Model-based Feedback Control Strategy Research Articles

Quantifying the impact of electric fields on single-cell motility

Cell motility in response to environmental cues forms the basis of many developmental processes in multicellular organisms. One such environmental cue is an electric field (EF), which induces a form of motility known as electrotaxis. Electrotaxis has evolved in a number of cell types to guide wound healing and has been associated with different cellular processes, suggesting that observed electrotactic behavior is likely a combination of multiple distinct effects arising from the presence of an EF. To determine the different mechanisms by which observed electrotactic behavior emerges, and thus to design EFs that can be applied to direct and control electrotaxis, researchers require accurate quantitative predictions of cellular responses to externally applied fields. Here, we use mathematical modeling to formulate and parameterize a variety of hypothetical descriptions of how cell motility may change in response to an EF. We calibrate our model to observed data using synthetic likelihoods and Bayesian sequential learning techniques and demonstrate that EFs bias cellular motility through only one of a selection of hypothetical mechanisms. We also demonstrate how the model allows us to make predictions about cellular motility under different EFs. The resulting model and calibration methodology will thus form the basis for future data-driven and model-based feedback control strategies based on electric actuation.

Effective dose delivery in atmospheric pressure plasma jets for plasma medicine: a model predictive control approach

Atmospheric pressure plasma jets (APPJs) have been identified as a promising tool for plasma medicine. This paper aims to demonstrate the importance of using model-based feedback control strategies for safe, reproducible, and therapeutically effective application of APPJs for dose delivery to a target substrate. Key challenges in model-based control of APPJs arise from: (i) the multivariable, nonlinear nature of system dynamics, (ii) the need for constraining the system operation within an operating region that ensures safe plasma treatment, and (iii) the cumulative, nondecreasing nature of dose metrics. To systematically address these challenges, we propose a model predictive control (MPC) strategy for real-time feedback control of a radio-frequency APPJ in argon. To this end, a lumped-parameter, physics-based model is developed for describing the jet dynamics. Cumulative dose metrics are defined for quantifying the thermal and nonthermal energy effects of the plasma on substrate. The closed-loop performance of the MPC strategy is compared to that of a basic proportional-integral control system. Simulation results indicate that the MPC stategy provides a versatile framework for dose delivery in the presence of disturbances, while the safety and practical constraints of the APPJ operation can be systematically handled. Model-based feedback control strategies can lead to unprecedented opportunities for effective dose delivery in plasma medicine.

Load management: Model-based control of aggregate power for populations of thermostatically controlled loads

Large groups of electrical loads can be controlled as a single entity to reduce their aggregate power demand in the electricity network. This approach, known as load management (LM) or demand response, offers an alternative to the traditional paradigm in the electricity market, where matching supply and demand is achieved solely by regulating how much generation is dispatched. Thermostatically controlled loads (TCLs), such as air conditioners (ACs) and fridges, are particularly suitable for LM, which can be implemented using feedback control techniques to regulate their aggregate power. To achieve high performance, such feedback control techniques require an accurate mathematical model of the TCL aggregate dynamics. Although such models have been developed, they appear too complex to be effectively used in control design. In this paper we develop a mathematical model aimed at the design of a model-based feedback control strategy. The proposed model analytically characterises the aggregate power response of a population of ACs to a simultaneous step change in temperature set points. Based on this model, we then derive, and completely parametrise in terms of the ACs ensemble properties, a reduced-order mathematical model to design an internal-model controller that regulates aggregate power by broadcasting temperature set-point offset changes. The proposed controller achieves high LM performance provided the ACs are equipped with high resolution thermostats. With coarser resolution thermostats, which are typical in present commercial and residential ACs, performance deteriorates significantly. This limitation is overcome by subdividing the population into clusters of ACs that receive a coarse-grained, cluster-dependent control signal. The proposed clustering technique recovers the performance achieved with high resolution thermostats at the expense of some additional comfort penalty, which can be quantified using the controller output.

Limitations and performances of robust control over WSN: UFAD control in intelligent buildings

The aim of this paper is to propose a model-based feedback control strategy for indoor temperature regulation in buildings equipped with underfloor air distribution. Supposing distributed sensing and actuation capabilities, a zero-dimensional model of the ventilation process is derived, based on the thermodynamics properties of the flow. A state-space description of the process is then inferred, including discrete events and non-linear components. The use of a wireless sensor network and the resulting communication constraints with the IEEE 802.15.4 standard are discussed. Both synchronous and asynchronous transmissions are considered. Based on the linear part of the model, different H-infinity robust multiple-input multiple-output (MIMO) controllers are designed, first with a standard mixed-sensitivity approach and then by taking into account the network-induced delay explicitly. The impact of the communication constraints and the relative performances of the controllers are discussed based on simulation results.

A Hybrid Model and MIMO Control for Intelligent Buildings Temperature Regulation over WSN

The aim of this paper is to propose a model-based feedback control strategy for indoor temperature regulation in buildings equipped with underfloor air distribution (UFAD). Supposing distributed sensing and actuation capabilities, a 0 – D model of the ventilation process is first derived, based on the thermodynamics properties of the flow. A state-space description of the process is then inferred, including discrete events modeled by Markovian processes. This results in a hybrid model with nonlinear components. The use of a wireless sensor network (WSN) and the resulting communication constraints are also discussed. A H∞ MIMO controller is finally proposed and shown to effectively handle the discrete and nonlinear perturbations.

06/00093 Modeling of flashing-induced instabilities in the start-up phase of natural-circulation BWRs using the two-phase flow code FLOCAL: Manera, A. et al. Nuclear Engineering and Design, 2005, 235, (14), 1517–1535

The aim of this paper is to address the problem of suppressing unstable dynamics occurring in rectangular natural circulation loops on the base of a reliable model-based controller.The first part of the study is devoted to define a high order model, through the reduction by truncation of the Fourier series expansion of the functions describing the loop geometry of Navier–Stokes infinite-dimensional partial differential equations describing the flow, the heating conditions and the temperature distribution of the fluid. The first three modes were considered so that a closed model of seven ordinary differential equations was obtained. The model was then integrated and simulations compared with experimental data, confirming its ability to address the description of the dynamical behaviour of rectangular natural circulation loops.The satisfactory performances of the model lead to use it for the design and experimental testing of model-based feedback control strategies. In particular, a traditional proportional-derivative control approach has been applied to the model linearised around its equilibrium points. The flow velocity or an opportunely selected temperature difference between given points of the loop were chosen as feedback variables. Accordingly, the target of the control action was to drive the feedback variable to its stationary value, computed by means of the mathematical model. Experimental validation of the proposed model-based strategies satisfactorily demonstrated the capability of the approach in stabilising the system dynamics.

MODEL BASED BRAKING CONTROL WITH SUPPORT BY ACTIVE STEERING

Model based feedback control strategies for electrohydraulic braking and active steering systems in passenger cars are considered. Simulation results with a complex vehicle model and measurements from test drives with a real car are shown for brake control. For a μ-split road surface additional drive dynamics control is required like ESP or active front steering (AFS). Therefore, an AFS feedback controller is applied to stabilize the vehicle. Furthermore, the braking control is improved by AFS, assisting the driver to brake in critical situations.

Modelling and control of rectangular natural circulation loops

The aim of this paper is to address the problem of suppressing unstable dynamics occurring in rectangular natural circulation loops on the base of a reliable model-based controller. The first part of the study is devoted to define a high order model, through the reduction by truncation of the Fourier series expansion of the functions describing the loop geometry of Navier–Stokes infinite-dimensional partial differential equations describing the flow, the heating conditions and the temperature distribution of the fluid. The first three modes were considered so that a closed model of seven ordinary differential equations was obtained. The model was then integrated and simulations compared with experimental data, confirming its ability to address the description of the dynamical behaviour of rectangular natural circulation loops. The satisfactory performances of the model lead to use it for the design and experimental testing of model-based feedback control strategies. In particular, a traditional proportional-derivative control approach has been applied to the model linearised around its equilibrium points. The flow velocity or an opportunely selected temperature difference between given points of the loop were chosen as feedback variables. Accordingly, the target of the control action was to drive the feedback variable to its stationary value, computed by means of the mathematical model. Experimental validation of the proposed model-based strategies satisfactorily demonstrated the capability of the approach in stabilising the system dynamics.

Model Based Control of Voids and Product Thickness during Autoclave Curing of Carbon/Epoxy Composite Laminates

In this article we present a novel feedback control strategy for the autoclave curing of carbon/epoxy laminates. The strategy utilizes an on-line model of the process to control the quality by adjusting the cure cycle. On line measurements are used to correct for modeling errors. The quality variables of interest here are the thickness of the product laminate and the maximum void size present in the laminate. Artificial neural networks are utilized to regress past operational data to generate nonlinear models for predicting the product quality. These models utilize properties of the raw material prepreg and secondary measurements taken while the process cycle is in progress. Some results of a control study done using a simulated model of a process for autoclaving a carbon fiber/epoxy resin system are also reported. The main contribution of this paper is the successful demonstration of a neural network model based feedback control strategy for autoclave curing. While discussion in this paper is limited to control of the autoclave process, the methodology suggested is also equally applicable to other composite manufacturing processes.