identification is designed to compensate for the model deviation. Simulation and experimental results show that the improved differentiator can effectively improve the tracking speed and derivation accuracy of the signals. Compared with other algorithms, the proposed identification method has a faster convergence speed and higher identification accuracy, and feedforward compensation control can effectively correct model parameters and improve control accuracy.

Microgrid inverter control strategy based on augmented state feedback and dynamic feedforward compensation

In order to improve the rapidity and immunity of microgrid inverter response, an inverter control structure with augmented state feedback plus dynamic feedforward is designed. The control structure is based on the augmented state feedback, robust mutual mass decomposition and Youla parameterisation theory, which can get the augmented state feedback control parameters and feedforward control structure, and the specific expression of feedforward controller is obtained by model matching theory, after which the Current loop compensation structure is added by combining the inverter and controller structures. The load switching and three-phase unbalance experiments are designed by Matlab/Simulink. The results show that without changing the structural parameters of the original system, the new controller can quickly stabilise the voltage fluctuation within 20 ms, change the fluctuation from 15 V to 2 V, and reduce the unbalance degree from 4% to less than 1%, effectively improving the response speed and anti-interference performance of the whole system, The speed and robustness of the inverter are improved.

Design and Control of Pressure-Swing Heat Integration Distillation for the Trichlorosilane Purification Process.

Trichlorosilane (TCS) is a crucial intermediate product in the polysilicon manufacturing process, and its purification consumes a significant amount of energy. The design and control of the TCS heat integration pressure-swing distillation (HIPSD) process was investigated using Aspen Plus V8.4 and Aspen dynamics in this study. Three partial processes and one full HIPSD process were investigated by adjusting the operating conditions and rationally configuring the material flow. Compared with the conventional distillation process, the partial and full HIPSD can reduce total annual cost by 15.75 and 27.39%, respectively. The aforementioned process was controlled robustly by adding the ratio of reboiler heat duty to feed (QR/F) feedforward control structure and the ratio of recycle to feed (FREC/F) control structure. In addition, the performance of the control structure was evaluated by introducing ±10% disturbances of the feed flowrate and composition. To compare the performance of the control structure, the integral squared error value is combined with the dynamic response curve. The full HIPSD scheme can resist ±10% disturbances of flow and composition with the best economic performance. This study has certain reference significance for the distillation process and control strategy design of TCS in the polysilicon manufacturing process.

Development of an extended proportional–integral–proportional control for improving positional motion performance of permanent magnet synchronous motor‐driven servomechanism

AbstractTo achieve high‐speed and high‐accuracy positional motions in a permanent magnet synchronous motor (PMSM)‐driven servomechanism, this study developed an extended proportional–integral–proportional (PIP) control, particularly by considering the limitations of the hardware structure of commercialized PMSM drivers. PIP feedback and feedforward controls were developed, such that the existing PIP feedback control, which is extensively used in commercialized PMSM drivers, can perform dynamic and friction torque compensations in PMSMs. Thereafter, an extended PIP control with the newly added design degrees of freedom was developed based on the PIP feedback and feedforward control structures, thereby further improving the position response of the PMSM‐driven servomechanism and positional motion performance of advanced motion control systems. Position control experiments were performed on a commercialized PMSM pack installed on the rotary table of a five‐axis computer numerical control (CNC) machining center. Results indicate that the extended PIP control can significantly reduce position errors, which can be minimally influenced by the change in frequency of the position command. Furthermore, circular motion experiments were performed along the motion axes of the five‐axis CNC machining center. Results indicate that the extended PIP control with dynamic matching design can significantly reduce the root‐mean‐square value of contouring errors and roundness error value. Experimental results validate the feasibility of the extended PIP control for improving the positional motion performance of the PMSM‐driven servomechanism.

Designing and tuning MIMO feedforward controllers using iterated LMI restriction

<abstract> <p>In this paper, a multi-input multi-output (MIMO) feedforward control structure is proposed and designed based on the linear matrix inequality (LMI) approach to improve disturbance rejection and reference tracking of the given feedback system. The proposed architecture consists of two MIMO feedforward controllers, where each controller can be designed independently using the proposed method. The unknown variables of the feedforward controllers are calculated using LMI restrictions such that the H<sub>∞</sub>-norm of the transfer function matrix from disturbance (set-point) to output (error) is minimized. By taking advantage of the frequency sampling techniques and using some iterative algorithms, convergence of the solution to a local optimal point is guaranteed. For solving this optimization problem the CVX optimization tool is used and the numerical results are presented. The proposed method can be considered as a new tractable approach for tuning the parameters of MIMO feedforward controllers.</p> </abstract>

Evasion-Faced Fast Adaptive Neural Attitude Control for Generic Hypersonic Vehicles with Structural and Parametric Uncertainties

In general, the evasion task requires the hypersonic vehicles (HSVs) to quickly complete the attitude maneuver in a short time. Moreover, the rapid variation of the flight modes often induces the structural and parametric uncertainties as well as the highly dynamic disturbances of the HSVs. The peculiar and complex characteristics of the evasion process make it difficult to design the evasion-faced flight control systems. In this work, we investigate the fast adaptive control design problem for the generic HSVs under the evasion task. By introducing several especial nonlinear functional vectors and properly designing the adaptive laws, the high dynamic disturbances and uncertainties can be suppressed. To deal with the completed unknown parts of the structural uncertainties and aerodynamic uncertainties caused by evasion maneuver, two radial basis function neural networks (RBFNNs) are introduced as real-time approximators. Furthermore, to improve the response speed of the flight control system, a super-twisting (STW) algorithm-based predictor is used as a feed-forward term of the controller. Consequently, a novel evasion-faced fast adaptive feed-forward control structure has been established for the HSVs. It has been proven that all the signals of the closed-loop system are bounded with satisfactory tracking velocity. Finally, the simulation experiment has been set up to show the effectiveness and advantages of the proposed control method.

Passing zenith stabilization method of two-dimensional gyro platform based on disturbance sources classification control

Aiming at the instability problem caused by the nonlinear constraint between the driving axis and the sensitive axis of the azimuth line-of-sight (LOS) control with the two-dimensional gyro platform, the variation rules of influence of azimuth line-of-sight (LOS) by different types of disturbance sources were analyzed, and a passing zenith stabilization method based on the disturbance sources classification control was proposed. This method used the feedback and feedforward dual channel compound control structure, eliminated the endogenous torque disturbance caused by gyro measurement noise amplification in the zenith position based on the control structure itself, and the torque disturbance caused by the high frequency component of the roll disturbance was suppressed by adding the filtering link of the feedforward channel, then the vibration problem of the azimuth drive axis in zenith position was solved. At the same time, the azimuth and the low frequency component of the roll disturbance were effectively isolated by the feedback channel and the feedforward channel. The simulation results show that this method can effectively suppress the amplitude of azimuth motor torque disturbance caused by the gyro measurement noise and high frequency component of the roll disturbance, and enhance the system stability. Finally, an experiment was carried out on a two-dimensional gyro platform. The stabilization precision of the line-of-sight bearing subjected to vibration in zenith position was reduced from 82.4 μrad to 44.6 μrad, and the isolation ratio was increased from −14.54 dB to −27.85 dB under the swing condition. The experimental results show that this method can effectively improve the disturbance isolation performance of azimuth line-of-sight in zenith position.

A Novel Fast Error Convergence Approach for an Optimal Iterative Learning Controller

Design an optimized iterative learning control for linear and nonlinear dynamical systems is a challenging task. Norm-optimal iterative learning control (NOILC) is a valuable criterion for these dynamical systems. An iterative learning control algorithm based on optimal control theory is proposed, and the stability and convergence conditions of the proposed control algorithm are analyzed by using the convergence conditions of iterative learning control, and the control design is carried out based on feedforward and feedback control structure. At the same time, by introducing a weighted matrix coefficient to the feedforward control action, the convergence speed of iterative learning control algorithm based on optimal control theory is improved, and it is applied to the Matlab simulation control system. The results show that the convergence effect of the basic optimal control theory and the iterative learning control algorithm based on the weighted matrix coefficient is significant and the performance of the trajectory tracking is improved. The numerical example simulated on MATLAB@2019 and mollified results confirm the validation of the designed algorithm.

Stepwise Voltage Drop and Transient Current Control Strategies to Enhance Fault Ride-Through Capability of MMC-HVDC Connected DFIG Wind Farms

This paper proposes advanced control strategies to enhance fault ride-through capability of modular multilevel converter-based high voltage direct current (MMC-HVDC) connected doubly-fed induction generator (DFIG)-based wind farms. A stepwise voltage drop control is proposed for the sending-end MMC to suppress dc line voltage fluctuations by demagnetizing DFIGs. Meanwhile, a modified transient current control is proposed for the DFIG, where a voltage-dependent active current control is integrated into the rotor-side converter to improve synchronization stability of the converter, and a feedforward transient stator current control structure is designed to eliminate dc component in the stator current. The proposed control strategies are validated by comparing with three typical methods through time-domain simulations.

Model based control strategies to control voltage of Proton Exchange Membrane Fuel Cell

Abstract The present work deals with the evaluation of model based control strategies for a PEM fuel cell to control voltage. PEM fuel cell is an electrochemical device that converts the chemical energy to electrical energy. Stack voltage is affected by many factors like stack temperature, moisture content of the membrane, partial pressure of hydrogen and air, inlet rate of hydrogen and air and also fuel starvation affects the rate of reaction and hence the voltage produced. In this work, two single input single output models are taken with stack voltage as controlled variable and hydrogen and air flow rate as manipulated variables respectively. The simulation study on two different control structures i.e., feedback and feedback plus feed forward control structures evaluates the effectiveness of proposed controllers concerning set-point tracking and disturbance rejection. Comparative study is carried out by simulations by implementing various model based control strategies, PI, IMC-PID and MPC. The results shows that MPC gives best results in terms of Integral Square error (ISE), Integral Absolute error (IAE) and controller effort (TV). In addition, robust stability analysis is carried out for uncertainty in the process parameters. Also, the controller fragility is studied for uncertainty in the controller parameters.

Rigorous design and control of thermally integrated pressure‐swing reactive distillation process for isobutyl acetate production considering the effect of column pressures

AbstractBy studying the effect of pressure on relative volatility, azeotrope composition, and net reaction rate, a rigorous pressure‐swing thermally integrated reactive distillation (PST‐RD) process for isobutyl acetate synthesis is proposed. The steady‐state and dynamic characteristics of the PST‐RD process are evaluated based on Aspen and Aspen Dynamic. Steady‐state optimization results show that the energy consumption and the total annual cost (TAC) reduced by 42.32% and 34.20% compared with the conventional two‐column process, respectively. Subsequently, two control structures of the PST‐RD process under a rigorous model are developed and evaluated by large disturbances in throughput and feed composition. Dynamic simulation results show that peak dynamic transients can be effectively reduced by adding a Q/F feedforward control structure. Furthermore, the effective heat integration of high‐pressure (HP) and low‐pressure (LP) columns can be realized by implementing composition/pressure cascade control when the capacity of the LP column increases.

Fuel cell humidity modeling and control using cathode internal water content

Humidity of proton exchange membrane fuel cell, a critical underlying variable that affects stack efficiency and durability, is quite challenging to be well controlled due to the measuring difficulty and multiple couplings with other variables. For precise humidity description and control, this paper utilizes the internal water content as the feedback signal, whose dynamic model is developed by taking into account various auxiliary couplings. Based on the mechanistic model, the dynamic responses of the internal water content are exhibited and analyzed by manipulating the external current, air compressor voltage and humidifier electrical power, respectively. It is shown that the internal water content is able to better describe the real humidity environment, in contrast with the conventional method using cathode inlet relative humidity. Furthermore, a combined feed-forward and feedback control structure is proposed to maintain the internal humidity as close to the desired as possible. Simulation results show that the proposed control method is able to maintain the fuel cell operating within the safe and efficient region, and the humidification power consumption can be reduced because of the precise and less conservative description on the internal humidity.

Modified Structures for Hybrid Active Sound Quality Control System Disturbed by Gaussian Random Noise

A hybrid active sound quality control system, in which a hybrid feedforward and feedback structure is applied, can not only be used in cases where the line-spectrum noise is obtained easily with reference sensors, but it can also improve the comfortability of noise and eliminate unexpected Gaussian random noise. However, the traditional structure for a hybrid active sound quality control system, whereby a reference signal in the feedback control structure is synthesized by the output signals of the feedforward control filter, feedback control filter, and line-spectrum noise cancellation control filter, introduces couplings of the three control filters. To remove the coupling interactions of the feedforward and feedback control structures and to reduce the complexity of the control system, two modified structures with less computational complexity or a smaller increase in computation are investigated in this paper. The first one involves a simplified structure in which the reference signal in the feedback control structure is replaced by the summation of the residual error signal and the output signal of the line-spectrum noise cancellation control filter, and the second one is a modified structure which integrates the output signals of the feedback control filter and the line-spectrum noise cancellation control filter for the reference signal in the feedback control structure. Numerical simulations are carried out to show the performance of the modified structures. The results illustrate that the two modified structures have the ability to cancel Gaussian random noise and to reduce or enhance the amplitude of line-spectrum noise to promote sound quality. Moreover, a simplified structure with a new leaky filtered-x least mean square (FxLMS) algorithm is proposed to upgrade the noise reduction performance and elevate stability in the feedback control structure. The effectiveness of the proposed algorithm also is proven by the simulation results.

Permanent Magnet Synchronous Motor Speed Control System Based on Adaptive Inverse Control Method

The classical feedback control method for the permanent-magnet synchronous motor cannot fulfill the dynamic requirement and anti-interference requirement at the same time. In this paper, an adaptive inverse control method with disturbance elimination is proposed based on the vector control including speed and current loops. It avoids the system instability and the anti-disturbance performance of the system can be enhanced as well. Firstly, the speed loop adopts the adaptive inverse controller possessing a feed forward control structure, and a normalized least-mean square filtering algorithm accelerates the speed error convergence. The inverse model of the approximately linearized system is obtained by modifying the weighting factor online. Secondly, in order to suppress and eliminate the influence of motor parameter perturbation and external disturbance on the control system, an extended state observer is designed to observe and compensate the disturbance of the system. Thus, the dynamic performance and anti-disturbance performance of the system can be improved simultaneously. Finally, the effectiveness of the proposed method is verified by experiment and simulation.

Optimal design of adaptive shaking vibration control for electric vehicles

ABSTRACTThis paper provides a complete design solution about adaptive optimal shaking vibration control for electric vehicles. A general 4-DOF and 5-order linear torsional vibration model is established under given wheel speed, and the frequency characteristics of the vibration system are elaborately analysed in terms of variation of wheel speed and different model parameters. Aiming at decreasing the shaking vibration at the least sacrifice of acceleration loss, and improving the robustness of the system against external disturbance, a combination of feed-forward and feed-backward adaptive control structure is proposed. Further, a non-linear multi-constraint optimisation problem is formulated for solving the optimal adaptive control variables within the two-dimensional design space composed of the wheel speed and driver's torque command. Furthermore, the distribution of the optimal adaptive control variables within the design space and its extended application under different tyre road conditions are discussed. Eventually, several simulation test cases are particularly designed to verify the performances of the controller on all aspects. Test results show that the optimal adaptive controller achieves satisfactory anti-shaking vibration, acceleration maintaining and robustness performances within the whole adaptive design space as desired.