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Poor stability of the permanent magnet electrodynamic levitation hinders its application in the maglev field. Therefore, building a control-oriented model to improve its stability is most challenging. However, intractable electromagnetic models leading to an implicit relationship between levitation force and gap, yields a barrier for model-based controller design. To solve the above-mentioned problem, this paper develops a control-oriented model by two stages. Specifically, the first stage is to show an explicit formula of the levitation force with regard to the levitation gap by neglecting end effect; meanwhile the “maximum–minimum rectification” method is put forward to evaluating an accurate levitation force. The second stage is to bring forth the control-oriented model on basis of the estimated levitation force. Although the paper focus mainly on the development of the control-oriented model, an example of PD controller is provided to verify its validation. Experiment results demonstrate the estimated levitation force is highly consistent with the real one. Simulation results show that the control-oriented model is sufficiently reliable. The research bridges the gap between the physical model and the model-based controller for the electrodynamic levitation with permanent magnet Halbach array.

The purpose of this study is to develop a model for the gas exchange process in a rebreathing homogeneous charge compression ignition (HCCI) engine. HCCI engines are attracting significant attention due to their low emissions and high efficiency. To design the control system of an HCCI engine, it is necessary to develop a control-oriented engine model. The developed model lowers its computational load by combining two types of models. The model consists of a discrete model for the exhaust process (the first half of the gas exchange process) and a continuous model with a variable calculation step size for the rebreathing process (the latter half of the gas exchange process). Also, the constructed model maintained its prediction accuracy, as the pressure pulsation in the exhaust port was modeled, and an unsteady flow equation was used. It was confirmed that the model developed for the gas exchange process calculated in about half time of one cycle and reproduced the results of 1D engine simulation software with a maximum error of about 10% in the in-cylinder pressure, temperature, and trapped mass.

This paper proposes model reduction techniques for reducing engine airpath models in real-time (RT), for a control oriented application in an engine equipped with high pressure exhaust gas recirculation (EGR-HP) and single stage turbocharger. There are two major challenges addressed by authors: First, reducing the order without compromising the performance in terms of accuracy by decoupling the nonlinear coupled differential equations of airpath system in-order to use them in real-time processor-in-loop control application. A model reduction technique based on different dynamic characteristics between thermodynamic states followed by semi-implicit Euler (SIE) numerical method to solve coupled dynamic multi-input multi-output (MIMO) differential equation models is demonstrated. Second, the authors have proposed a novel method to calculate gas mass flow via compressor, coupled with engine airpath model in real-time. The proposed models of airpath system coupled with turbocharger models for a diesel engine is validated with experimental data to evaluate performance of pressures, temperatures, mass flows at relevant components. The developed airpath model is used for calculating thermodynamic properties in real-time for state of art engine control unit (ECU) in production engine and become basis for feedforward as well as closed loop control of airpath variables for real-time system. Authors further propose to use this modeling approach for calculating airpath system variables for exhaust aftertreatment system, injection system, and for virtualization of sensor values in airpath systems.

This paper presents a model to incorporate the secondary effects of wake steering in large arrays of turbines. Previous models have focused on the aerodynamic interaction of wake steering between two turbines. The model proposed in this paper builds on these models to include yaw-induced wake recovery and secondary steering seen in large arrays of turbines when wake steering is performed. Turbines operating in yaw-misaligned conditions generate counter-rotating vortices that entrain momentum and contribute to the deformation and deflection of the wake at downstream turbines. Rows of turbines can compound the effects of wake steering that benefit turbines far downstream. This model quantifies these effects and demonstrates that wake steering has greater potential to increase the performance of a wind farm due to these counter-rotating vortices especially for large rows of turbines. This is validated using numerous large-eddy simulations for three-turbine, five-turbine, and wind farm scenarios.

The wheeled mobile robots have recently become a better choice for repetitive tasks and especially in the agricultural field, but the existing constraint remains in its electrical motor, either in its consumption or its control. Therefore, we will focus on the Brushless Direct Current Motor (BLDCM) included on the robot wheels. Hence, the objective of this paper is to provide a model of BLDCM to have both maximum torque and a reduced torque ripple. Indeed, it is important to give a mathematical model that correctly represents the motor in three phases reference frame. To reduce the complexity of the model, we have used the extended park reference frame, which provides a biphasic representation in order to control the current using Proportional Integral Controller (PI Controller). The angular velocity of the motor is controlled using two types of regulators; ones called PI Controller and the other is Fuzzy Logic Controller (FLC) to compare its performance. The motor is attached to an inverter, which is controlled using a Full-Wave offset method. The modeling machine is done and validated using MATLAB Simulink Library. The simulation results of the modeling system are evaluated to have the profile of the wheel speed rotating freely, and the energetic efficiency of the BLDCM during functioning.

As requirements for continuously improving internal combustion engine fuel economy with satisfactory emissions, model-based control strategies are often used to optimize the combustion process. To apply advanced control techniques for closed-loop engine combustion control, control-oriented engine combustion models are necessary and they are physics-based, accurate enough for model-based control, computationally low cost, and capable of real-time simulations. In addition, control-oriented combustion model with adequate fidelity may need to adapt to physical system and environment changes over time to maintain model-based control performance, such as model-reference (guided) control, where the control-oriented combustion model runs in real-time to generate an error signal between physical system and reference-model output for feedback control. This paper provides a review of existing control-oriented engine combustion models, along with their associated applications. Three main groups of control-oriented combustion models are reviewed from simple to sophisticated physics-based dynamic models, including mean-value, Wiebe function-based, and reaction-based models. The fundamental principle of each model group is reviewed briefly and its applications are also addressed. At the macro level, a control-oriented engine model can be used for crank angle-based and/or cycle-based control. As the engine control hardware performance continuous improving with reduced cost, model-reference (guided) combustion control shall become reality since now it is feasible to run a physics-based control-oriented engine combustion model inside an engine control module. On the other hand, each model group, even for the simple mean-value model, has its own applicable scenarios.

In this article, we derive a mechanical distributed parameter model for the annular sector plate segments of the Extremely Large Telescope’s deformable mirror M4. Additionally, we modally analyse t...

Reliable prediction of future blood glucose (BG) values is of high relevance for diabetes patients, since it enables the use of predictive glucose alarms (warning the patient about impending situations with dangerously low or high BG), as well as of model-based algorithms for smart glucose control. Control-oriented graybox process models have proven very suitable for such tasks, especially when identified on data from clinical trials under well-defined conditions. The current paper analyzes how such models can also be reliably parametrized using outpatient data of patients on multiple daily injection (MDI) therapy. A dedicated preprocessing algorithm is presented to look for suitable (i.e. complete and sensible) data segments that allow for a reliable system identification. The focus of the current paper is on the prediction of postprandial glucose trajectories, more specifically on predictions made exactly at the time of meal ingestion. This corresponds to a particularly challenging task, but one with high importance for the model-based optimization of insulin doses. It is demonstrated that the identified process models are a suitable choice for predicting such postprandial glucose excursions.

Today several modelling and control synthesis methods are available to construct accurate aircraft representations and a large portion of these tools are appropriate for educational use. It is extremely beneficial for students studying in related areas to be able to construct and evaluate such vehicle systems, since it allows them to gain experience with aircraft dynamics and control without requiring a great amount of resources. However, the connections between these methods are not necessarily straightforward for someone who has never taken part in creating such representations. To provide an aid in this process, widely researched and used methods are collected and assembled into a well-structured framework for modelling, analysis and control of conventional aircraft. The framework is complemented with additional options to model unconventional aspects, such as the flexibility of an airframe or the deformation of a morphing wing. The result is a broadly applicable modelling scheme, appropriate to be used for educational purposes. The goal of the paper is to present the main aspects of the framework through unconventional aircraft examples.

A new non-unique $\Theta $ -inverse of non-square polynomial matrices is presented in this paper. It is shown that the above inverse specializes to the unique Moore-Penrose one under several specific assumptions. Due to the existence of some degrees of freedom, the $\Theta $ -inverse outperforms the Moore-Penrose inverse in various inverse-related problems covering the multivariable control theory. In many scenarios the former inverse can stabilize a closed-loop control plant being unstable by application of the Moore-Penrose formula. Practical and theoretical simulation examples confirm the correctness of the proposed method.

This article focuses on developing a strategy for control of systems, whose dynamics are almost entirely unknown. This situation arises naturally in a scenario, where a system undergoes a critical failure. In that case, it is imperative to retain the ability to satisfy basic control objectives in order to avert an imminent catastrophe. To deal with limitations on the knowledge of system dynamics, we develop a theory of myopic control. At any given time, myopic control optimizes the current direction of the system trajectory, given solely the knowledge about system dynamics obtained from data until that time. We propose an algorithm that uses small perturbations in the control effort to learn system dynamics around the current system state, while ensuring that the system moves in a nearly optimal direction, and provide bounds for its suboptimality.

In this article, two data-driven modeling approaches are investigated, which allow an explicit modeling of uncertainty. For this purpose, parametric Takagi-Sugeno multi-models with bounded-error parameter estimation and nonparametric Gaussian process regression are applied and compared. These models can for instance be used for robust model-based control design. As an application, the prediction of residual stresses during hard turning depending on the machining parameters and the initial hardness is considered.

De-oiling hydrocyclones are a promising choice for produced-water treatment in the oil and gas industry. The compact nature of hydrocylones makes them suitable for offshore and subsea installations...

In this work, a low-order model designed for glucose regulation in Type 1 Diabetes Mellitus (T1DM) is obtained from the UVA/Padova metabolic simulator. It captures not only the nonlinear behavior of the glucose-insulin system, but also intra-patient variations related to daily insulin sensitivity (SI) changes. To overcome the large inter-subject variability, the model can also be personalized based on a priori patient information. The structure is amenable for linear parameter varying (LPV) controller design, and represents the dynamics from the subcutaneous insulin input to the subcutaneous glucose output. The efficacy of this model is evaluated in comparison with a previous control-orientedmodel which in turn is an improvement of previous models. Both models are compared in terms of their open- and closed-loop differences with respect to the UVA/Padova model. The proposed model outperforms previous T1DM control-oriented models, which could potentially lead to more robust and reliable controllers for glycemia regulation., Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales

This work focuses on zero-dimensional modeling of the heat release rate in a compression ignition engine operating on gasoline-like fuels. Due to the properties of gasoline, such as high volatility and longer ignition delay than diesel, the injection strategies can vary significantly from the operation with conventional diesel fuel. Different injection strategies are commonly used to achieve varying degrees of in-cylinder stratification in order to shape the combustion event and maximize efficiency. The proposed zero-dimensional combustion model was developed to account for the different stages in combustion caused by the fuel stratification. As the ignition delay model is an integral part of the entire combustion process and significantly affects the prediction accuracy, special attention has been paid to local phenomena influencing ignition delay. A one-dimensional spray model by Musculus and Kattke was employed in conjunction with a Lagrangian tracking approach in order to estimate the local air–fuel ratio within the spray tip, as a proxy for reactivity. The local air–fuel ratio, in-cylinder temperature and pressure were used in an integral fashion to estimate the ignition delay. Heat release rates were modeled using first-order non-linear differential equations. The proposed combustion model was validated against experimental data of a heavy-duty compression ignition engine with up to three injection events at mostly 1038 r/min and 14 bar brake mean effective pressure. Further validation of the model was carried out at other engine loads and speeds. Model prediction errors in CA50 of less than 1 °CA across all conditions were found. Modeling results of other combustion metrics such as combustion duration and indicated mean effective pressure are also highly satisfactory. In addition, the model has been shown to be capable of estimating the ringing intensity for most conditions.

The Open Daylight platform with its power by working with IEEE 802.1X port level authentication for wired and wireless networks has been very supportive because of the massive deployments at mean charge for main design considerations. Within the current marketplace, 802.1X has flourished the ground works for wireless, wire stability, LAN stability and authentication methods. EAP (Extensible Authentication Protocol) supports long time protection of the supplicant and the authentication software till the end condition of the RADIUS (Remote Authentication Dial-In User Service) server is met. This paper is focused on the RAR (RADIUS Access Request) unique identification about the users on the network with SAA (Supplicant, Authenticator and Authentication server) system which records on the attribute cost of RFC 2865 according to the forwarding server. NAA (Non-Adaptive Algorithm) using FlowVisor based virtualization packages drive inward the network timescales or statistics, dynamically controlling the flow space of switches to control the speed and results in scaling of networks. NAA is an application level protocol that contains authentication and configuration information between a Network Access Server and a shared authentication server. It avoids the attacker from listening for requests and responses from the server and calculates the improved MD5 client secret key of the response.

Roll yaw coupled dynamics are not well characterized and existing low cost models are limited in range of applicability. We utilize an interpolation based approach to address a wider range of conditions with reduced computational requirements. By interpolating test data to estimate hydrodynamic forces and empirically modeling roll damping and added mass, we establish a 4DOF maneuvering model for prismatic planing hulls in calm water. It is validated against relevant tests and show significant computational resource savings in comparison with potential flow based methods. Simulation of an extreme turning maneuver and an asymmetrical loading case demonstrates its potential for use in initial design, control and evaluation.

Diesel engines equipped with ignition assist devices such as glow plugs may improve combustion behavior at low temperatures and with low cetane fuels found in remote fields. The coordination of injection timing and the energy input of the ignition assist needs to continuously adjust to maintain the best combustion phasing at all conditions. However, most diesel engines do not use closed-loop combustion control and operate in a sub-optimal manner because the dispersion of combustion phasing, also known as cycle-to-cycle variability, requires careful feedback controller design. This work presents an initial investigation of a control-oriented model that captures the average and statistical influence of commercial glow plugs used for ignition assist beyond the start-up phase. Experiments were conducted at a single speed and load operating point as a proof of concept to obtain a model that quantifies the combustion phasing statistics and thus can guide feedback control design. The developed phenomenological model includes the engine’s thermal state because it impacts combustion behavior over the course of repeated experiments. The 3-term mean phasing model and 2-term standard deviation model estimate start of combustion within 0.6 and 0.2 crank angle degrees, respectively, and can be readily expanded to more operating conditions.

The main purpose of the shutdown purge is to reduce the residual moisture inside the stack and improve the water storage capacity in the cold start process and thereby reduce icing damage. ...

3D digitalization of the human body has been studied extensively for various applications in anthropology, ergonomics, healthcare, entertainment and fashion industries. There are different methods and approaches to reconstruct the 3D body model namely using RGB cameras, depth cameras, scanning systems or anthropometric measurements of the human body. Generally, most of existing approaches have to tackle issues relating to security of personal data, the impact of the surrounding environment, cost of 3D scanning systems and complication of anthropometric measurements. This study proposes a method using simple body measurements and given body shapes to digitalize the human body. The effectiveness of proposed method is evaluated and demonstrated based on two datasets: a synthetic dataset generated from a parametric model and a real dataset on Vietnamese collected by Viettel Military Industry and Telecoms Group (Vietnam).

This study examines whether intellectual capital and corporate culture affects financial performance in Indonesia. Data are drawn form 34 sample of publicly bank that listed in Indonesia Stock Exchange (IDX). Intellectual capital using VAIC method and the four type of corporate culture (collaboration oriented/COL, control oriented/CON, competition oriented/COM, dan creation oriented) using ATLAS.ti following the bag of words by Fiordelisi & Ricci (2014). We find evidence that intellectual capital, collaboration oriented - culture (COL), creation – oriented culture (CRE) are positevely related to financial performance. Competition – oriented culture (COM) is negatively related to financial performance, while the last type of corporate culture: control – oriented culture (CON) is not relayed to financial performance.

In this study, a multiple-input multiple-output feedforward controller for use with multiple-point fuel injection systems is applied to a diesel engine using an original control-oriented model. The target-tracking performance of this multiple-input multiple-output feedforward controller was then tested in terms of how well the controller adjusts the fuel delivery ratios to the pilot injection, pre-injection, main fuel injection, and the main fuel injection timing, and controls the in-cylinder peak pressure and its timing. Control experiments are conducted at different engine outputs and speeds while changing the targets of the in-cylinder peak pressure and its timing. The controller is able to track the varying targets within an acceptable error included in the original model. The calculation time, which is almost double that of a single-input single-output controller, is sufficiently fast to derive the applicable inputs.

Exhaust gas temperature is one of the main parameters under engine manufacturers' focus due to its effects on both turbocharger durability and catalyst efficiency. Typically, the measurement of such variable at the test bench is carried out by using thermocouples (TCs), which are not available for on-board applications. For this reason, an accurate and reliable model for Real-Time (RT) calculation of this variable is particularly important. In this work a control-oriented model for the estimation of exhaust temperature in Spark Ignition (SI) engines is developed and validated exploiting experimental data. A fundamental quantity that has to be necessarily known is the temperature of the gas within the exhaust manifold or at the Exhaust Valve Opening (EVO). The first part of this paper deals with the development of a zero-dimensional (0-D) combustion model, identifying the main parameters of the Wiebe function with an automatic optimization routine. Such method allows to accurately reproduce the in-cylinder pressure trace and calculate the temperature of the gas at EVO. Hence, an analytical function that converts such temperatures into the exhaust manifold ones is developed by analyzing the experimental measurements of TCs installed in the exhaust manifold under steady-state operating conditions. This is the main reason why the proposed approach cannot be considered fully empirical. The resulting 0-D model is not suitable for an RT application nor to be implemented in an Engine Control Unit (ECU) due to a differential equation that needs to be solved in the angular domain. For this reason, in the second part of the article, a control-oriented model is developed by using an analytical methodology, which exploits the combustion model and the temperature analytical function presented in the first part. Finally, the control-oriented model is coupled with a TC dynamics RT model, and both are validated under transient conditions.

The scramjet model used in the control system needs to consider both accuracy and real-time requirements. In this paper, a quasi-one dimensional component level model method for scramjet is proposed. Under the premise of meeting the real-time requirement, this modeling method has higher calculation accuracy, and can obtain higher thrust performance without exceeding the limits. In order to improve the calculation accuracy of the scramjet model, the boundary layer correction and the interaction between shock wave and boundary layer are considered in the inlet and isolator modeling process by using reference temperature method. For the scramjet compression components, the inlet and isolator models are simplified based on shock train theory to improve real-time performance. Meanwhile, the combustor model and nozzle model are established and the combustor model is established with the combination of equal area and isothermal based on temperature limitation. Considering the boundary layer correction, the accuracy of the inlet and isolator model is improved by 8.79 and 7.9% respectively. Compared with the equal area combustion mode, the combined combustion mode can get higher thrust. In the C + + simulation environment, the average calculation time of each state point is about 25 ms which meets the real-time requirements.

This chapter outlines the fundamentals of air path modeling for the purpose of optimization-based control. First, an overview of the requirements is given. To realize appropriate real-time optimization, a suitable trade-off is needed between the accuracy of a model and its computational complexity. Additionally, if gradient-based methods are applied for a numerical solution of the optimization problem, models are required that are continuously differentiable. Gray-box modeling is proposed as a suitable solution. Wherever it is computationally feasible, models based on first principles are applied. When such first-principle models become very complex, data-driven approaches are investigated instead. Based on these considerations, the various components of the air path are reviewed and suitable models are proposed. Among the components investigated are volumes, flow restrictions, and turbochargers.

The incoming emission regulations for internal combustion engines are gradually introducing new pollutant species, which requires greater complexity of the exhaust gas aftertreatment systems concerning layout, control and diagnostics. This is the case of ammonia, which is already regulated in heavy-duty vehicles and to be included in the emissions standards applied to passenger cars. The ammonia is injected into the exhaust gas through urea injections for NOx abatement in selective catalytic reduction (SCR) systems and can be also generated in other aftertreatment systems as three-way catalysts. However, ammonia slip may require removal on a dedicated catalyst called ammonia slip catalyst (ASC). The set consisting of the urea injection system, SCR and ASC requires control and on-board diagnostic tools to ensure high NOx conversion efficiency and minimization of the ammonia slip under real driving conditions. These tasks are based on the use of NOx sensors ZrO2 pumping cell-based, which present as a drawback high cross-sensitivity to ammonia. Consequently, the presence of this species can affect the measurement of NOx and compromise SCR-ASC control strategies. In the present work, a methodology to predict ammonia and NOx tailpipe emissions is proposed. For this purpose, a control-oriented ASC model was developed to use its ammonia slip prediction to determine the cross-sensitivity correction of the NOx sensor placed downstream of the ASC. The model is based on a simplified solution of the transport equations of the species involved in the main ASC reactions. The ammonia slip model was calibrated using steady- and quasi-steady-state tests performed in a Euro 6c diesel engine. Finally, the performance of the proposed methodology to predict NOx and ammonia emissions was evaluated against experimental data corresponding to Worldwide harmonized Light vehicles Test Cycles (WLTC) applying different urea dosing strategies.

[EN] In this work, a methodology is proposed to standardize turbochargers testing based on measuring the maps twice: in close to adiabatic and in diathermal conditions. Along the paper, it is discussed with special detail the impact of the procedure followed to achieve said quasi-adiabatic conditions in both the energy balance of the turbocharger and the testing complexity. As a conclusion, the paper proposes a methodology which combines quasi-adiabatic tests (cold and hot gas flow) with diathermal tests (hot gas flow) in order to extract from a turbocharger gas-stand all information needed by engine designers interested in controlling or one-dimensional-modeling the internal combustion engine (ICE). The methodology is completed with a guide for calibrating said control-oriented turbocharger models in order to separate aerodynamic efficiency (adiabatic) from heat transfer (HT) losses and from friction losses in the analysis of the turbocharger performance. The outsourced calibration of the turbocharger model allows avoiding uncertainties in the global ICE model calibration, what is very interesting for turbochargers benchmarking at early ICE-turbo matching stages or for global system analysis at early control design stages., Alejandro Gomez Vilanova is partially supported through contract Subprograma 1 (PAID-01-18) of Universitat Politecnica de Valencia. This work was partially funded ayuda a Primeros Proyectos de Investigacion (PAID-06-18), Vicerrectorado de Investigacion, Innovacion y Transferencia of Universitat Politecnica de Valencia

The paper presents novel control-oriented transport models for evaporating liquid films in the tubes of a falling film evaporator. In this context, our goal consists in qualitatively mapping the experimentally observed input-output behavior. Two transport models are proposed, where the difference between them is that one allows overtaking of liquid particles and the other does not. The transport models are equipped with two new models of evaporation which are different from the commonly assumed uniform evaporation. The models are initially developed from the conservation laws in the form of partial differential equations. Using the method of characteristics we then obtain the input-output relations for the proposed models in the form of time-delay equations. The time-delay representation is advantageous for simulation and for the future control design. In a simulation study, we observe the principal properties of the models and find that they correspond well with the experimentally observed input-output behavior.

With the deepening research on wind farms, wake effects have gradually been paid attention to and used in wind farm optimization. During this development, the engineering wake models are adopted, which could be further improved in modeling accuracy. This paper adopts a control-oriented wake model to improve the modeling accuracy, especially in the near wake region. A double-Gaussian wake model is incorporated with appropriate wake deflection and combination models and a vertical wind profile function. Based on a Large-eddy simulated dataset, the proposed model is adopted and verified. The widely-used Gaussian wake model is also adopted and compared with the proposed model. Results show good agreement between the presented model and LES results, especially in the focused near wake region.

Although many studies have been carried out using control-oriented engine models for advanced combustion technologies, methods of adapting model parameters for these models have still not been considerably studied. In this paper, we propose a method to adapt model parameters for an ignition model and a combustion model of a physics-based discrete diesel engine model using neural networks. Using experimental data on an engine bench as well, we examined how to perform adapting and training, such as optimization algorithms, how to select training data, appropriate feature values, and algorithms for switching the neural networks according to the operating regions. As a result, this adaptation method was able to improve the prediction accuracy of the heat release rate of pre-combustion better than when adapted using the previous adaptation method and when the model parameters were fixed.

A control-oriented model is presented that can capture the prior-cycle correlation of combustion cycles during conditions with high levels of exhaust gas recirculation (EGR). Combustion events are modeled in discrete time and the dynamic evolution is captured by the residual air, fuel, and inert gas trapped in the combustion chamber. The mathematical formulation of the model is presented together with the calibration procedure to emulate a particular engine operating condition. A cycle-to-cycle system identification methodology is described which allows regressing model parameters from experimental data. Simulations are presented and compared to real engine measurements to show the modeling potential for analysis and control of combustion events.

Modern Diesel engines have become highly complex multi-input multi-output systems. Controls of modern Diesel engines to meet various requirements such as high fuel efficiency and low NOx and particulate matter (PM) emissions, remain a great challenge for automotive control community. While model-based controls have demonstrated significant potentials in achieving high Diesel engine performance. Complete and high-fidelity control-oriented Diesel engine models are much needed as the foundations of model-based control system development. In this study, a semi-physical, mean-value control-oriented model of a turbocharged Diesel engine equipped with high-pressure exhaust gas recirculation (EGR) and variable geometry turbocharger (VGT) is developed and experimentally validated. The static calibration of Diesel engine model is achieved with the least-square optimization methodology using the experimental test data from a physical Diesel engine platform. The normalized root mean square errors (NRMSEs) of the calibration results are in the range of 0.1095 to 0.2582. The cross-validation results demonstrated that the model was capable of accurately capturing the engine torque output and NOx emissions with the control inputs of EGR, VGT and Start of Injection timing (SOI) in wide-range operating conditions.

Biofeedback mechanisms affect the overall efficacy of the medical experience in different ways; while being often a suitable approach to improve and enable efficient treatments, they might also lead to unexpected, unplanned or even undesired effects. Motivated by these considerations, we discuss the problem of detecting whether specific designs of biofeedback mechanisms lead to unexpected, unplanned or undesired behaviors in the specific case of gamified pelvic floor muscles exercising. To solve the problem we use a control-theoretic framework, and ladder on the construction of a online estimator of the intentions of the patients in performing muscle activity. We propose thus to use a mixed model- and data-driven framework for which a parametric model is first opportunely identified and then used to forecast the behavior of the patient. This model, in conjunction with the data collected under the influence of biofeedback, is then used to investigate the resulting changes in patients’ intentions in real life settings, and report quantitative assessments on the performance of the overall scheme in field tests.

A microbial fuel cell (MFC) is a potentially viable renewable energy option which promises effective and commercial harvesting of electrical power by bacterial movement and at the same time also treats wastewater. Microbial fuel cells are complicated devices and therefore research in this field needs interdisciplinary knowledge and involves diverse areas such as biological, chemical, electrical, etc. In recent decades, rapid strides have taken place in fuel cell research and this technology has become more efficient. For effective usage, such devices need advanced control techniques for maintaining a balance between substrate supply, mass, charge, and external load. Most of the research work in this area focuses on experimental work and have been described from the design perspective. Recently, the development in mathematical modeling of such cells has taken place which has provided a few mathematical models. Mathematical modeling provides a better understanding of the operations and the dynamics of MFCs, which will help to develop control and optimization strategies. Control-oriented bio-electrochemical models with mass and charge balance of MFCs facilitate the development of advanced nonlinear controllers. This work reviews the different mathematical models of such cells available in the literature and then presents suitable parametrization to develop control-oriented bio-electrochemical models of three different types of cells with their uncertain parameters.