Simple System Model Research Articles

Learning a Low-Dimensional Representation of a Safe Region for Safe Reinforcement Learning on Dynamical Systems.

For the safe application of reinforcement learning algorithms to high-dimensional nonlinear dynamical systems, a simplified system model is used to formulate a safe reinforcement learning (SRL) framework. Based on the simplified system model, a low-dimensional representation of the safe region is identified and used to provide safety estimates for learning algorithms. However, finding a satisfying simplified system model for complex dynamical systems usually requires a considerable amount of effort. To overcome this limitation, we propose a general data-driven approach that is able to efficiently learn a low-dimensional representation of the safe region. By employing an online adaptation method, the low-dimensional representation is updated using the feedback data to obtain more accurate safety estimates. The performance of the proposed approach for identifying the low-dimensional representation of the safe region is illustrated using the example of a quadcopter. The results demonstrate a more reliable and representative low-dimensional representation of the safe region compared with previous works, which extends the applicability of the SRL framework.

A Simplified Model of the HVDC Transmission System for Sub-Synchronous Oscillations

As the installed capacity of the power system is scaled up and the distance of transmission increases constantly, high-voltage direct current (HVDC) transmission technology has been widely applied across the power system. The HVDC system can lead to sub-synchronous oscillations (SSO) in the turbine and new energy generation systems. When the SSO caused by HVDC are studied through small signal analysis, it is usually necessary to establish the detailed state space model and electromagnetic transient model, which shows various disadvantages such as the high complexity of the model, the high order of the state space matrix, the complex calculation of eigenvalues, and the slow pace of simulation. In the present study, a simplified model intended for the HVDC transmission system is proposed, which can be used to simplify the calculation model and accelerate the simulation by omitting the high-frequency component and simultaneously keeping the sub-synchronous frequency component unchanged. The time domain simulation method is used to compare the dynamic response of the proposed simplified simulation model with that of the original detailed model, and the accuracy of the proposed model is demonstrated. The proposed simplified simulation model is applied to explore the SSO of wind-thermal power bundling in the HVDC transmission system. Additionally, the simulation results of SSO are compared by using the simplified model and the detailed model; the results of which demonstrate the effectiveness and rapidity of the simplified simulation model. The simplified model proposed can greatly improve the efficiency of SSO risk assessment. By selecting reasonable types and parameters of new energy units, SSO of the system can be avoided under risky operation mode, and the power grid operation mode can be monitored and adjusted to ensure the safe operation of the system. Finally, it can promote the sustainable development of the power system.

Large-signal modeling and stable region estimation of DC microgrid with virtual DC machine control

In order to enhance the anti-disturbance capability of a DC microgrid, the virtual DC machine control (VDMC) is usually utilized. However, the existing literature on VDMC mainly focuses on the small-signal modeling based on linearization technique, which cannot be used to describe the system dynamics under large disturbance. Furthermore, the power electronics-based loads have the features of constant power characteristic, which increases the nonlinear of the DC microgrid. In such case, it becomes difficult to obtain the system stability region accurately via the small-signal methods. To settle such problem, the simplified large-signal model of the DC microgrid system with VDMC is established via the TS fuzzy modelling method. Thereupon, an approach to estimate the asymptotic stability region of the system is put forward. The region of asymptotic stability can be used to estimate the maximum undertaking changes of both the DC bus voltage and load power. Finally, the accuracy of the proposed model and the effectiveness of the presented methods are verified by simulations and experiments.

Moment-Based Model Predictive Control of Autonomous Systems

Great efforts have been devoted to the intelligent control of autonomous systems. Yet, most of existing methods fail to effectively handle the uncertainty of their environment and models. Uncertain locations of dynamic obstacles pose a major challenge for their optimal control and safety, while their linearization or simplified system models reduce their actual performance. To address them, this paper presents a new model predictive control framework with finite samples and a Gaussian model, resulting in a chance-constrained program. Its nominal model is combined with a Gaussian process. Its residual model uncertainty is learned. The resulting method addresses an efficiently solvable approximate formulation of a stochastic optimal control problem by using approximations for efficient computation. There is no perfect distribution knowledge of a dynamic obstacle's location uncertainty. Only finite samples from sensors or past data are available for moment estimation. We use the uncertainty propagation of a system's state and obstacles' locations to derive a general collision avoidance condition under tight concentration bounds on the error of the estimated moments. Thus, this condition is suitable for different obstacles, e.g., bounding box and ellipsoid obstacles. We provide proved guarantees on the satisfaction of the chance-constraints corresponding to the nominal yet unknown moments. Simulation examples of a vehicle's control are used to show that the proposed method can well realize autonomous control and obstacle avoidance of a vehicle, when it operates in an uncertain environment with moving obstacles. It outperforms the existing moment methods in both performance and computational time.

A comparison of explicit Runge-Kutta methods

Recent higher-order explicit Runge–Kutta methods are compared with the classic fourth-order (RK4) method in long-term integration of both energy-conserving and lossy systems. By comparing quantity of function evaluations against accuracy for systems with and without known solutions, optimal methods are proposed. For a conservative system, we consider positional accuracy for Newtonian systems of two or three bodies and total angular momentum for a simplified Solar System model, over moderate astronomical timescales (tens of millions of years). For a nonconservative system, we investigate a relativistic two-body problem with gravitational wave emission. We find that methods of tenth and twelfth order consistently outperform lower-order methods for the systems considered here. doi: 10.1017/S1446181122000141

Research on Active Disturbance Rejection Controller for Electromechanical Servo System with Large Inertia Loads

In this paper, an Active Disturbance Rejection Controller (ADRC) based on an improved Particle Swarm Optimization (PSO) algorithm is proposed. The ADRC is conducive to addressing the situation that the electromechanical servo system is loaded with a large inertia barrel and is significantly affected by disturbances when working at high speed and precision. It can not only improve the anti-disturbance performance of the system but also ensure the dynamic performance of the system. Firstly, a simplified mathematical model of the electromechanical servo system is established and the non-linear factors of the system are analyzed. Secondly, the ADRC is designed and the parameters are optimized by utilizing the improved PSO algorithm. Finally, the control effect of the proposed method is simulated and analyzed. The simulation consequences demonstrate that compared with the traditional PID control, the proposed method can significantly increase the anti-disturbance capability of the servo system, and guarantee the accuracy index of the system.

Analysis of ideal models of real nonlocal acoustic and elastic metamaterials

Nonlocal coupling in acoustic and elastic systems has received growing attention for its potential to expand the capabilities of active metamaterials. Previously, we have shown experimentally how nonlocality imposed through action at a distance, where signals from disturbances at one location are used to drive actuators at separate locations, gives rise to unique scattering characteristics, namely highly nonreciprocal transmission. We showed how the mathematical models for these experimental systems were excellent predictors for real system behavior, and as such, represented powerful experimental design tools. However, these models were elaborate, incorporating the characteristics of real sensors and actuators, electronic controllers, and material properties and geometries, consequently obscuring the underlying nonlocal physics responsible for their unique behavior. Here, we present simplified models of these real systems that feature closed form expressions for system scattering characteristics, allowing for the identification of relevant dimensionless quantities and revealing how the interactions of those quantities affect both system performance and stability. We compare and contrast ideal models for both acoustic and elastodynamic nonlocal systems, highlighting how each ideal model is qualitatively representative of its real counterpart, thus providing a pathway to a deeper understanding and further exploration of nonlocality in wave-bearing systems.

Augmented random search based inter-area oscillation damping using high voltage DC transmission

The high voltage DC (HVDC) Transmissions are under rapid development all over the world. The HVDC transmission not only provides a low-loss electric energy transfer path, but also acts as an alternative tool for damping inter-area oscillations in modern electric power systems. In this paper, we proposed a novel reinforcement learning based HVDC oscillation damping controller using the augmented random search (ARS) algorithm. By leveraging the wide-area information such as voltages, phase angle, machine speeds, the ARS was able to determine the modulation power of HVDC to effectively damp inter-area oscillations. The proposed research overcomes the challenges of setting optimal controller parameters of the HVDC under various system transient events. The proposed ARS-based HVDC power oscillation damping control approach was tested on a simplified Western American large-scale power system model called minniWECC. Extensive studies have demonstrated the superiority of the proposed ARS-based HVDC control approach over conventional power oscillation damping methods.

Power Consumption Characteristics Research on Mobile System of Electrically Driven Large-Load-Ratio Six-Legged Robot

The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration. However, due to the particularity of its parallel structure, the effective utilization rate of energy is not high, which has become an important obstacle to its practical application. To research the power consumption characteristics of robot mobile system is beneficial to speed up it toward practicability. Based on the configuration and walking modes of robot, the mathematical model of the power consumption of mobile system is set up. In view of the tripod gait is often selected for the six-legged robots, the simplified power consumption model of mobile system under the tripod gait is established by means of reducing the dimension of the robot's statically indeterminate problem and constructing the equal force distribution. Then, the power consumption of robot mobile system is solved under different working conditions. The variable tendencies of the power consumption of robot mobile system are respectively obtained with changes in the rotational angles of hip joint and knee joint, body height, and span. The articulated rotational zones and the ranges of body height and span are determined under the lowest power consumption. According to the walking experiments of prototype, the variable tendencies of the average power consumption of robot mobile system are respectively acquired with changes in duty ratio, body height, and span. Then, the feasibility and correctness of theory analysis are verified in the power consumption of robot mobile system. The proposed analysis method in this paper can provide a reference on the lower power research of the large-load-ratio multi-legged robots.

Robust two-degrees of freedom linear quadratic gaussian position control for the front axle actuator of a steer-by-wire system

The Steer-by-Wire (SbW) system is a key technology for highly automated driving. For automated lateral vehicle guidance, the precise position control of the SbW Front Axle Actuator is an essential prerequisite. This contribution presents the modeling, control design, nominal performance, and stability analysis as well as the robustness analysis of the position control for the SbW Front Axle Actuator. Based on a nonlinear model of the plant a simplified linear system model is derived. This model yields the basis for the design of a Two-Degrees of Freedom Linear Quadratic Gaussian Control (2DOF LQG control), which allows an independent design of the command and the disturbance response. Besides an evaluation of the nominal control behavior, μ-analysis is applied to assess the robustness of performance and stability. Finally, real vehicle tests for different driving maneuvers are presented to verify simulation results.

Evaluating the intensity, duration and frequency of flexible energy resources needed in a zero-emission, hydropower reliant power system

Abstract Rapid increases in global temperature are motivating governments to restructure the energy sector towards emissions-free electricity generation. One of the key factors affecting the viability of emissions-free power systems is the joint variability of renewable resources and drivers of energy demand across spatiotemporal scales. This study evaluates the impact of multi-scale hydroclimatic variability on the reliability of a zero-emissions power system in a case study of New York State (NYS), which recently passed the Climate Leadership and Community Protection Act (CLCPA) requiring zero-emissions electricity generation by 2040. We first analyze covariation between renewable energy generation and energy demand, including large-scale hydropower generation on the Great Lakes, and develop a stochastic generator to simulate an ensemble of plausible realizations of this joint variability. Using a simplified energy balance model of the NYS power system, we then quantify resource gaps across spatiotemporal scales that emerge under load and generation scenarios projected under the CLCPA. We focus on the intensity, duration, and frequency of these gaps, which will have to be filled with carbon-free, dispatchable resources not prescribed under the CLCPA. We show that the covariability between load and wind can lead to major short-term resource gaps, which is exacerbated by transmission constraints. We also show that long-duration hydropower droughts increase the likelihood of co-occurring renewable resource deficits and extended periods (weeks to months) of energy shortage. We conclude by discussing the implications of these results on the need for alternative, carbon-free, and dispatchable resources to support zero emission, hydropower-reliant electric grids.

Evaluation of the accuracy of established patient inspiratory effort estimation methods during mechanical support ventilation

There is a clinical need for monitoring inspiratory effort to prevent lung- and diaphragm injury in patients who receive supportive mechanical ventilation in an Intensive Care Unit. Different pressure-based techniques are available to estimate this inspiratory effort at the bedside, but the accuracy of their effort estimation is uncertain since they are all based on a simplified linear model of the respiratory system, which omits gas compressibility of air, and the viscoelasticity and nonlinearities of the respiratory system. The aim of this in-silico study was to provide an overview of the pressure-based estimation techniques and to evaluate their accuracy using a more sophisticated model of the respiratory system and ventilator.The influence of the following parameters on the accuracy of the pressure-based estimation techniques was evaluated using the in-silico model: 1) the patient's respiratory mechanics 2) PEEP and the inspiratory pressure of the ventilator 3) gas compressibility of air 4) viscoelasticity of the respiratory system 5) the strength of the inspiratory effort.The best-performing technique in terms of accuracy was the whole breath occlusion. The average error and maximum error were the lowest for all patient archetypes. We found that the error was related to the expansion of gas in the breathing set and lungs and respiratory compliance. However, concerns exist that other factors not included in the model, such as a changed muscle-force relation during an occlusion, might influence the true accuracy. The estimation techniques based on the esophageal pressure showed an error related to the viscoelastic element in the model which leads to a higher error than the occlusion. The error of the esophageal pressure-based techniques is therefore highly dependent on the pathology of the patient and the settings of the ventilator and might change over time while a patient recovers or becomes more ill.

Simulation and experimental investigations of ultrasonic-assisted drilling with Micro-PDC bit

Ultrasonic-assisted drilling (UAD) technology is a new drilling technology, which combines polycrystalline diamond compact (PDC) bits and performs better than conventional PDC drilling in improving the rock-breaking efficiency during deep hard formations. In this study, a series of simulations and laboratory tests were conducted to explore the dynamic rock-breaking mechanism of UAD with a PDC bit and the influence of different input parameters on the force and energy distribution. First, the UAD process was analyzed using a simplified drilling system model, and the relationship between the axial and tangential forces was investigated using a single PDC cutter cutting model. Then, a finite element analysis model that considers rock heterogeneity was used for the analysis. The drilling process, element damage situation, and broken form of the borehole bottom of conventional drilling (CD) and UAD were compared, and the impact of amplitude, frequency, and rotary speed on the weight on bit (WOB), torque, cutting force, and energy consumption were evaluated. Finally, laboratory experiments on PDC micro-drilling for different drilling conditions were conducted to verify the effectiveness of UAD. The results indicate that during rock-breaking using UAD, the PDC cutter periodically penetrated and broke away from the rock with ultra-high frequency, causing a large amount of damage to the rock. The frequency and amplitude significantly influenced the UAD: when the vibration frequency was between 25 and 35 kHz, the force state of the PDC cutter greatly improved compared with that of CD, and the effect of ultrasonic load reached the maximum at 33 kHz; when the amplitude was between 10 and 50 μm, WOB and torque decreased significantly and the effect of ultrasonic load improved with increase in amplitude, but the rotary speed had little effect on the torque and WOB of UAD. During the laboratory experiments, the drilling efficiency and rate of penetration (ROP) improved on using UAD. When the WOB was 100–200 N and the rotary speed was 300–400 rpm, the efficiency of ultrasonic rotary drilling to improve the ROP increased by 14.7–23.4%.

Data-Driven Adaptive Optimal Control Under Model Uncertainty: An Application to Cold Atmospheric Plasmas

Cold atmospheric plasmas (CAPs) are increasingly used for applications requiring the processing of heat- and pressure-sensitive (bio)materials. A key challenge in model-based control of CAPs arises from the high-computational requirements of theoretical plasma models as well as lack of mechanistic understanding of plasma-surface interactions. Thus, control strategies that rely on simple, physics-based models that can be adapted to mitigate plant-model mismatch will be particularly advantageous for CAP applications. This article presents an optimal control approach for controlling the nonlinear and cumulative effects of CAPs delivered to a target surface using a simple system model. Through parsimonious input parameterization, the solution to the optimal control problem (OCP) is given by an arc sequence that does not include any singular arcs. A data-driven adaptive algorithm based on modifier adaptation is proposed to deal with the structural plant-model mismatch by estimating the mismatch in the cost and constraints of the OCP. The adaptive approach is shown to converge to a Karush–Kuhn–Tucker (KKT) point of the OCP for the true system. Moreover, a control strategy based on feedback linearization and derivative estimation is proposed for online tracking of path constraints in the presence of disturbances and model uncertainty. The proposed approach is demonstrated by simulations and real-time control experiments on a kilohertz-excited atmospheric pressure plasma jet in helium, in which the plasma treatment time is minimized while delivering a desired amount of nonlinear thermal effects to the target surface.

Dynamic analysis of the subsea production system with lazy-wave risers attached to FPSO.

The lazy-wave riser is an input and output riser for a flexible development system, which is widely used in all the riser and pipeline systems. Because of the influence of various factors, its configuration description, control and motion which have a strong nonlinear character are complex during the running process of the lazy-wave riser. Reference to the specific structure and environmental parameters of a certain lazy-wave risers system with a 300 thousand tons FPSO, with the basis of the specific process of the flexible riser system at work, the lazy-wave risers were discretized into lumped mass models, combined with AQWA, the simplified dynamic model of the whole system at the depth of 2100m has been established by the large hydrodynamic analysis software OrcaFlex. The dynamic response characteristics of the lazy-wave risers have been given by using time domain coupling method. With and without the consideration of the 2nd wave drift load in the simulation process, the effects of the 2nd wave drift load on the results are obtained. The simulation results reveal the difficulty of simulation convergence caused by a large number of risers and flexible components. The 2nd order wave drift loads have a significant effect on the riser system, resulting in the increasement of the effective tension at each end of each riser. To counteract the magnitude of the FPSO response caused by such loads, the number of mooring lines needed to be increased or combined with dynamic positioning techniques to optimize the design.

A New Proposal Generalized Predictive Control Algorithm With Polynomial Reference Tracking Applied for Sodium Fast Reactors

This paper proposes a generalized predictive control (GPC) with constraints and orthonormal Laguerre functions using the simplified model of the primary system (reactor core and intermediate heat exchanger (IHX)) of a prototypical sodium fast reactor (SFR). This paper develops a multiple-input multiple-output (MIMO) GPC with input constraints able to track polynomial references of any degree applied in coolant temperature difference across the core and fractional power. The manipulated variables of the GPC-SFR are the reactivity and the sodium flow rate of the primary and secondary pipes. Moreover, orthonormal Laguerre functions and step down condition number techniques were also applied to avoid the numerical ill-conditioning issue in quadratic programming of large systems. Thus, a GPC type-2 was designed to control fractional power, coolant temperature difference across the core and sodium tank temperature of the SFR primary system when temperature references change according to a linear ramp after reaching their steady-state operation, sustaining 100% power operation on the reactor. In order to analyze the load tracking capability of the GPC-SFR type-2, the load following from 100% fractional power (FP) to 60% FP at 0.8% FP/min rate is simulated. Constraints on the rate of coolant temperature difference across the core and reactivity were applied for the design safety. For comparison criteria, this paper compares the GPC-SFR type-2 with the GPC-SFR type-1, i.e, standard model predictive control (MPC), to verify the viability and superior performance of the proposal regarding: (a) ramp-tracking capability of temperature and load; (b) the rejections of a reactivity disturbance of -1 cent and a secondary sodium inlet temperature disturbance of +10°F; and (c) a simulation with uncertainty in reactor design. The simulations show that the GPC-SFR type-2 overcome the GPC-SFR type-1 robustness and performance.

Дослідження динамічних навантажень рами фронтального навантажувача з використанням комп’ютерних 3D моделей у середовищі Siemens NX

When designing new construction and road machines, a variety of CAD and CAE computer programs are used. The designer has the ability to set certain strength properties of the future structure using finite element calculations, and after the first prototype is made, the moment comes when it needs to be tested for loads applied during technological operations to confirm the preliminary strength calculations. The goal of this work is to compare the test results of 3D models of two load-bearing systems of the T-156B loader, one of which is the original and the other a fivefold reduced copy. The result of the comparison is a reduction factor, the calculation of which will allow us to determine how and how many times the load is reduced when scaling 3D models. Previous work on this topic was done in the Ansys calculation complex, but the long process of calculating the task, importing, and complex process of configuring the model forced us to switch to a faster Siemens NX software complex. This software package has a clear and simple interface while performing calculation tasks much faster than Ansys. In this work, similarity coefficients were calculated for two more common cases of forklift operations: moving a full bucket over an uneven surface and colliding with an obstacle while filling the bucket. Thus, knowing these coefficients, it can be assumed that when modeling a new load-bearing system, by making a reduced copy of it in the appropriate scale and testing it for loading by means of computer modeling, or by conducting field tests, it is possible to calculate what loads will affect the model with natural dimensions. The article proposes a new solution for analyzing the strength of load-bearing systems at the design stage using the theory of similarity. This method makes it possible not to create a full-size model of a new load-bearing system (frame) in metal for testing. In accordance with the proposed method, it is enough to make a scaled simplified model of the future load-bearing system (frame), conduct strength tests and, in accordance with the similarity coefficient, calculate what loads will affect the full-size load-bearing system. This method can significantly reduce the cost of materials, production, and manufacturing time for new products.

An Online Approach to Covert Attack Detection and Identification in Power Systems

The development of information technology and digital control systems has posed an inevitable trend of interconnectivity and wirelessness of data communications in power systems. As a result, the cybersecurity of power systems has been raising concerns over the past decades. Yet the complexity of power systems and their conventional designs with local and wide area network communications has posed increasing vulnerability to cyberattacks. Among the types of cyberattacks, data integrity attacks can be more harmful to power systems, especially power transmission systems, through malicious manipulation of measurement and control data to cause damage to the physical system. As the sophistication of cyberattacks increases, certain cyberattacks can successfully bypass traditional intrusion detection systems, which calls for better design of detection schemes. On the other hand, in a large-scale network, attack identification for a power system is as important as attack detection. In this paper, we develop an online approach based on the Sparse Group Lasso to detect and identify the location of a typical type of data integrity attack named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">covert attacks</i> on power transmission systems. We provide the theoretical foundation of the proposed method with a simplified linear system model and extend the method to nonlinear systems. We validate the performance of our method on both linear and nonlinear system settings with a comprehensive numerical study.

Adaptive Cooperative Load Transportation by a Team of Quadrotors With Multiple Constraint Requirements

Cable-suspended load carried by multiple unman- ned aerial vehicles (UAVs) has applications in many areas. However, most existing aerial load transportation works are tailored to a specific type of load transportation tasks, or assume simplified system models or transportation scenarios. Furthermore, no existing works on this topic can provide a unified framework to address multiple performance and safety constraints during the cooperative transportation operation. In this paper, we propose and investigate a new constrained cooperative control architecture for an UAV team, which are collaboratively carrying a three-dimensional load, subject to multiple user-defined time-varying performance and safety constraint requirements. A unified framework using universal barrier functions has been proposed to deal with different types of constraint requirements. Moreover, control saturation and uncertainties in UAV inertia matrices are dealt with by employing adaptive estimators. Exponential convergence on the distance and attitude tracking errors can be guaranteed by the algorithm. Lastly, we discuss a simulation example that further shows the efficacy of the proposed cooperative control framework.

DESIGN AND MANUFACTURE OF AN INDUSTRIAL AUTOMATIC ROTI (SOUTH ASIAN FLAT-BREAD) MAKER

As a part of research, this product was consigned to design with the development with an engineering concept. At the preliminary stage, the industrial automatic flour bread maker machine was chosen the group, and accordingly, it was approved by the respected faculty. Bangladesh is not only a densely populated country but also a fastest developing country in the world. For saving precious time and capturing large market of this sub-continent, it is important to finish research on product development and market analysis accurately. Restaurants in busy area, people wait in a queue to have their ordered Roti (a south Asian bread with round and flat shape) for the lengthy process of Roti making as they are made by human hand. Industrial automatic Roti maker will help people a lot to make Roti in a very simple way within a short time. This machine can rapidly use in restaurants, canteens, and hostels to serve bread to the customers timely. It reduces the working effort of the chef as well. In this project, it was offered with progressed design for the automatic Roti maker machine along with supplementary features like a ‘hand controlled wheel’ to operate without power source for emergency purpose, safety box was used for safeties. The innovative design reduces the cost of the machine more than before. This project aims to learn with close observation about the industrial automatic Roti maker machine and its working functions. It was also tested the efficiency of Roti making process considering cost and time factors. The main purpose was to reduce the bread-making effort along with maintaining a better shape and size of Roti to illustrate a simple system model. All parts of this machine are structured by ‘Solid Works-2015’ software.