Model-based Feedback Research Articles

Effects of water induced pore blockage and mitigation strategies in low temperature PEM fuel cells – A simulation study

Ineffective water management in proton exchange membrane fuel cells (PEMFCs) can cause performance degradation. A simple mathematical model capturing the effect of water on the overall performance of the fuel cell system is of immense use in developing tools for water management. In this work, a computationally efficient first principles dynamic model for PEMFC system simulations and concomitant water management studies are developed. The steady-state version of this model is validated with experimental data. The effect of various operating conditions and design parameters on the performance of the fuel cell is studied using this model. Various control strategies for improving fuel cell performance in the presence of flooding are evaluated using the model. The simplicity and adequate predictive capability of the model make it amenable to be used in a model-based feedback control framework for online water management.

Dynamic modeling of a sensible thermal energy storage tank with an immersed coil heat exchanger under three operation modes

In this paper we consider control-oriented modeling of a sensible thermal energy storage (TES) tank with a helical immersed heat exchanger (IHX) coil. A key focus of the modeling approach is to minimize the number of dynamic states required to adequately describe the system dynamics. The resulting model is well-suited for model-based control design, real-time simulation, and hardware-in-the-loop testing aimed at intelligent operation of TES systems. We use a discretized approach to model the temperature dynamics of the water within the storage tank. We use a quasi-steady approach to model the IHX coil dynamics, thereby limiting computational complexity. In simulation, the model runs up to 1200× faster than real-time. A simulated case study of model-based feedback control demonstrates the utility of the modeling approach. The model contains four tuning parameters that are empirically determined using experimental data collected from a commercially available domestic hot water storage tank. The model is then validated, both temporally and spatially, against data collected during the simultaneous charge/discharge mode. Finally, we quantify the trade-off between model fidelity and increased control volume discretization, showing that a 60 node model yields a RMSE value under 4.5%.

Simultaneous feedback control of plasma rotation and stored energy on NSTX-U using neoclassical toroidal viscosity and neutral beam injection.

A model-based feedback system is presented enabling the simultaneous control of the stored energy through βn and the toroidal rotation profile of the plasma in National Spherical Torus eXperiment Upgrade device. Actuation is obtained using the momentum from six injected neutral beams and the neoclassical toroidal viscosity generated by applying three-dimensional magnetic fields. Based on a model of the momentum diffusion and torque balance, a feedback controller is designed and tested in closed-loop simulations using TRANSP, a time dependent transport analysis code, in predictive mode. Promising results for the ongoing experimental implementation of controllers are obtained.

Simultaneous Travel and Hoist Maneuver Input Shaping Control Using Frequency Modulation

This paper presents an input shaping control system for overhead crane operations involving simultaneous hoist and travel maneuvers. The control system utilizes model-based partial feedback linearization with frequency modulation. Traditional input shaping controllers target specific system frequencies. Therefore, they are incapable of accommodating the time dependant frequency associated with simultaneous hoist and travel crane maneuvers. Frequency modulation is used to tune the time-dependent system frequency to the design frequency of a primary input shaping controller. Partial feedback linearization is used to eliminate the time-dependent damping of the system. The primary input shaper frequency is based on lowest operating frequency of the system associated with the longest hoisting cable length operation. Simulations results, using primary zero-vibration (ZV) and zero-vibration-derivative (ZVD) input shapers, are presented. General arbitrary input travel and hoist commands are simulated. Results demonstrate the ability of the proposed control system to eliminate residual oscillations in all simulated cases.

Enhancing model-based feedback perimeter control with data-driven online adaptive optimization

Most feedback perimeter control approaches that are based on the Macroscopic Fundamental Diagram (MFD) and are tested in detailed network structures restrict inflow from the external boundary of the network. Although such a measure is beneficial for the network performance, it creates virtual queues that do not interact with the rest of the traffic and assumes small unrestricted flow (i.e. almost zero disturbance). In reality, these queues can have a negative impact to traffic conditions upstream of the protected network that is not modelled. In this work an adaptive optimization scheme for perimeter control of heterogeneous transportation networks is developed and the aforementioned boundary control limitation is dropped. A nonlinear model is introduced that describes the evolution of the multi-region system over time, assuming the existence of well-defined MFDs. Multiple linear approximations of the model (for different set-points) are used for designing optimal multivariable integral feedback regulators. Since the resulting regulators are derived from approximations of the nonlinear dynamics, they are further enhanced in real-time with online learning/adaptive optimization, according to performance measurements. An iterative data-driven technique is integrated with the model-based design and its objective is to optimize the gain matrices and set-points of the multivariable perimeter controller based on real-time observations. The efficiency of the derived multi-boundary control scheme is tested in microsimulation for a large urban network with more than 1500 roads that is partitioned in multiple regions. The proposed control scheme is demonstrated to achieve a better distribution of congestion (by creating “artificial” inter-regional queues), thus preventing the network degradation and improving total delay and outflow.

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.

Feedback control of electrical stimulation electrode arrays

Electrical stimulation electrode arrays are an emerging technology that enables muscles to be artificially contracted through the activation of their associated motor neurons. A principal application of electrical stimulation is to assist human motion for orthotic or therapeutic purposes. This paper develops a framework for the design of model-based electrode array feedback controllers that balance joint angle tracking performance with the degree of disturbance and modeling mismatch that can exist in the true underlying biomechanical system. This framework is used to develop a simplified control design procedure that is suitable for application in a clinical setting. Experimental results evaluate the feasibility of the control design approach through tests on ten participants using both fabric and polycarbonate electrode arrays.

Promoting Representational Competence with Molecular Models in Organic Chemistry

Mastering the many different diagrammatic representations of molecules used in organic chemistry is challenging for students. This article summarizes recent research showing that manipulating 3-D molecular models can facilitate the understanding and use of these representations. Results indicate that students are more successful in translating between diagrams when they have models available, that using a model to enact the translation process in the world is predictive of learning, and that using models as feedback (to check the accuracy of diagram translation) is particularly effective. Model-based feedback is superior to verbal feedback alone, models scaffold learning rather than act as a crutch, learning with model-based instruction is resilient over a delay of several days, and learning with models transfers to performance when models are no longer available. Finally, virtual models are equivalent to hand-held models in promoting learning in the studied contexts.

Effectiveness of prednisone and low dose of IVIG in RM treatment in patients with elevated NK cytotoxicity associated with hyperandrogenism

Model-based feedback control is developed for a continuous granulation process addressing the challenge of time delay and physics-based input-output constraints. The process plant is a multi-input multi-output (MIMO) linear model with time delay. A robust H∞ controller is designed using the mixed sensitivity loop shaping design. A framework has been laid down to insure the robustness of the Smith predictor by incorporating the model mismatch as an additive uncertainty in the predictor’s structure. The control performance and robustness is assessed by simulations for regulation and reference tracking problems. We show significant performance gains by employing a Smith predictor and the technique of reference updating: The control is coping significantly better with time delay, physical constraints and model mismatch. The proposed control approach is more efficient as compared to other widely used methods such as model predictive control (MPC); obtaining a stable behaviour of the response and control effort while forcing them to remain within the desired bounds.

Model manipulation and learning: Fostering representational competence with virtual and concrete models.

This study investigated the development of representational competence among organic chemistry students by using 3D (concrete and virtual) models as aids for teaching students to translate between multiple 2D diagrams. In 2 experiments, students translated between different diagrams of molecules and received verbal feedback in 1 of the following 3 intervention conditions: with concrete models, with virtual models, or without models. Following the intervention, diagram translation accuracy was measured in 3 posttests, which were with models, without models, and after a 7-day delay. The virtual models in the 2 experiments differed in the level of congruence between the actions performed with the input device and the resulting movement of the virtual model. Study 1 used a low congruence interface and Study 2 used a high congruence interface. Students learned more when models were available. In terms of learning outcomes, model-based feedback was superior to verbal-feedback alone, models served as a learning scaffold rather than a crutch, and learning with model-based feedback was resilient over a 7-day delay. Finally, concrete and virtual models were equivalent in promoting learning, and action-congruence of the interface did not affect learning. The results are discussed with respect to their implications for instruction in organic chemistry and science, technology, engineering, and mathematics disciplines more generally. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

Model-based control of vortex shedding at low Reynolds numbers

Model-based feedback control of vortex shedding at low Reynolds numbers is considered. The feedback signal is provided by velocity measurements in the wake, and actuation is achieved using blowing and suction on the cylinder’s surface. Using two-dimensional direct numerical simulations and reduced-order modelling techniques, linear models of the wake are formed at Reynolds numbers between 45 and 110. These models are used to design feedback controllers using $$\mathcal {H}_\infty $$ loop-shaping. Complete suppression of shedding is demonstrated up to Re $$=$$ 110—both for a single-sensor arrangement and for a three-sensor arrangement. The robustness of the feedback controllers is also investigated by applying them over a range of off-design Reynolds numbers, and good robustness properties are seen. It is also observed that it becomes increasingly difficult to achieve acceptable control performance—measured in a suitable way—as Reynolds number increases.

Global robust output regulation of multivariable systems with nonlinear exosystem

Summary It is well known that multi-input, multi-output nature of nonlinear system and generalized exosystem have posed some challenges to output regulation theory. Recently, the global robust output regulation problem for a class of multivariable nonlinear system subject to a linear neutrally stable exosystem has been studied. It has been shown that a linear internal model-based state feedback control law can lead to the solution of previous problem. In this paper, we will further study the global robust output regulation problem of the system subject to a nonlinear exosystem. By utilizing nonlinear internal model design and decomposing the multi-input control problem into several single-input control problems, we will solve the problem by recursive control law design. The theoretical result is applied to the non-harmonic load torque disturbance rejection problem of a surface-mounted permanent magnet synchronous motor. Copyright © 2016 John Wiley & Sons, Ltd.

Modeling and control of plasma rotation for NSTX using neoclassical toroidal viscosity and neutral beam injection

A model-based feedback system is presented to control plasma rotation in a magnetically confined toroidal fusion device, to maintain plasma stability for long-pulse operation. This research uses experimental measurements from the National Spherical Torus Experiment (NSTX) and is aimed at controlling plasma rotation using two different types of actuation: momentum from injected neutral beams and neoclassical toroidal viscosity generated by three-dimensional applied magnetic fields. Based on the data-driven model obtained, a feedback controller is designed, and predictive simulations using the TRANSP plasma transport code show that the controller is able to attain desired plasma rotation profiles given practical constraints on the actuators and the available measurements of rotation.

Control of an exothermic packed-bed tubular reactor

The problem of robustly controlling a highly exothermic gas-phase packed-bed tubular reactor on the basis of feed and reactor temperature measurements is addressed. First, advanced nonlinear control yields a detailed model-based output feedback (OF) control design with passivity and observability solvability conditions, sensor location criterion, and simple tuning. Then, the behavior of the advanced controller is recovered with a simplified model-based realization that amounts to an industrial temperature tracking controller with feedforward (FF) dynamic setpoint compensation. The advanced and industrial controllers are formally connected. The approach is illustrated and tested with a representative case example through numerical simulations.

Interval model control of human welder’s movement in machine-assisted manual GTAW torch operation

Torch maneuver skills possessed by a skilled welder typically require a long time to develop. A machine-assisted feedback control system that can stabilize the welder movement would thus be of interest in the manufacturing industry. In this paper, an interval model-based feedback control system is designed to assist the welder to adjust the torch movement for tracking desired speed in manual gas tungsten arc welding (GTAW) process. To this end, an innovative helmet-based manual welding platform is utilized. In this system, vibrators are installed on the helmet to generate vibration sounds to instruct the welder to speed up or slow down the torch movement. The torch movement is monitored by a leap motion sensor. The torch speed is used as the feedback for the control algorithm to determine how to change the vibrations. To design the control algorithm, dynamic experiments are conducted to correlate the arm movement (torch speed) to the vibration control signal. Linear models are first identified and the corresponding linear parameter intervals are obtained. Interval model control algorithm is then implemented. Simulation results reveal that the proposed interval model control algorithm outperforms traditional Proportion Integration Differentiation (PID) controller. Experiments further verified that the welder’s speed is controlled with acceptable accuracy.

Model-Based Transmission Control

Abstract This article presents an overview of model-based transmission control. The transmission is an integral part of the automotive powertrain and connects the engine to the vehicle via the driveline. Just as for the internal combustion engine, traditional transmission control has been conducted with extensive calibrations. This is mainly due to the lack of precise models and low cost sensors that can enable real-time model-based feedback control. However the calibration-based approach is facing more challenges as the recent trend in transmission systems has driven up the time and cost associated with the calibration process. Recently, eight and nine speed transmissions have been introduced. The increasing number of different types of transmissions and the gear ratios can drastically increase the burden for control calibration. This calls for control-oriented model development and model-based control. Transmission control is mainly concerned with the transmission shift scheduling and gear ratio shift control. This shift scheduling determines when to shift and which gear to shift.

Physics-based control-oriented modeling and robust feedback control of the plasma safety factor profile and stored energy dynamics in ITER

Many challenging plasma control problems still need to be addressed in order for the ITER plasma control system (PCS) to be able to maintain the plasma within a predefined operational space and optimize the plasma state evolution in the tokamak, which will greatly aid in the successful achievement of ITER’s goals. Firstly in this work, a general control-oriented, physics-based modeling approach is developed to obtain first-principles-driven (FPD) models of the plasma magnetic profile and stored energy evolutions valid for high performance, high confinement (H-mode) scenarios, with the goal of developing model-based closed-loop algorithms to control the safety factor profile (q profile) and stored energy evolutions in the tokamak. The FPD model is tailored to H-mode burning plasma scenarios in ITER by employing the DINA-CH & CRONOS free-boundary tokamak simulation code, and the FPD model’s prediction capabilities are demonstrated by comparing the prediction to data obtained from DINA-CH & CRONOS. Secondly, a model-based feedback control algorithm is designed to simultaneously track target q profile and stored energy evolutions in H-mode burning plasma scenarios in ITER by embedding the developed FPD model of the magnetic profile evolution into the control design process. The feedback controller is designed to ensure that the closed-loop system is robust to uncertainties in the electron density, electron temperature and plasma resistivity, and is tested in simulations with the developed FPD model. The effectiveness of the controller is demonstrated by first tracking nominal q profile and stored energy target evolutions, and then modulating the generated fusion power while maintaining the q profile in a stationary condition. In the process, many key practical issues for plasma profile control in ITER are investigated, which will be useful for the development of the ITER PCS that has recently been initiated. Some of the more pertinent investigated issues are the time necessary to drive the q profile and stored energy to a target evolution, and whether plasma control can be achieved through the use of separate individual control algorithms or whether a more fully integrated approach is required.

Feedback Linearization Control of a Cardiovascular Circulatory Simulator

In this brief, a nonlinear model-based feedback linearization (FBL) control is proposed for a high-performance cardiovascular circulatory simulator (CCS). The challenges are that the piston pump used for a mock ventricle in CCS has high-bandwidth pressure dynamics and hard nonlinearity due to check valves. Limited control performance in the previous researches due to these difficulties even raises the question of the physiological feasibility of the developed CCS. To overcome this problem, FBL theory based on the Lie algebra is applied in this research for the piston pump mock ventricle control. Dynamic model of the piston pump was derived, and parameter values of the model were identified experimentally for the controller design. The experimental results confirmed good performance of the proposed controller for various physiological scenarios. Good match with the reference model behavior was verified as well, and physiological feasibility of the CCS was secured thereby thanks to the proposed high-performance controller.

Design of [formula omitted] adaptive controllers for human patient anesthesia

In this paper, the development and implementation of L1 adaptive control designs for anesthesia delivery to patients in surgical settings is presented. Our main objectives are the design of model-based feedback controllers ensuring that the patient׳s bispectral index profile tracks a prespecified reference trajectory, and demonstrates robustness to inter-patient variability. Patient models are constructed based on clinical trial data and gray box system identification methods. Controller switching mechanisms and specific safety measures are considered in the design and discussed in the paper. Simulation results are provided, demonstrating the effectiveness of the control methods.

A Layer-To-Layer Model and Feedback Control of Ink-Jet 3-D Printing

Ink-jet 3-D printing is a promising additive manufacturing technology with the potential for impacting a wide variety of industries. In typical ink-jet 3-D printing, the part is built up by depositing droplets layer upon layer in an open-loop manner, while curing each layer after it is deposited. Droplet and edge dimensions are typically predicted through extensive experimentation and are assumed to remain constant throughout the printing process. However, there is no guarantee of the consistent droplet shape and dimensions or the smoothness of the finished parts due to the inherent uncertainty in the process. To address this issue, we propose a model-based feedback control law for ink-jet 3-D printing that uses a height sensor for measuring profile height after each layer for determining the appropriate layer patterns for subsequent layers. Toward this goal, a model describing the relationship between height profile change and droplet deposition in the layer building process is first proposed and experimentally identified. Based on this model, a closed-loop layer-to-layer control algorithm is then developed for the ink-jet printing process. The proposed algorithm uses a model predictive control algorithm to minimize the difference between the predicted height and the desired height and the predicted surface unevenness after a fixed number of layers. We also present an extension of the algorithm for two-material printing, which can enable printing of complex 3-D geometry (by using a support material for overhang). Experimental and simulation results show that the algorithm is able to achieve more consistent shapes between layers, reduced edge shrinking of the part, and a smoother top layer surface.