Closed-loop Cases Research Articles

FPGA real-time melt-pool temperature control in Directed Energy Deposition

Sensing and control are key in laser-based Directed Energy Deposition (DED-LB) in terms of repeatability and good quality builds. This work presents a real-time control system where the melt-pool temperature is monitored, and the laser power is adjusted in closed-loop as control parameter. The control system includes a Field-Programmable Gate Array (FPGA) for the real-time estimation of the melt-pool temperature extracted from data from a coaxial high-speed hyperspectral camera, and a Proportional-Integral (PI) controller for the laser power regulation. The controller gains are tuned to ensure constant temperature during deposition. However, different sets of gains, with differences in the response time and transient behavior of the controller, achieve this goal but produce different deposition quality. The presented paper discusses the impact of the different controller gains on the melt-pool temperature and melt-pool size during the deposition of thin-walls and squared spirals, and compares open-loop (without control) and closed-loop (with control) cases.

System modeling and temperature control for a fuel cell system based on local model networks

ABSTRACT Fuel cells have been studied for use in stationary power generation and vehicle propulsion systems. The fuel cell thermal management subsystem is coupled and nonlinear, posing challenges for modeling and temperature control. This paper aims to integrate the physical models of the fuel cell stack, pump, thermostat, and other components combined with intelligent algorithms into an efficient system-level thermal management model framework and develop a model predictive controller to solve the temperature control problem. First, a physics-based nonlinear model of the fuel cell system is developed and used as a basis to identify the linearized model for different operating points. Then, the global model is obtained by fusing the local models with Gaussian validity functions using the local linear model tree method. Third, a multi-step prediction model is derived based on the local model networks, and a parameterized linear state space form is obtained and used for controller design. Furthermore, an online correction method is developed to reduce the model discrepancy. Finally, the accuracy of the system model and the performance of the proposed controller are verified by open-loop experimental data and a series of closed-loop simulation cases.

Build your own closed loop: Graph-based proof of concept in closed loop for autonomous networks

Next Generation Networks (NGNs) are expected to handle heterogeneous technologies, services, verticals and devices of increasing complexity. It is essential to fathom an innovative approach to automatically and efficiently manage NGNs to deliver an adequate end-to-end Quality of Experience (QoE) while reducing operational expenses. An Autonomous Network (AN) using a closed loop can self-monitor, self-evaluate and self-heal, making it a potential solution for managing the NGN dynamically. This study describes the major results of building a closed-loop Proof of Concept (PoC) for various AN use cases organized by the International Telecommunication Union Focus Group on Autonomous Networks (ITU FG-AN). The scope of this PoC includes the representation of closed-loop use cases in a graph format, the development of evolution/exploration mechanisms to create new closed loops based on the graph representations, and the implementation of a reference orchestrator to demonstrate the parsing and validation of the closed loops. The main conclusions and future directions are summarized here, including observations and limitations of the PoC.

On the informativity of direct identification experiments in dynamical networks

Data informativity is a crucial property to ensure the consistency of the prediction error estimate. This property has thus been extensively studied in the open-loop and in the closed-loop cases, but has only been briefly touched upon in the dynamic network case. In this paper, we consider the prediction error identification of the modules in a row of a dynamic network using the full input approach. Our main contribution is to propose a number of easily verifiable data informativity conditions for this identification problem. Among these conditions, we distinguish a sufficient data informativity condition that can be verified based on the topology of the network and a necessary and sufficient data informativity condition that can be verified via a rank condition on a matrix of coefficients that are related to a full-order model structure of the network. These data informativity conditions allow to determine different situations (i.e., different excitation patterns) leading to data informativity. In order to be able to distinguish between these different situations, we also propose an optimal experiment design problem that allows to determine the excitation pattern yielding a certain pre-specified accuracy with the least excitation power.

Case Study of a Hybrid Geothermal-Solar System

The usage and management of renewable energy have become a topic of interest since existing literature suggests that it would replace fossil fuels. In this study, an analysis of a closed-loop hybrid geothermal-solar energy system is introduced to control air temperature. This can be used in different air-conditioning applications including greenhouses, living quarters, and buildings. Such a case study was carried out in Damanhur city, Beheira Governorate, Egypt. First, the air produced from the proposed hybrid system conditioned the air of a room with the dimensions of L 2m x W 2m x H 2m. Geothermal energy was used to transfer heat to/from an air stream flowing inside a 5 m long, 2 inches in diameter, and 5.3 mm thickness PVC pipe. The pipe was buried 2 m below the ground’s surface and was supported by a solar chimney during the winter for the natural draft of air stream. In addition, a numerical model was built with 9 closed-loop geothermal cases of different design conditions. The pipe’s diameter varied in different cases from 0.17, 0.35, and 0.65 m, while the total pipe length was 47, 64, and 87 m. After that, the air stream was supplied to a room with the dimensions of L 3m x W 3m x H 3m. The air was subject to a 1m long solar chimney at 45ᵒ angle on a horizontal plane. The results of the numerical model prove that the maximum room temperature difference, which is close to 5 ᵒC, can be achieved using a pipe with a diameter of 0.65 m, and a length of 87 m. The validation of the numerical model was carried out using experimental results.

Dynamic response analysis of aircraft with actuation system failure: open-loop and closed-loop cases

On flight control implementation, the control surface actuator system plays one of the key roles that will significantly affect the closed-loop performance of the aircraft. The actuators must provide the required effort for moving the control surface so that the desired control action can be reached. Any failure on the actuator system will limit or degrade the operation of the control surface, so that it will affect the performance of the system in controlling the aircraft, or even worse, may bring the aircraft into an unsafe condition. In this project, the effect of some control surface problems due to actuator failures are modeled, simulated, and analyzed. To reconstruct the situation, the control device failure model is integrated into the flight dynamic model of an aircraft. The numerical model of the equation then is used for simulating the aircraft response under some failure conditions. It can be seen from the simulation results that control surface failure can significantly affect the trim condition of the aircraft, since the failures can change the balance of forces and moments that work on the aircraft. The simulation results also show that for some control surface failures may initiate an asymmetrical response from the aircraft dynamics. On closed-loop simulations, where some type of flight control systems for stabilization and maneuvering tasks are implemented, control surface failures may affect the performance of the control system. The results of the study suggest that any possibilities of control surface failure must be anticipated, by using a robust control scheme or other reconfigurable schemes that can cope with the change in the dynamic characteristics due to the failures.

Active vibration control analysis in smart composite structures using ANSYS

Piezoelectric Macro-Fiber Composite (MFC) utilization is increasing in engineering fields due to its strong actuation forces and high flexibility. In this paper, piezoelectric ( ) type (M8528-P1) patches are applied for active control of a cantilever composite beam. A linear coupled finite element model for piezoelectric MFC actuation of the composite beam was developed based on the APDL-ANSYS codes by using linear piezoelectric constitutive equations to study smart composite beam behavior in open and closed-loop cases. Active vibration control response of laminated composite beams with various stacking sequence configurations was examined, and the results were compared. In this, the proportional type (kp) of control algorithms is utilized, and in the summary of work refined two sets of finite element models. The first set their laminates to have an orientation (0 with 90), and others have an orientation (0 with 45). When the control signal applied with the gain (kp) to a system increases, the rise time generally decreases, the actuator voltages for different control gain for all cases are observed with the increase in the proportional constant. The findings of this study indicate that the composite beams composed from (0/90) stacking sequence sets had reached stability state faster than the composite beams composed from (0/45) stacking sequence sets.

On robustness against disturbances of passive systems with multiple invariant sets

Robustness of stability with respect to external perturbations is an important property characterising the ability of the dynamics to counteract the influence of uncertainties. In the present paper, such a property is investigated for the class of passive and strictly passive systems, which have several invariant compact and globally attracting subsets in the unforced scenario. It is assumed that the storage and supply rate functions are sign-definite with respect to these sets. The results are obtained within the framework of input-to-state stability and integral input-to-state stability for multistable systems. The robustness conditions are obtained for open-loop and for closed-loop cases, i.e. when an output feedback is required to guarantee robustness. Two applications (related to the model of multispecies populations) of the proposed theory are used to illustrate its efficiency.

Stochastic Norton–Simon–Massagué Tumor Growth Modeling: Controlled and Mixed-Effect Uncontrolled Analysis

Tumorigenesis is a complex process that is heterogeneous and affected by numerous sources of variability. This article proposes a stochastic extension of a biologically grounded tumor growth model, referred to as the Norton-Simon-Massagué (NSM) model. First, we study the uncontrolled version of the model where the effect of the chemotherapeutic drug agent is absent. Conditions on the model's parameters are derived to guarantee the positivity of the solution of the proposed stochastic NSM model and hence its validity to describe the dynamics of tumor volume. The proof of positivity makes use of a Lyapunov-type method and the classical Feller's test for explosion. To calibrate the proposed model, we utilize a population mixed-effect modeling formulation and a maximum likelihood-based estimation algorithm. The identification algorithm is tested by fitting previously published tumor volume mice data. Second, we study the controlled version of the model, which includes the effect of chemotherapy treatment. Analysis of the influence of adding the control drug agent into the model and how sensitive it is to the stochastic parameters is performed both in open- and closed-loop viewpoints. The designed closed-loop control strategy that solves an optimal cancer therapy scheduling problem relies on the model predictive control (MPC) combined with extended Kalman filter approaches. The simulation results and concluding guiding principles are provided for both the open-and closed-loop control cases.

Vibration analysis of a free moving thin plate with fully covered active constrained layer damping treatment

A comprehensive dynamic model for a free moving thin plate with fully covered active constrained layer damping (ACLD) treatment is developed. The discrete equations of motion of the moving ACLD plate are derived by using Ritz method and Lagrange’s equations. Free vibration analysis of the composite plate undergoing large rotational or translational motions are performed by solving the complex modal eigenvalue problem of the system in open-loop and closed-loop cases. Interesting frequency curve veering, mode shape switching as well as damping ratio jumping phenomena are observed and discussed for the plate rotating around two different axes. It is demonstrated that the flexible plate undergoing rigid motions can not only generate dynamic stiffening effect but also dynamic softening effect. Effects of parameters such as angular velocity, acceleration, and control gain on the modal and damping characteristics of the ACLD plate are also investigated.

Advanced method for neutronics and system code coupling RELAP, PARCS, and MATLAB for instrumentation and control assessment

The operation of current nuclear power plants (NPP) and the deployment of advanced nuclear reactors rely on digital instrumentation and control (I&C) and information technology systems. The growing use of digital systems implies considerable security and safety challenges, as the usual standard codes used for designing, licensing, and analyzing accidents over the last few decades have been limited in terms of I&C features. This study presents an innovative method to couple PARCS/RELAP5 with the high-performance language MATLAB/Simulink. As a proof-of-concept proof, a 2772 MWt pressurized water reactor modeled using the coupled package PARCS/RELAP5 is simulated. A supervisory system is implemented that allows MATLAB/Simulink to oversee the nuclear codes for exchanging online data. In addition, I&C high-level computing tools are added to the NPP model, endorsing the application of “on-the-fly” decision logics. The coding strategy does not change the nuclear binary source codes, as the PARCS/RELAP5 codes have been validated for design and licensing. By running open- and closed-loop cases for control rod assembly movement, we found that PARCS/RELAP5 capabilities for digital I&C modeling and simulations can be extended by adding MATLAB/Simulink flexibility.

Magneto-rheological dampers—model influence on the semi-active suspension performance

Recently, automotive industry has adopted semi-active damper systems to improve handling and comfort properties of vehicles. Nowadays, Magneto-Rheological (MR) dampers are among the most effective solutions; with the control algorithm used for their operation being a key element. While basic controllers do not require mathematical damper models, improved performance can be achieved if these are available. Usually, the accuracy of a particular set of models can be assessed by evaluating standard quantitative metrics. However, two models with similar error-metrics can still have widely different qualitative properties. In this context, the main aim of this paper is to study the effects that may appear in the closed-loop performance of an automotive suspension system when the damper model is unable to represent crucial nonlinear MR phenomena. To highlight the model influence on the controller synthesis and subsequently on the suspension performance, two damper models with different accuracy levels were chosen: an Artificial Neural Networks (ANN)-based model is compared with the classical Bingham model. First, their accuracy is experimentally validated using typical error-metrics. Afterwards, the same suspension control strategy is designed using both models. Frequency-Estimation-Based control was selected because it better exploits available model data than other typical strategies such as sky-hook. The resulting performance is assessed with a software-in-the-loop approach using CarSim® and complemented with a hardware-in-the-loop implementation using a CAN-bus, both closed-loop control cases use a Simulation-Oriented ANN model as benchmark to represent the MR damper nonlinearities. Results show that although the difference in error-metrics between models can be small using typical identification methods (e.g. 16% in one scenario), suspension performance in comfort and road-holding are significantly different. Error-metrics can be deceptive for assessing the effectiveness of MR damper models during the controller design phase. Accurate qualitative modeling in the pre/post-yield regions are the main factors which determine the resulting controller performance.

Dynamic modeling and vibration analysis of rotating beams with active constrained layer damping treatment in temperature field

A new rigid-flexible coupled dynamic model considering temperature variation is developed for rotating beams with active constrained layer damping (ACLD) treatment in closed-loop and open-loop cases. By solving the corresponding linearized vibration equations of the smart system, the thermal vibration characteristics of the system in the two cases are analyzed. Influences of parameters, such as the angular velocity, the temperature, the gains of PD control, on the modal frequencies and damping ratios of the smart beam are discussed. Simulation results show that the variation of temperature can strongly affect the modal frequencies and damping performance of the ACLD beam, and there are critical temperatures that can change the damping performance of the ACLD beam in both open-loop and closed-loop cases. Research in this paper will be helpful for the dynamics of high speed rotating blades operating under thermal environment.

Dynamic modeling and analysis of rotating beams with partially covered enhanced active constrained layer damping treatment

A new dynamic model for vibration analyses of rotating flexible beams with partially covered enhanced active constrained layer damping (EACLD) treatment is developed. To improve the previous EACLD beam modeling method that only considers the edge element stiffness, the edge element of the EACLD patch is modeled as an equivalent spring with attached point mass so that the mass effect of the two added edge elements are included. The discrete rigid-flexible coupled dynamic equations of the hub-beam systems with EACLD treatment in the open-loop and closed-loop cases are derived by using the assumed mode method and Lagrange's equations. The effect of the angular velocity, edge element stiffness, edge element mass, and coverage ratio of the EACLD on the vibration characteristics of the system are investigated. Simulation results show that the edge element stiffness will increase the natural frequencies of the system and make the system become stiffer, while the edge element mass will decrease the natural frequencies of the system. Results from the traditional ACLD beam model, the EACLD beam model without edge element mass and the present EACLD beam model with edge element mass are also compared with each other. It is indicated that the mass effect of the added edge elements should be considered in practical applications and it could even play a positive role in stiffness or damping regulation of systems in conjunction with the vibration controller design.

Subspace-Aided Closed-Loop System Identification With Application to DC Motor System

A novel closed-loop numerical algorithm for subspace state space system identification (CN4SID) is proposed in this paper. Different from standard schemes, CN4SID algorithm can extend the standard LQ decomposition to the closed-loop cases by incorporating the controller information. Moreover, the proposed method can deliver unbiased pole estimation in the closed-loop framework. To this end, CN4SID algorithm shows superior pole estimation performance compared with a class of subspace identification method via principal component analysis algorithms. The effectiveness of the proposed CN4SID algorithm is finally verified through a practical dc motor system.

IMU-Assisted 2D SLAM Method for Low-Texture and Dynamic Environments

Generally, the key issues of 2D LiDAR-based simultaneous localization and mapping (SLAM) for indoor application include data association (DA) and closed-loop detection. Particularly, a low-texture environment, which refers to no obvious changes between two consecutive scanning outputs, with moving objects existing in the environment will bring great challenges on DA and the closed-loop detection, and the accuracy and consistency of SLAM may be badly affected. There is not much literature that addresses this issue. In this paper, a mapping strategy is firstly exploited to improve the performance of the 2D SLAM in dynamic environments. Secondly, a fusion method which combines the IMU sensor with a 2D LiDAR, based on framework of extended Kalman Filter (EKF), is proposed to enhance the performance under low-texture environments. In the front-end of the proposed SLAM method, initial motion estimation is obtained from the output of EKF, and it can be taken as the initial pose for the scan matching problem. Then the scan matching problem can be optimized by the Levenberg–Marquardt (LM) algorithm. For the back-end optimization, a sparse pose adjustment (SPA) method is employed. To improve the accuracy, the grid map is updated with the bicubic interpolation method for derivative computing. With the improvements both in the DA process and the back-end optimization stage, the accuracy and consistency of SLAM results in low-texture environments is enhanced. Qualitative and quantitative experiments with open-loop and closed-loop cases have been conducted and the results are analyzed, confirming that the proposed method is effective in low-texture and dynamic indoor environments.

Index-3 divide-and-conquer algorithm for efficient multibody system dynamics simulations: theory and parallel implementation

There has been a growing attention to efficient simulations of multibody systems, which is apparently seen in many areas of computer-aided engineering and design both in academia and in industry. The need for efficient or real-time simulations requires high-fidelity techniques and formulations that should significantly minimize computational time. Parallel computing is one of the approaches to achieve this objective. This paper presents a novel index-3 divide-and-conquer algorithm for efficient multibody dynamics simulations that elegantly handles multibody systems in generalized topologies through the application of the augmented Lagrangian method. The proposed algorithm exploits a redundant set of absolute coordinates. The trapezoidal integration rule is embedded into the formulation and a set of nonlinear equations need to be solved every time instant. Consequently, the Newton–Raphson iterative scheme is applied to find the system coordinates and joint constraint loads in an efficient and highly parallelizable manner. Two divide-and-conquer-based mass-orthogonal projections are performed then to circumvent the effect of constraint violation errors at the velocity and acceleration level. Sample open- and closed-loop multibody system test cases are investigated in the paper to confirm the validity of the approach. Challenging simulations of multibody systems featuring long kinematic chains are also performed in the work to demonstrate the robustness of the algorithm. The details of OpenMP-based parallel implementation on an eight-core shared memory computer are presented in the text and the parallel performance results are extensively discussed. Significant speedups are obtained for the simulations of small- to large-scale multibody open-loop systems. The mentioned features make the proposed algorithm a good general purpose approach for high-fidelity, efficient or real-time multibody dynamics simulations.

A parallel Hamiltonian formulation for forward dynamics of closed-loop multibody systems

This paper presents a novel recursive divide-and-conquer formulation for the simulation of complex constrained multibody system dynamics based on Hamilton’s canonical equations (HDCA). The systems under consideration are subjected to holonomic, independent constraints and may include serial chains, tree chains, or closed-loop topologies. Although Hamilton’s canonical equations exhibit many advantageous features compared to their acceleration based counterparts, it appears that there is a lack of dedicated parallel algorithms for multi-rigid-body system dynamics based on the Hamiltonian formulation. The developed HDCA formulation leads to a two-stage procedure. In the first phase, the approach utilizes the divide and conquer scheme, i.e., a hierarchic assembly–disassembly process to traverse the multibody system topology in a binary tree manner. The purpose of this step is to evaluate the joint velocities and constraint force impulses. The process exhibits linear O(n) (n – number of bodies) and logarithmic O(log_{2}{n}) numerical cost, in serial and parallel implementations, respectively. The time derivatives of the total momenta are directly evaluated in the second parallelizable step of the algorithm. Sample closed-loop test cases indicate very small constraint violation errors at the position and velocity level as well as marginal energy drift without any additional form of constraint stabilization techniques involved in the solution process. The results are comparatively set against more standard acceleration based Featherstone’s DCA approach to indicate the performance of the HDCA algorithm.

Modelling of Baker’s Yeast Production

In the present work, parametric models for the control of bioreactor temperature have been applied. Various order discrete time model parameters were evaluated theoretically and experimentally. Two types of input signals were used as external force to determine Auto Regressive Moving Average with Exogenous (ARMAX) model parameters with Recursive Least Square (RLS) parameter estimation algorithm. The third order ARMAX model is utilized, and compared with the second order one. Ternary and square disturbances are given to the cooling water flow rate which can be chosen as manipulating variable in closed loop cases. System response is monitored continuously and the model parameters are calculated. The models with experimentally identified parameters are compared with ones that their parameters are identified theoretically.

Dynamic Oligopoly with Sticky Prices: Off-Steady-state Analysis

In this paper we carry out a comprehensive analysis of the model of oligopoly with sticky prices with full analysis of prices’ behaviour outside their steady-state level in the infinite horizon case. An exhaustive proof of optimality is presented in both open loop and closed loop cases.