Control Design Tools Research Articles

Investigation of Hybrid Laminar Flow Control Capabilities from the Flight Envelope Perspective

The present work conducts a multifidelity aerodynamic design of a medium-range commercial aircraft wing featuring hybrid laminar flow control (HLFC) technology. The design was performed to investigate the capabilities of the HLFC, considering the entire design flight envelope, low-speed performance requirements, and various potential mission scenarios. A combination of medium-fidelity aerodynamic design tools for laminar flow control using MSES-COCO-LILO, CFD RANS for high-lift cases, the quasi-three-dimensional for database generations, and SUAVE for mission analysis were used to design and assess aircraft’s performance with the HLFC wing. Studies of the design objective demonstrated a conflict between friction and compressibility drag that strongly affects the design objective function and the wing performance at various off-design conditions. A strong dependence of HLFC on flight conditions was observed to indicate technology performance limitations and a tradeoff between airplane emissions, range, and costs. Finally, a comparison of medium- and low-fidelity performance results showed deviations in the design fuel burn of 4%, a minimum possible harmonic range difference of 3%, and direct operating costs of 2%. The outcome suggests the need for better compressibility and parasite drag models for early design stages to accurately model the HLFC technology without introducing complicated methods at the first sizing steps.

Trajectory tracking in linear complementarity systems with and without state jumps: A passivity approach

This work is largely concerned with trajectory tracking in linear complementarity systems (LCS). The main analytical tool for stability analysis and control design is passivity and the associated linear matrix inequalities (LMIs) for feedback passification. Cases with and without state-jumps, with and without parametric uncertainties, are analyzed. Theoretical findings are illustrated with examples from circuits with set-valued, nonsmooth electronic components, networks with unilateral interactions, and mechanical system with unilateral spring.

Advanced plant-wide control design tools applied to the fluid catalytic cracker-fractionator benchmark

In this work two advanced multivariable control structure design tools are applied on the recently appeared fluid catalytic cracking (FCC)-fractionator benchmark process. Indeed, the partial least squares-based sum of squared deviations (PLS-based SSD) approach and the control allocation (CA) with measurement combination procedure are proposed here to develop new control policies. The minimally invasive feature of PLS-based SSD, allows to obtain an open-loop steady-state model of the process by using closed-loop normal data and to perform a performance/feasibility assessment of the already installed control structure. In this regard, the procedure identified some global integrity problems of the industrial-based control structure proposed in previous works and, therefore, new plant-wide control structures (with different sizing and input/output pairings) were proposed, where the SSD indexes have improved in the range of 50% to 90% and the matrix conditioning guaranteed. The proposed control structures were dynamically tested under typical set point and disturbance variations.

Quality by Design (QBD) Tool for Quality Control in Pharmaceutical Industry

Multiple approaches are operating in the modern world to analyze pharmaceutical dosage forms, but Quality by design is one of the most prominent approaches that can be used. Quality must be built into the product or method during pharmaceutical or analytical development, per the Quality by Design (QbD) concept. Commonly, input factors affect the Quality of products and techniques. The system is highly dynamic and adaptable to the changing environment, with better efficiency and an enhanced level of manufacturing within it. The quality-by-design strategy is also more consistent in upholding the product's designs and quality characteristics. The paper aims to better organize information by understanding and studying the elements of Quality by design. The pharmaceutical sector places a strong emphasis on quality prospects while also improving productivity and product designs. The paper seeks to describe the design development and study its multiple factors.

Novel extreme seeking control framework with ordered excitation and nonlinear function based PSO: Method and application

The performance of a photovoltaic power system is heavily influenced by mismatches, for example, partial shading effects. In literature, it lacks of a scrupulous study on intelligent control designs whose transient responses and steady state responses are not directly given when achieving the goal of global maximum power point tracking (GMPPT). A novel and systematic control design approach is proposed mathematically to derive explicit discrete controllers for the overall GMPPT performance. Specifically, the new algorithms of nonlinear function (NF) based particle swarm optimization (PSO) and ordered excitation (OE) are incorporated into the extreme seeking controller for the enhancement of both transient and steady state responses when fulfilling the extreme seeking task. The explicit control functions are easy to implement in the applications. Both the simulation based analysis and experimental study are carried out in a statistical manner in order to evaluate the proposed controller through a number of control performance indicators. A comparison analysis of the statistical data reveals that both simulation and experimental results agree with the theory where both algorithms of NF-PSO and OE play a role to improve transient responses and steady state responses for the global extreme seeking. Meanwhile, the proposed intelligent controller outperforms the classical benchmark in tracking the GMPP. The insightful and instructive control design tool is promising in both academia and engineering.

A Software Realization of Disturbance Rejection Optimal FOPID Controller Design Methodology by Using Soft Computing Techniques

This study presents a soft computing tool for the computer-aided design of disturbance rejection FOPID controllers based on the maximization of Reference to Disturbance Ratio (RDR) index. The study illustrates the utilization of software routines to implement a soft computing scheme in order to solve a closed loop disturbance rejection FOPID control system design problem for a target gain margin specification. Authors demonstrate that the complex design efforts, which involve a high level of mathematical knowledge, can be easily performed by using basic software routines when soft computing techniques are employed effectively in the computation processes. Illustrative design examples are shown to show effectiveness of the proposed design method.

Performance and control of a CO2 dual source solar assisted heat pump with a photovoltaic-thermal evaporator

• Tests have been conducted with a PV-T evaporator and with a finned coil evaporator. • Experimental data show that the PV-T evaporator can increase the COP up to 30% • The evaporators operate at the maximum possible pressure with no superheating. • The measurements allow to validate a model of the heat pump. • The iso-COP maps can be used as a control strategy or design tool. This work presents a double source transcritical CO 2 heat pump that features hybrid photovoltaic-thermal collectors as evaporator. The heat pump can work in two different modes using alternatively air or solar radiation as thermal sources. In air-source mode, a conventional finned coil heat exchanger is used as the evaporator, whereas in solar-source mode, an innovative solar hybrid collector (photovoltaic-thermal) is used as the direct expansion evaporator. The photovoltaic-thermal collector has a double effect: it allows to evaporate the CO 2 that flows in the tubes and to cool down the photovoltaic cells improving the photovoltaic conversion efficiency. An experimental comparison between the two operative modes is presented in terms of evaporation temperature and performance coefficient, which can increase up to 30% in the Solar-source mode as compared to the Air-source mode. Moreover, due to the cooling of the photovoltaic cells, the photovoltaic electric production can be 10 % higher compared to that estimated if the cells were not cooled. The present design of the refrigerant loop allows to avoid the presence of superheated vapor at the outlet of the evaporators and thus it regulates the evaporation pressure always at the highest possible value using efficiently all the available evaporator area to vaporize the CO 2 mass flow rate. The present measurements have been used to develop and validate a mathematical model of the heat pump, able to predict the performance when varying the ambient conditions or the photovoltaic-thermal evaporator area. The iso-COP maps obtained from the model can be used for the switching strategy between the air-source and the solar-source but also to determine the minimum evaporator area in the design of the system.

Modeling and Intelligent Controller Design for Reactor Regulating System of Advanced CANDU Reactor (ACR-700) in LabVIEW

In this research work, an Advanced CANDU Reactor of 700 MWe rating (ACR-700) is attempted for Reactor Regulating System (RRS) modeling and intelligent controller design. ACR-700 is a state-of-the-art advanced generation-III reactor. The reactor regulating system is modeled with special emphasis on internal and external reactivity devices. ACR-700 is designed with Liquid Zone Control (LZC) Model, Adjuster Banks Model, Absorber Banks Model and Shutdown Banks Model. The RRS model is a highly sophisticated model developed based on the principle of spatial nuclear reactor dynamics. The RRS model is a multivariable model. The spatial reactor dynamics is modeled based on five internal feedbacks and three feedbacks. The original controller design of RRS is comprised of a PID control algorithm. The control design is reattempted with an advanced intelligent algorithm in which the ANFIS controller is used as a modern control design tool. The new ANFIS controller is basically a multivariable controller. All the modeling of RRS is implemented in Visual Basic (VB) Software while the controller is configured in LabVIEW. A special toolkit is designed for the interfacing of Visual Basic and LabVIEW known as VBLAB. The optimization of intelligent controller parameters is carried out by Genetic Algorithm (GA). The GA-optimized intelligent controller is configured with the VB RRS model. All the variable trends are visualized in the VB environment. The proposed closed-loop ACR-700 RRS control system is tested for small perturbation Analysis and power ramp-down transient and found with excellent behavior well within the design limits. The performance of the suggested ACR-700 RRS controller is compared with the existing conventional controller. The performance of the suggested control scheme is marked with reduced oscillations and faster as compared to the existing control scheme.

Quadrotor physical parameters online estimation

Online estimation of unmanned aerial vehicles' physical parameters is an essential tool for aerodynamic and control design. This paper numerically evaluates two methods for physical parameter estimation for a quadrotor. The estimation methods are based on recently introduced techniques that relax the persistency of excitation constraint in the least-squares estimation methods.

Development and Evaluation of Control System in Mechatronics – A Systematic Survey

The advancement of mechatronic enabling technologies and the mechatronic design approach has resulted in sophisticated mechatronic systems. Automated mechatronic systems are becoming more complicated and more intelligent. Mechanical systems that enable the next generation of manufacturing systems will have whole new features and capabilities as a result of these modifications. Even basic monitoring has grown into self-optimizing performance in these gadgets. With the addition of bio-mechatronics and micro-mechatronics, the application fields of mechatronics have expanded. Bio or microcontroller-based applications are the focus of this publication, which aids researchers in building and testing control systems. Design considerations for mechatronic systems are addressed in this work. In order to implement more complicated control algorithms in an industrial setting, new controller design tools are required. The early evaluation of designs and the support of critical design choices may be made possible via the use of modelling and simulation technologies.

Reinforcement Learning Impedance Control of a Robotic Prosthesis to Coordinate With Human Intact Knee Motion

This study aims to demonstrate reinforcement learning tracking control for automatically configuring the impedance parameters of a robotic knee prosthesis. While our previous studies involving human subjects have focused on tuning the impedance control parameters to meet a fixed, subjectively prescribed target motion profile to enable continuous walking with human-in-the-loop, in this paper we develop a new tracking control solution for a robotic knee to mimic the motion of the intact knee. As such, we replaced the prescribed target knee motion by an automatically generated profile based on the intact knee. As the profile of the intact knee varies over time due to human adaptation, we are presented with a challenging tracking control problem in the context of classical control theory. By formulating the “echo control” of the robotic knee as a reinforcement learning problem, we provide a promising new tool for real-time tracking control design without explicitly representing the underlying dynamics using a mathematical model, which can be difficult to obtain for a human-robot system. Additionally, our results may inspire future studies and new robotic prosthesis impedance control designs that can potentially coordinate between the intact and the robotic limbs toward daily use of the robotic device.

Dissipative Dynamical Systems With Set-Valued Feedback Loops: Well-Posed Set-Valued Lur’e Dynamical Systems

Passivity and dissipativity, in Jan Willems’s sense, are known to be powerful tools for stability analysis and feedback control design. For instance, passive systems in negative feedback interconnection with slope-restricted, static, single-valued, smooth nonlinearities, known as Lur’e systems, have been thoroughly studied in automatic control, yielding the so-called absolute stability problem (with the famous Popov and circle criteria). On the other hand, large classes of nonsmooth systems (complementarity dynamical systems, relay systems, projected dynamical systems, evolution and differential variational inequalities, Moreau’s sweeping processes, and maximal monotone differential inclusions), with applications in circuits, mechanics, and economics, are interpreted as set-valued Lur’e systems, in which the feedback nonlinearity is a multivalued mapping. Therefore, the closed-loop system is a differential inclusion of a certain type, the well posedness of which must be analyzed as a prerequisite for stability and control. This introductory article focuses on the well posedness of such set-valued feedback systems. It is shown how the existence and uniqueness of solutions to these specific differential inclusions benefit a lot from the passivity of the system and the maximal monotonicity (which is a form of incremental passivity) of the feedback set-valued mapping. Available results are reviewed, many illustrative examples are given, and some open issues are highlighted.

ATP synthase FOF1 structure, function, and structure-based drug design.

ATP synthases are unique rotatory molecular machines that supply biochemical reactions with adenosine triphosphate (ATP)-the universal "currency", which cells use for synthesis of vital molecules and sustaining life. ATP synthases of F-type (FOF1) are found embedded in bacterial cellular membrane, in thylakoid membranes of chloroplasts, and in mitochondrial inner membranes in eukaryotes. The main functions of ATP synthases are control of the ATP synthesis and transmembrane potential. Although the key subunits of the enzyme remain highly conserved, subunit composition and structural organization of ATP synthases and their assemblies are significantly different. In addition, there are hypotheses that the enzyme might be involved in the formation of the mitochondrial permeability transition pore and play a role in regulation of the cell death processes. Dysfunctions of this enzyme lead to numerous severe disorders with high fatality levels. In our review, we focus on FOF1-structure-based approach towards development of new therapies by using FOF1 structural features inherited by the representatives of this enzyme family from different taxonomy groups. We analyzed and systematized the most relevant information about the structural organization of FOF1 to discuss how this approach might help in the development of new therapies targeting ATP synthases and design tools for cellular bioenergetics control.

A Data-Driven Identification Procedure for HVAC Processes with Laboratory and Real-World Validation

Linear system identification is a well-known methodology for building mathematical models of dynamic systems from observed input–output data. It also represents an essential tool for model-based control design, adaptive control and other advanced control techniques. Use of linear identification is, however, often limited to academic environment and to research facilities equipped with scientific computing platforms and highly qualified staff. Common industrial or building control system technology rarely uses these advanced design techniques. The main obstacle is typically lack of experience with their practical implementation. In this article, a procedure is proposed, implemented, and tested, that brings the benefits of linear identification into broader control system practice. The open-source DCU control system platform with its advanced control framework is used for implementation of the proposed linear identification procedure. The procedure is experimentally tested in the laboratory setting using a unique model of HVAC system as well as in real-world environment in an experimental two storey family house. Testing this novel feature of the control system has proved satisfactory results, while some of them are presented in graphical and numerical form.

Derivative-Based Koopman Operators for Real-Time Control of Robotic Systems

This article presents a generalizable methodology for data-driven identification of nonlinear dynamics that bounds the model error in terms of the prediction horizon and the magnitude of the derivatives of the system states. Using higher order derivatives of general nonlinear dynamics that need not be known, we construct a Koopman-operator-based linear representation and utilize Taylor series accuracy analysis to derive an error bound. The resulting error formula is used to choose the order of derivatives in the basis functions and obtain a data-driven Koopman model using a closed-form expression that can be computed in real time. Using the inverted pendulum system, we illustrate the robustness of the error bounds given noisy measurements of unknown dynamics, where the derivatives are estimated numerically. When combined with control, the Koopman representation of the nonlinear system has marginally better performance than competing nonlinear modeling methods, such as SINDy and NARX. In addition, as a linear model, the Koopman approach lends itself readily to efficient control design tools, such as linear–quadratic regulator, whereas the other modeling approaches require nonlinear control methods. The efficacy of the approach is further demonstrated with simulation and experimental results on the control of a tail-actuated robotic fish. Experimental results show that the proposed data-driven control approach outperforms a tuned proportional–integral–derivative controller and that updating the data-driven model online significantly improves performance in the presence of unmodeled fluid disturbance. This article is complemented with a video available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://youtu.be/9_wx0tdDta0</uri> .

On the efficacy and accuracy of freezing technique for the response analysis of time-varying vehicle-bridge interaction systems

The basic problem of vehicle-bridge interaction (VBI) is a linear time-varying system for which no exact solution is available and even numerical solutions can be complicated. In this paper, the efficacy and accuracy of a freezing technique (FT), in which the time parameter is frozen, applied to obtain the forced response of the VBI system are assessed. To improve the accuracy, a time-step approach, in which FT is employed in each time subinterval, is proposed. The FT is relatively simple to implement and results are validated with and compared to those obtained by a highly accurate Runge-Kutta method (treated as “exact” solution) for different vehicle models, vehicle and bridge parameters, and time steps. It is found that numerical results obtained by the FT are accurate, even for high vehicle speeds. Moreover, the FT outperforms the Newmark-β method. An analytical local error bound for the FT is derived, which shows the error dependence on the vehicle-bridge coupling dynamics, in particular, the tire stiffness and the vehicle speed. An important implication of this study is that, since the FT can be applied to analyze the time-varying VBI system, the method essentially transforms the coupled system into a time sequence of linear time-invariant (LTI) systems and allows tools for dynamic analysis and controller design of LTI systems to be applicable to the VBI problem.

Guest Editorial Special Issue on the 2018 Workshop on the Algorithmic Foundations of Robotics (WAFR)

This Workshop on the Algorithmic Foundations of Robotics (WAFR) Special Issue of the IEEE Transactions on Automation Science and Engineering (T-ASE) brings together eight extended articles from the thirteenth WAFR. While these eight articles span several application domains, they demonstrate advances in automation through algorithmic development and analysis. Nomination to this Special Issue was done in coordination with the entire program committee and guest edited by the four WAFR Co-Chairs. The articles in this Special Issue highlight cutting-edge research in general tools for motion planning, learning, control, manipulation, sensor-based planning, and robotic design.

A derivative-free nonlinear Kalman filtering approach using flat inputs

ABSTRACT Differential flatness theory has been widely used for both tracking control and state estimation of nonlinear systems. Recently, the concept of flat inputs has been proved to be a valuable tool for control design if the system is non-differentially flat. However, flat inputs have not been used yet to solve state estimation problems for these systems. By constructing flat inputs, we introduced a novel state estimation-based control strategy for both observable non-differentially flat nonlinear systems and differentially flat nonlinear systems whose flat output vector is not a measurable variable, as long as the internal dynamics of the system are stable. The efficiency of the proposed approach is illustrated through two numerical examples. Our findings indicated that we increased the class of systems to which the derivative-free nonlinear Kalman filtering based on differential flatness theory can be applied.

Design and Build a Motorcycle Security Controller Using the IoT-Based GPS Tracking Method

Motor vehicle theft cases still often occur around us, this happens because there is still a lack of security systems in motorized vehicles that only use ignition keys and key covers, where weaknesses in standard security systems like this have been understood by motor vehicle theft perpetrators. to do the action. To overcome this, a motorized vehicle security system was created using the IOT-based GPS tracking method to prevent and make it easier to retrieve a stolen motorized vehicle. So far, most motorcycle safety devices are still physically secure, for example a solution commonly used by motorized vehicle owners by adding safety locks to discs, chaining and so on, but owners often forget to install locks, or vehicle alarms. The result of this research is the production of a controller design tool, motorcycle safety and GPS tracking to provide information on the last location of motorized vehicles and can control remotely based on iot. which has been experienced by motorized vehicle users.

Analytical study of time-delayed feedback control of rectangular prisms undergoing subcritical galloping

In this study, time-delayed feedback control is investigated for an elastically mounted rectangular prism undergoing subcritical galloping in the transverse direction, when subjected to wind excitation. The mathematical model of the galloping system under consideration is established by using the quasi-steady aerodynamic theory. The control performance in terms of the galloping onset speed of the time-delayed displacement, velocity and acceleration feedback is investigated via linear stability analysis, respectively. Subsequently, the method of multiple scales is implemented for nonlinear analysis in order to derive the analytical expression of the vibration amplitude of the galloping system and determine the criticality curve that is the boundary of the subcritical and supercritical bifurcation regions. The results show that the hybrid objective of increasing the galloping onset speed, changing the Hopf bifurcation behavior from subcritical to supercritical and reducing the amplitude of limit-cycle oscillations can be achieved by means of delayed acceleration feedback. This study provides an analytical tool and procedure for time-delayed feedback control design of such a kind of flow–structure interaction system.