Proportional-integral Feedback Controller Research Articles

Cognitively Driven Autonomous Flow Chemistry for Producing On-Demand Perovskite Quantum Dots Via Advanced Closed-Loop Feedback Control.

Recent developments in the synthesis of hybrid organic-inorganic halide perovskite quantum dots (HP-QDs) through compositional adjustments have highlighted their potential applications in the fields of photovoltaics and light sources due to their unique optoelectronic properties. However, traditional methods to fine-tune their composition involve repetitive, labor-intensive, and costly processes. Herein, the utilization of a continuous flow chemistry approach is developed, in combination with a Proportional-Integral (PI) feedback control system as an effective method for producing on-demand methylammonium lead bromoiodide (MAPbBrx I3-x ) HP-QDs. The PI feedback control allows for real-time optimization of the flow rates of halide precursor solutions (halide PSs), enabling the precise tuning of the emission wavelength of HP-QDs. HP-QDs having an emission wavelength of 550 and 650nm are synthesized through a blue-shifted and red-shifted algorithm, respectively, from any arbitrary reaction condition within 400 s. The iterative process through the PI feedback control produces the target HP-QDs with short rise time and low overshoot. The proposed automatic flow chemistry system integrated with a universal and accessible control algorithm of PI can generate the target HP-QDs with high accuracy, stability, and robustness, demonstrating a significant advancement in constructing an autonomous flow chemistry synthetic system.

A Proportional–Integral Feedback Controlled Automatic Flow Chemistry System to Produce On‐Demand AgAu Alloy Nanoboxes

Mixed‐metal nanoparticles present a challenging task for synthesis with high precision and reproducibility due to the complex interplay of compositional and reaction condition factors. The present study demonstrates a highly precise and automated flow chemistry technique for synthesizing AgAu alloy nanoboxes with tailored optical properties. The synthesis process involves a proportional–integral (PI) feedback control mechanism that enables accurate regulation of reaction parameters, such as the flow rate, to achieve the target AgAu nanoboxes having a desired UV–vis absorbance wavelength. The PI control algorithm is built on the first‐order plus dead‐time model, which correlates the flow rate of the precursors with the maximum absorbance peaks of the resultant nanoalloy products. Based on the difference between the real‐time measured UV–vis absorbance wavelength and the target wavelength, the flow rate of the precursor (i.e., reagent concentration) is tuned via an iterative process until the real‐time absorbance wavelength of the AgAu alloy nanoboxes is matched with the target setpoint. The implementation of a PI feedback control mechanism in a flow chemistry system can offer a highly versatile and universal strategy for generating on‐demand complex nanomaterials with significantly enhanced consistency and reliability by mitigating concentration variations and minimizing the need for human intervention.

Back propagation neural network based proportional-integral hybrid control strategy for a solar methane reforming reactor

To handle the impact of solar radiation fluctuations on the solar reactor, a new proportional-integral (PI) hybrid control strategy based on back propagation neural network (BPNN) is designed in this study to achieve stable operation. Firstly, the BPNN model optimized by genetic algorithm is trained using reactor model simulation data. Then, the BPNN model is combined with PI feedback control to obtain a BPNN-based PI feedforward-feedback hybrid control strategy for regulating the inlet flow rate. Finally, the effectiveness of the control strategy during transient operation under different disturbances is tested. The results show that during actual solar radiation disturbance, the integral square errors (ISE) of outlet hydrogen fraction and methane conversion for BPNN-based PI hybrid control are 7.03 × 10−6 and 1.05 × 10−4, respectively. Compared to traditional PI feedback control, the new hybrid control strategy represents a reduction of 94% and 91% in ISE, indicating that the strategy can significantly improve production stability.

Tracking control of a piezo-actuated compliant mechanism based on an improved Bouc–Wen hysteresis model with variable parameters

To deal with the challenges that the classical Bouc–Wen model fails to precisely characterize amplitude-dependent hysteresis and asymmetric hysteresis, an improved Bouc–Wen model with variable parameters is presented. The proposed model introduces asymmetric terms and parameter functions related to sinusoidal excitation amplitudes into the classical Bouc–Wen model. It has a relatively simple mathematic form and can be easily identified and applied for inverse feedforward compensation in real-time applications. By comparison with the classical Bouc–Wen model and other existing hysteresis models, the superiority of the proposed model has been verified. Furthermore, inverse hysteresis control and hybrid control combining the developed inverse control and proportional-integral feedback control are proposed. Several comparative experiments are conducted on a piezo-actuated micro-scanner. Results demonstrate that inverse control and hybrid control using the improved Bouc–Wen model with variable parameters can achieve better tracking performance and are meaningful in actual trajectory-tracking applications.

Dynamics and control of electrified pressure-swing distillation for separating a maximum-boiling azeotrope featuring small pressure-induced shift

Pressure-swing distillation (PSD) is a typical thermal-driven technique for separating pressure-sensitive azeotropes. By implementing heat pump assisted distillation (HPAD) and self-heat recuperation technology (SHRT), the process can be modified as an electrical-driven one. Previous works have verified the overwhelming steady-state economic advantages of electrified PSDs over a conventional design. However, highly integrated electrified processes could jeopardize the dynamics and controllability. In light of potential dynamic control issues, a demonstrating case of a maximum-boiling acetone/chloroform azeotrope featuring a small pressure-induced shift was studied. Severe snowball effects were observed in these complicated electrified systems. To maintain process stability under throughput and composition disturbances, several robust control structures based on decentralized proportional-integral feedback controllers were developed. These control structures feature temperature controllers with no composition measurement. The results indicate that there is no conflict between the steady-state advantage and dynamic controllability. Therefore, considering the great advantages in economic and environmental aspects of electrified PSD, it is encouraged to extend process electrification measures to other distillation processes.

Proportional Integral Predictive Control of High-Order Fully Actuated Networked Multiagent Systems With Communication Delays

This research is devoted to the cooperative control of high-order fully actuated networked multiagent systems (HOFA-NMASs) with communication delays between network node and sensors, and network node and actuators. A proportional integral (PI) predictive control scheme is developed to effectively implement the cooperation among HOFA-NMASs and actively compensate the communication delays. In this scheme, a local PI feedback controller is applied to stabilize the closed-loop nominal HOFA-NMASs, then a Diophantine equation is presented to establish an incremental HOFA prediction model rather than a reduced-order one, so that the optimization of cost function considered cooperative performance and the compensation of communication delays are completed via multistep output predictions, thus the optimal cooperative controllers are constructed. The further discussion provides a simple condition of simultaneous stability and output consensus of closed-loop HOFA-NMASs, which is easy to verify and extend in practice and is independent on communication delays. An experiment of formation control of air-bearing simulators is shown to prove the availability of the proposed PI predictive control scheme.

Inverse dynamics modelling and tracking control of conical dielectric elastomer actuator based on GRU neural network

This paper presents intelligent modelling and tracking control methods for a conical dielectric elastomer actuator (CDEA) utilized in soft robots. Firstly, an inverse dynamics model (IDM) of the CDEA is established based on a gated recurrent unit neural network. Then, the IDM is directly taken as a feed-forward compensation controller to compensate the complex “memory” characteristic (mainly including the hysteresis nonlinearity and the creep nonlinearity) of the CDEA in its tracking control. Next, a proportional integral feedback controller is devised to cooperate with the compensating controller to enhance the tracking control performance. Lastly, some tracking control experiments with various target trajectories are implemented to demonstrate the validity of the presented methods. Different from traditional methods, using the proposed method can directly construct the compensating controller, thereby avoiding the complicated calculation of the analytical inverse of the dynamics model. Moreover, the fitness values of the results of tracking control experiments are higher than 93.6%, and the root-mean-square errors are lower than 1.3%. Therefore, the proposed intelligent modelling and tracking control methods are superior.

Data-driven fractional order phase-lead and proportional–integral feedback control strategy with application to a reluctance-actuated compliant micropositioning system

This paper aims to overcome complex dynamic problems such as low damping resonant frequency, resonant point drift, and uncertainty of dynamic model of the large stroke micropositioning stage, based on Maxwell reluctance actuator. A composite control method of data-driven fractional phase-lead proportional-integral feedback controller with series hysteresis compensator is proposed. Firstly, the working principle of the Maxwell reluctance actuator is briefly explained, a large stroke flexure micropositioning system is built, and its motor constant and stiffness characteristics are experimentally measured. Secondly, aiming at the rapid phase drop caused by low damping resonance, a data-driven fractional order phase-lead and proportional-integral feedback controller is designed, and the parameters of the fractional order feedback controller are experimentally adjusted based on the iterative feedback tuning algorithm. And the intrinsic hysteresis nonlinearity of the reluctance actuator is firstly compensated by a Prandtl–Ishlinskii model hysteresis compensator which is always placed in the feedback loop of the control system. Then, the proposed controller is compared with other controllers. The experimental results show that this method has a significant suppression effect on high-frequency noise, and the tracking error is significantly reduced, which proves the effectiveness of this stage and control method. • Based on the Maxwell reluctance actuator, a large stroke flexure micropositioning system is built. • A fractional order phase-lead proportional integral controller is proposed, and the integer order approximation of the controller is completed by using oustaloup approximation method • The data-driven method of iterative feedback tuning is used to obtain the parameters of the fractional order controller. • Through the analysis and comparison of linearity, sensitivity function and open-loop frequency response, the advantages of the proposed controller are fully proved.

Data-driven fractional order feedback and model-less feedforward control of a XY reluctance-actuated micropositioning stage.

This paper proposes a compound data-driven control method to solve the problems of low damping resonance, different dynamic properties, and hysteresis in the large-range compliant micropositioning stage driven by a Maxwell reluctance actuator. First, in order to verify the proposed control algorithm, a reluctance-actuated, XY compliant micropositioning stage is constructed according to the principle of operation of a reluctance actuator. Second, in order to eliminate the influence of complex dynamics on the controller design, a fractional order proportional-integral feedback controller is designed using a data iterative feedback turning algorithm. Third, the finite impulse response feedforward filter is optimized using experimental data, and the on-line inverse estimation of the system frequency response function and its iterative feedforward compensation are carried out to further eliminate the influence of light damping resonance. Finally, the proposed control method is used for tracking the experiment and compared with other methods. The experimental results show that the proposed control method can better meet the requirements of high precision, fast speed, and strong anti-interference ability for large stroke micro/nanopositioning and tracking.

Proportional integral feedback control of ultrafiltration rate in hemodialysis

Most hemodialysis patients without residual kidney function accumulate fluid between dialysis session that needs to be removed by ultrafiltration. Ultrafiltration usually results in a decline in relative blood volume (RBV). Recent epidemiological research has identified RBV ranges that were associated with significantly better survival. The objective of this work was to develop an ultrafiltration controller to steer a patient's RBV trajectory into these favorable RBV ranges. We designed a proportional-integral feedback ultrafiltration controller that utilizes signals from a device that reports RBV. The control goal is to attain the RBV trajectory associated with improved patient survival. Additional constraints such as upper and lower bounds of ultrafiltration volume and rate were realized. The controller was evaluated in in silico and ex vivo bench experiments, and in a clinical proof-of-concept study in two maintenance dialysis patients. In all tests, the ultrafiltration controller performed as expected. In the in silico and ex vivo bench experiments, the controller showed robust reaction toward deliberate disruptive interventions (e.g. signal noise; extreme plasma refill rates). No adverse events were observed in the clinical study. The ultrafiltration controller can steer RBV trajectories toward desired RBV ranges while obeying to a set of constraints. Prospective studies in hemodialysis patients with diverse clinical characteristics are warranted to further explore the controllers impact on intradialytic hemodynamic stability, quality of life, and long-term outcomes.

MPD choke control considering the thixotropic gelation behavior of drilling fluids

This study evaluates control algorithms that manage choke pressure during managed pressure drilling applications (MPD) while also taking the thixotropic behavior of drilling fluids into account. This evaluation analyzes proportional-integral (PI) feedback control and proposed preview-based feedback control for choke pressure. A pressure spike can be observed in standpipe and bottomhole pressure after making a drillstring connection or experiencing a prolonged break in drilling operations. This is caused by the gelation of drilling fluids. It is vital to be able to predict the magnitude of such pressure spikes when drilling with active annular pressure control, such that the choke can be effectively controlled to mitigate an induced non-productive time event (i.e., lost circulation events, pump or pipe failures, or well control situations). In this study, a shear-rate and time-dependent thixotropy model is integrated into a rigorously validated transient hydraulics engine with MPD control capabilities. Drilling scenarios are simulated with choke controllers and a case study is presented. When using a preview-based feedback control algorithm, a physics-based model is executed while setpoints are established proactively. The combined capabilities of the physics-based model and the improved MPD controller are demonstrated. Accurately modeling and controlling pressure during drilling operations is essential, especially for wells drilled in narrow-margin environments. The results of our study show that a reactive PI controller is not fast enough to account for transient pressure behavior related to fluid thixotropy. Moreover, the results show that a preview-based feedback controller is more robust and efficient. We demonstrate how a physics-based model can be used in a preview-based control scenario to keep the bottomhole pressure constant with strongly attenuated pressure fluctuations, leading to safer, more optimized operations.

Modeling, Controller Design and Simulation Groundwork on Multirotor Unmanned Aerial Vehicle Hybrid Power Unit

This paper presents the results of modeling, control system design and simulation verification of a hybrid-electric drive topology suitable for power flow control within unmanned aerial vehicles (UAVs). The hybrid power system is based on the internal combustion engine (ICE) driving a brushless DC (BLDC) generator supplying the common DC bus used for power distribution within the aircraft. The overall control system features proportional-integral-derivative (PID) feedback control of the ICE rotational speed using a Luenberger estimator for engine-generator set rotational speed estimation. The BLDC generator active rectifier voltage and current are controlled by proportional-integral (PI) feedback controllers, augmented by estimator-based feed-forward load compensators. The overall control system design has been based on damping optimum criterion, which yields straightforward analytical expressions for controller and estimator parameters. The robustness to key process parameters variations is investigated by means of root-locus methodology, and the effectiveness of the proposed hybrid power unit control system is verified by means of comprehensive computer simulations.

Dynamics and control of thermal- versus electrical-driven pressure-swing distillation to separate a minimum-boiling azeotrope

The implementations of heat integration (HI, thermal-driven), vapor recompression (VRC, electrical-driven), and self-heat recuperation (SHR, electrical-driven) in pressure-swing distillation (PSD) are available for providing energy saving and CO2 emission reduction over the conventional design (CONV, thermal-driven), exemplified by a minimum-boiling tetrahydrofuran/water. Approximately a 20 % decrease in total annual cost (TAC) and over 25 % CO2 emission reduction can be reached by using these measures. However, these steady-state advantages sometimes go along with decreases in controllability, so it is necessary to investigate the dynamics and control of these highly integrated and interacting processes. Robust temperature control structures based on decentralized proportional-integral (PI) feedback controllers are developed to tackle ± 20% disturbances in throughput and feed composition. For the thermal-driven processes, the PSD-CONV is easily controlled with the single-end control strategy. Based on that, the effective control of PSD-HI is achieved by either pressure compensation or bypass strategy. Regarding the complicated electrical-driven arrangements, the dynamic responses of PSD-VRC and PSD-SHR indicate their controllability is comparable to those of a regular sequence. These results demonstrate that there are no conflicts between the steady-state advantages and dynamic controllability for this specific separation. Meanwhile, these electrical-driven processes can be considered to extend to other minimum-boiling azeotropes owing to their economic and environmental advantages.

Critical values of cyber parameters in a dynamic microgrid system

An islanded microgrid is cyber-physical system, and the control relies on the communication system significantly. Improper parameters of the cyber system can result in instability of a microgrid system. To evaluate the impact of a networked control system on control performance, a cyber model is developed to represent data acquisition periods and communication delays. Simplification of the networked control system model is proposed to enhance the computational performance, making the analytical method applicable for large-scale systems. Based on the analysis, a two-dimensional stability region of a microgrid in the space of cyber parameters can be obtained. To validate the proposed method, a microgrid control scheme is proposed for power dispatch and regulation based on the droop and proportional-integral (PI) feedback control. The analytical method is compared to the time-domain simulation, and it is shown that the stability regions are nearly identical. The critical values of cyber parameters are determined based on the analytical results. The proposed control strategy with the given cyber parameters is validated for transient stability following dynamic events. Simulation results indicate that the design of a microgrid as a cyber-physical system needs to be guided by critical values for cyber parameters to prevent system instability.

Design, modeling, and control of a monolithic compliant x-y-θ microstage using a double-rocker mechanism

This paper reports the design, modeling, and control of a novel three-degrees-of-freedom piezoelectric compliant microstage by introducing a new double-rocker mechanism. The double-rocker mechanism combines a first (leverage) amplifier and a second (rocker) amplifier for double-stage displacement amplification and parasitic motion reduction. An analytical model is established to calculate the deformation behavior of the microstage, and the model is verified using finite-element analysis (FEA). An improved Prandtl-Ishlinskii (PI) model is proposed to describe piezoelectric hysteresis characteristics by optimizing the threshold selection. Then, a composite control strategy is designed to achieve precision trajectory control. The control strategy consists of a hysteresis-based feedforward controller and a proportional-integral feedback controller. A prototype of the microstage is manufactured, and an experimental system is established. Several open-loop and closed-loop experiments are conducted, and the experimental results validate the effectiveness of the proposed microstage and the designed control strategy.

High-performance state feedback controller for permanent magnet synchronous motor

Due to the outstanding characteristics of permanent magnet synchronous motor (PMSM), such as fast response speed, high torque and power density, it has been widely used in the automation industry. However, it remains a challenge to obtain high control performance caused by its dynamic complexity. In order to achieve favorable control performance, a novel state feedback control algorithm and parameter tuning method for permanent magnet synchronous motor is proposed in this paper. The development of the presented control method starts with the analyses of current state–space equation in rotor reference frame and then provides the design procedure of state feedback controller from the first-order to third-order system. An enhanced Proportional–Integral (PI) plus state feedback controller is designed, which includes the information of current, the error of current and the integral of the current error. The stability and convergence of the proposed control approach, as the extension of the conventional PI regulator, is mathematically justified in state feedback theory. The simulation and experimental results compared with the classical state feedback control method illustrate that the proposed PI plus state feedback control scheme can obtain better control performance in the presence of parameter changes and disturbance.

Model-Based Analysis of Feedback Control Strategies in Aerobic Biotrickling Filters for Biogas Desulfurization

Biotrickling filters are one of the most widely used biological technologies to perform biogas desulfurization. Their industrial application has been hampered due to the difficulty to achieve a robust and reliable operation of this bioreactor. Specifically, biotrickling filters process performance is affected mostly by fluctuations in the hydrogen sulfide (H2S) loading rate due to changes in the gas inlet concentration or in the volumetric gas flowrate. The process can be controlled by means of the regulation of the air flowrate (AFR) to control the oxygen (O2) gas outlet concentration ([O2]out) and the trickling liquid velocity (TLV) to control the H2S gas outlet concentration ([H2S]out). In this work, efforts were placed towards the understanding and development of control strategies in biological H2S removal in a biotrickling filter under aerobic conditions. Classical proportional and proportional-integral feedback controllers were applied in a model of an aerobic biotrickling filter for biogas desulfurization. Two different control loops were studied: (i) AFR Closed-Loop based on AFR regulation to control the [O2]out, and (ii) TLV Closed-Loop based on TLV regulation to control the [H2S]out. AFR regulation span was limited to values so that corresponds to biogas dilution factors that would give a biogas mixture with a minimum methane content in air, far from those values required to obtain an explosive mixture. A minimum TLV of 5.9 m h−1 was applied to provide the nutrients and moisture to the packed bed and a maximum TLV of 28.3 m h−1 was set to prevent biotrickling filter (BTF) flooding. Control loops were evaluated with a stepwise increase from 2000 ppmv until 6000 ppmv and with changes in the biogas flowrate using stepwise increments from 61.5 L h−1 (EBRT = 118 s) to 184.5 L h−1 (EBRT = 48.4 s). Controller parameters were determined based on time-integral criteria and simple criteria such as stability and oscillatory controller response. Before implementing the control strategies, two different mass transfer correlations were evaluated to study the effect of the manipulable variables. Open-loop behavior was also studied to determine the impact of control strategies on process performance variables such as removal efficiency, sulfate and sulfur selectivity, and oxygen consumption. AFR regulation efficiently controlled [O2]out; however, the impact on process performance parameters was not as great as when TLV was regulated to control [H2S]out. This model-based analysis provided valuable information about the controllability limits of each strategy and the impact that each strategy can have on the process performance.

Anoxic biogas biodesulfurization promoting elemental sulfur production in a Continuous Stirred Tank Bioreactor

Biological desulfurization of biogas has been extensively studied using biotrickling filters (BTFs). However, the accumulation of elemental sulfur (S°) on the packing material limits the use of this technology. To overcome this issue, the use of a continuous stirred tank bioreactor (CSTBR) under anoxic conditions for biogas desulfurization and S° production is proposed in the present study. The effect of the main parameters (stirring speed, N/S molar ratio, hydraulic residence time (HRT) and gas residence time (GRT)) on the bioreactor performance was studied. Under an inlet load (IL) of 100 g S-H2S m–3 h–1 and a GRT of 119 s, the CSTBR optimal operating conditions were 60 rpm, N/S molar ratio of 1.1 and a HRT of 42 h, in which a removal efficiency (RE) and S° production of 98.6 ± 0.4 % and 88 % were obtained, respectively. Under a GRT of 41 s and an IL of 232 g S-H2S m–3 h–1 the maximum elimination capacity (EC) of 166.0 ± 7.2 g S-H2S m–3 h–1 (RE = 71.7 ± 3.1 %) was obtained. A proportional-integral feedback control strategy was successfully applied to the bioreactor operated under a stepped variable IL.

Hybrid controller for precision positioning application

In this paper, a precision positioning hybrid controller for long travel distance with submicron/nanometer resolution and accuracy is designed and developed. A hybrid control algorithm is designed to combine the coarse positioning system and a precision positioning system. The coarse positioning system consists of a linear stepper motor and coarse positioning controller, which is designed by microstepping with proportional-integral (PI) current feedback (MSPICF) control. In the precision positioning system, a piezoelectric actuator (PZA) is used. The mathematical model of the PZA has been represented by 2nd order mass-spring system with the Dahl hysteresis model and the model parameters are estimated by an autoregressive with exogenous terms (ARX) model identification technique using the input–output experimental data. The precision positioning controller designed by feedforward (FF) control which is the inverse of the mathematical model of the PZA and feedback (FB) control. The coarse, precision and hybrid controller is implemented using a low-cost DsPIC30F4012 microcontroller. Experiments have been performed to evaluate the performance of the controller.

Control of regenerative catalytic oxidizers used in coal mine ventilation air methane exploitation

Ventilation air methane in coal mining has an important environmental impact, since methane is a strong greenhouse gas (1kg of methane is equivalent to 28kg of carbon dioxide). The oxidation of methane in regenerative oxidizers can be an attractive technique to exploit this resource. Thus, part of the heat released by the reaction can potentially be recovered, in addition to decreasing methane environmental impact. However, the concentration of methane in the mine ventilation air may change considerably with respect to the oxidizer design value, which have negative consequences. An increase in concentration can produce overheating (with possible damage to the unit), while a decrease in concentration may cause the extinction of the reaction. In this work, three control systems have been considered in order to deal with these issues: proportional-integral-derivative (PID) and proportional-integral (PI) feedback controllers, and model predictive controller (MPC).The control action is based on regulating the heat extracted from the oxidizer by adjusting a hot gas purge from the centre of the reactor. First, the control systems have been designed (i.e. the tuning parameters of the controller have been calculated). To carry out the design of the controllers, a simplified dynamic model was obtained from a complex model of the oxidizer. Then, the performance of the controlled oxidizer has been simulated for different types of disturbances. In these simulations, the simple PID controller performed well, and the MPC exhibited the fastest response.