Proposed Performance Index Research Articles

Simulation study on four-wheeled mobile robot mechanisms using various performance criteria

In this paper, the performance criteria for various four-wheeled mobile robots that are crucial for assessing a robot’s fitness for mobility to successfully complete missions are introduced. The seven proposed performance indices, the root mean squared acceleration (RMSA), posture variance index (PVI), static stability margin (SSM), force angle stability margin (FASM), energy stability margin (ESM), friction requirement (μr), and velocity constraint violation (VCV), address the fluctuation, rollover, and slippage problems in four-wheeled mobile robots. The simulations considered a square bump-shaped obstacle, and the dimensions of the robot were based on nine simulation cases in a 3D environment. Additionally, a methodology for evaluating these seven criteria is outlined. To streamline the simulation process, Taguchi’s catalog of orthogonal arrays (OAs) was used for the experimental design, specifically L9 OA with four factors and three levels was used. Analysis of means (ANOM) was applied to assess the influence of each design factor on the seven criteria, leveraging the OA orthogonality. Finally, the sensitivity analysis and potential for evaluating general mobile robots in the future are discussed.

Beam narrowing test: a motor index of post-stroke motor evaluation in an aged rat model of cerebral ischemia

Each year, 15 million people worldwide suffer from strokes. Consequently, researchers face increasing pressure to develop reliable behavioural tests for assessing functional recovery after a stroke. Our aim was to establish a new motor performance index that can be used to evaluate post-stroke recovery in both young and aged animals. Furthermore, we validate the proposed procedure and recommend the necessary number of animals for experimental stroke studies. Young (n = 20) and aged (n = 27) Sprague–Dawley rats were randomly assigned to receive either sham or stroke surgery. The newly proposed performance index was calculated for the post-stroke acute, subacute and chronic phases. The advantage of using our test over current tests lies in the fact that the newly proposed motor index test evaluates not only the performance of the unaffected side in comparison to the affected one but also assesses overall performance by taking into account speed and coordination. Moreover, it reduces the number of animals needed to achieve a statistical power of 80%. This aspect is particularly crucial when studying aged rodents. Our approach can be used to monitor and assess the effectiveness of stroke therapies in experimental models using aged animals.

Model-Free Q-Learning for the Tracking Problem of Linear Discrete-Time Systems.

In this article, a model-free Q-learning algorithm is proposed to solve the tracking problem of linear discrete-time systems with completely unknown system dynamics. To eliminate tracking errors, a performance index of the Q-learning approach is formulated, which can transform the tracking problem into a regulation one. Compared with the existing adaptive dynamic programming (ADP) methods and Q-learning approaches, the proposed performance index adds a product term composed of a gain matrix and the reference tracking trajectory to the control input quadratic form. In addition, without requiring any prior knowledge of the dynamics of the original controlled system and command generator, the control policy obtained by the proposed approach can be deduced by an iterative technique relying on the online information of the system state, the control input, and the reference tracking trajectory. In each iteration of the proposed method, the desired control input can be updated by the iterative criteria derived from a precondition of the controlled system and the reference tracking trajectory, which ensures that the obtained control policy can eliminate tracking errors in theory. Moreover, to effectively use less data to obtain the optimal control policy, the off-policy approach is introduced into the proposed algorithm. Finally, the effectiveness of the proposed algorithm is verified by a numerical simulation.

Drivers’ Steering Behavior in Curve by Means of New Indicators

The design of road geometry is based on a rather elementary assumption that the user strictly follows the lane axis. Based on this hypothesis, the ideal trend of some factors related to the driver’s performance, such as steering angle and speed, can be derived to optimize the most appropriate design choices. In practice, driving behavior differs from the assumed one and produces trends in these variables, which are very different from the ideal functions. The purpose of this research is therefore to propose synthetic performance indicators useful for highlighting the real characteristics of users’ driving behavior during road travel. Toward this aim, some driving experiments along four different curves in a simulated environment were studied in order to evidence possible criticisms. The proposed indicators showed a remarkable ability to represent and synthesize even very complex performance function trends. The proposed performance indicators can have multiple uses, such as, for example, in statistical analyses—which are generally carried out at a later stage—or constitute sufficient information to guide the decisions of infrastructure managers. In the long term, in a “smart road” perspective, they can be used by road administrators for information exchange among users (with each other and with the infrastructure) to improve road operation and safety.

Using Pearson correlation coefficient as a performance indicator in the compensation algorithm of asynchronous temperature-humidity sensor pair

Artificial Intelligence (AI) based control algorithms for heating, ventilation, and air conditioning (HVAC) equipment have been gradually applied to improve building energy efficiency. Nevertheless, a reliable dataset is certainly a cornerstone for any meaningful AI training. Unfortunately, significant errors exist on humidity records due to asynchronous humidity and temperature sensor time constants, which need to be better compensated. This study aims to verify the general applicability of the previously proposed compensation algorithm and discover a new method to determine essential parameters for the algorithm without lab testing, which makes it possible to apply the compensation algorithm to on-duty sensor pairs. Experiment results from newly tested sensor pairs are found comparable to the previous study's outcome, which confirms the algorithm's general applicability. Meanwhile, the newly proposed performance indicator – the Pearson correlation coefficient (PCC) of humidity ratio and temperature – results in a 64–97 % error reduction on the tested sensor pairs. Despite not being as steady as the original lab method, the PCC proved a possible alternative method worth further investigation due to its accessibility.

Coordinated Control Strategy of Railway Multisource Traction System With Energy Storage and Renewable Energy

Influenced by the growing daily travel demand of citizens and extension of urban land, the construction of the urban railway transit (URT) system is gradually increasing nowadays. This situation implies more electricity consumption in URT and more challenges to URT operation stability. Therefore, based on the existing traction substation, this research proposes a configuration of multi-source traction system (MSTS) for URT with a coordinated control strategy according to power profile of the system. The proposed MSTS, including conventional traction system (CTS), renewable energy source (RES), and energy storage system (ESS), have been modelled first. After that, considering the system dynamic performance and ESS capacity, a coordinated control strategy is designed to manage the MSTS energy flow. The control strategy considers the substation voltage as control signal which is optimized by proposed performance index. The case study is conducted on a three-station railway route with two substations. The proposed MSTS with a coordinated control strategy is compared with normal CTS considering multi-train timetables with different departure intervals. The simulation result illustrates that the proposed MSTS can maintain the state of charge (SOC) of ESS and reduce the substation peak power and voltage fluctuation, which is verified both in short-term and long-term simulation. Meanwhile, it can improve the substation capacity by decreasing the energy consumption of CTS to deal with the increasing demand for URT. the case study denotes that the energy-saving rate can be up to 36.25%, and the peak power is reduced up to 46.32%.

Nearly optimal fault-tolerant constrained tracking for multi-axis servo system via practical terminal sliding mode and adaptive dynamic programming

In this paper, a nearly optimal tracking control is proposed for n-links robotic manipulators subject to parameter uncertainties, time-profile failures, and input saturation constraints. Firstly, the practical terminal sliding-mode (PTSM) manifold with a linear additional term is proposed to combine the system states related to joint rotation, such that the controlled states quickly fall into a tiny neighborhood of the equilibrium once they reach the PTSM manifold. Secondly, a nearly optimal sliding-mode reaching law is designed by using the adaptive dynamic programming (ADP) technique. Benefiting from a non-quadratic positive defined mapping of the proposed performance index, which relates to the derivative of the sliding-mode function, reduced-order system dynamics can be constrained to a desired region. For the bounded actuator fault caused by various inducements such as the power supply fluctuation and the wear of parts, a radial basis function neural network (RBFNN) is introduced to compensate for this, and the input saturation constraints of the controlled plant are also compensated at the same time. Innovatively, the node weights of RBFNN are updated by the critic network of the ADP framework, such that the integrity of the proposed control strategy is improved. Simulations verify the main conclusions.

Performance indices and fragility assessment of steel frame structure with bolted low-yield-point steel connection components

A resilient steel frame structure equipped with replaceable ductile and energy-dissipative connection components was developed in this study. Connective components, such as splice plates and T-stubs are made of low-yield-point steels (LYPs), which have superior ductility and energy dissipation capacity. The plastic hinge can be separated from the column surface by local weakening, thus concentrating local damage within low-yield-point steel connection components (LYP-Cs) to effectively enhance ductility of the structure. Five-story and ten-story bolted steel frame structures with four configuration parameters were designed to investigate the seismic performance and damage development of steel frame structures with LYP-Cs (SF-LYP-Cs). Corresponding numerical models were established. Welded steel frame structures with traditional reduced beam sections (SF-RBS) were also established for comparison. Pushover analyses were conducted to explore the effect of structural fuses and to obtain multi-stage performance indices of the resilient steel frame structure based on energy dissipation proportion (EDP) and damage behavior. Incremental dynamic analysis was performed to verify proposed performance indices, and seismic performance of SF-LYP-Cs was evaluated via fragility analysis. The results showed that LYP-Cs were not only effective structural fuses but also effectively delayed the damage development in the primary members, thus reducing the failure probability of the structures. The multi-stage performance indices were conductive to describe the multiple lines of resistance and effects of structural fuses. A larger weakening degree and smaller beam height mitigated plastic damage development in primary members. When LYP-Cs dominate the system’s energy dissipation, the section sizes of columns and the number of structural stories exert only slight influence on the structural performance indices.

Stiffness analysis and optimization of an asymmetric 3T1R parallel mechanism

In this paper, an asymmetric 3T1R parallel mechanism is proposed that has higher stiffness in specific directions. The stiffness model is established by using virtual spring theory, and the Cartesian stiffness matrix is obtained. The stiffness performance evaluation indices are deduced by the dimensionless parameterization method. Under the condition of satisfying the high-speed performance and dexterity, the optimal size parameters of the mechanism are got by using the DE (differential evolution) algorithm with stiffness performance as the index. By comparing the stiffness performance atlases before and after the optimization, it is showed that the stiffness performance has been improved and the reachable workspace has been increased. The results verify the feasibility of the proposed performance indices and optimization algorithm.

Recommendations for quality control in industrial 3D concrete printing construction with mono-component concrete: A critical evaluation of ten test methods and the introduction of the performance index

The critical assessment of the applicability of fresh concrete test methods for characterizing printable concrete quality and its structural build-up rate is rare in the literature. To address this gap, this study evaluates the potentials and limitations of eight offline test methods (hand vane, rheometer, compressive strength, squeeze flow, penetrometer, ultrasonic pulse velocity, slump, and flow table) and two inline test methods (slug test and extruder torque measurement). This research proposes a new parameter called “performance index” to assess the capability of any test to detect structural buildup. The study establishes a ranking of the eight offline tests on the proposed performance index and evaluates the advantages and disadvantages of each test in terms of portability, price, required human labor, and material. The results of this study can be used as a first guideline to select a proper quality control test for industrial 3D concrete printing construction.

Frequency Control of a Realistic Dish Stirling Solar Thermal System and Accurate HVDC Models Using a Cascaded FOPI-IDDN-Based Crow Search Algorithm

Unbalancing the real power in power system leads to fluctuation in system frequency which can cause the several negative effects on the performance and reliability of the interconnected power system. Therefore, to deal with this, the load frequency control (LFC) of a three-area asymmetric thermal power system integrated with a solar thermal power plant (STPP), a realistic dish-stirling solar thermal system (DSTS), and an accurate high voltage direct current (HVDC) link are presented in this work. For the suggested system, a novel cascade controller called fractional-order proportional-integral and integral-double-derivative with filter (FOPI-IDDN) is designed. By minimising a newly proposed performance index called the HPA-ISE and adjusting the controller and other system model parameters using a metaheuristic method called the crow search algorithm (CS). When comparing the system dynamics, it was found that the suggested FOPI-IDDN controller outperformed the FOPI, PIDN, and FOPIDN controllers. The findings of this study show that HPA-ISE shows approximately 30% and 60% improvements in settling time (ST) and peak overshoots (POS) for frequency response, and 32% and 18% improvements for the tie power responses in terms of ST and POS over ISE criteria. Also, studies on different area capacity ratios have shown that a system connected to a greater capacity ratio operates better. The realistic DSTS system with fixed and recurring insolation in area 1 and area 2 outperforms the others, according to experiments using different DSTS insolation. Also, it is discovered that the parallel AC-AHVDC link study is superior to the AC and HVDC connection research. Moreover, it seems from the sensitivity study that the CS-optimized FOPI-IDDN controller improvements obtained under normal settings are consistent across a wide range of changes.

General Modeling of Interconnected Hubs in Series and Parallel Structures

Energy decision-makers have considered solutions to meet the demand for affordable and highly reliable energy due to population growth and technological advancement. One of these possibilities is the utilization of several energy carriers in one system as an energy hub. Instead of optimizing a single energy carrier, the energy hub optimizes a system with many energy carriers, including electricity, natural gas, and local heat, by use of its converters and storages. In this paper, a novel and new general framework is proposed to evaluate and compare both series and parallel connections of n hub to analyze cost and reliability aspects by considering coupling matrices. In order to compare the outcomes of the connections of several comparable hubs in both series and parallel modes, new indices are proposed and evaluated from the aspect of evaluating the amount of energy not supplied and the amount of energy input to each hub. Additionally, simulations are run for a variety of scenarios in order to better assess the proposed model and investigate each type of connection by evaluating the proposed performance indices. The results show that in all the examined scenarios, the total cost of the energy carriers in the series mode (link in the output) is lower than in the parallel mode (link in the input).

Identification method of typical defects in transmission lines based on YOLOv5 object detection algorithm

In order to realize the automatic identification of typical defects in transmission lines, a typical defect identification method for transmission lines based on You Only Look Once (YOLO)v5 algorithm is proposed, which has the advantages of low missing detection rate and false detection rate. Firstly, a transmission line defect image dataset is constructed for three typical defects: bird’s nest defect, insulator defect and shakeproof hammer defect, and the corresponding image labeling strategy is formulated according to the defect characteristics. Secondly, this paper introduces the network structure of YOLOv5 in detail. For the sake of further improving the neural network’s ability to recognize the visual defects of transmission lines, the attention mechanism and small target detection layer are introduced into YOLOv5 neural network. Finally, this paper design transmission line defect recognition cases based on three kinds of typical defects, and the proposed method is compared with the recognition methods based on Faster Region based Convolutional Neural Network (RCNN) and Single Shot MultiBox Detector (SSD) in terms of the proposed performance indexes (missing detection rate and false detection rate). The results show that the missing detection rate and false detection rate of the YOLOv5-based identification method are much lower than those of the Faster RCNN and SSD-based identification methods, and the improved YOLOv5 network recognition rate is higher, which is significant for reducing the workload of transmission line inspection personnel.

Establishment of urban road maintenance model based on performance-based contracts

ABSTRACT Maintaining urban roads in a good condition is a basic duty of any city government. Traditionally, urban road maintenance is performed by a contractor that provides the required manpower and equipment resources to complete the necessary daily inspection and repair works. Although the quality of roads is acceptable, the inefficiency is evident everywhere. A performance-based contract (PBC) is used in the field of road maintenance in various countries, primarily for highway or large-area pavement rehabilitation and follow-up maintenance as the subject of the contract. In this study, we applied the design thinking approach to establish a PBC implementation model for urban road patrolling and sporadic repair. Moreover, to ensure the feasibility of the proposed model and to decrease the political risk of execution outcome, we adopted a two-stage validation in this study. The proposed performance indicators were examined by the historical data of road maintenance in Taipei City, and the feasibility of the proposed PBC implementation model was then confirmed by domain experts. The research outcomes could be used to develop PBCs for maintenance management of other infrastructures with better maintenance performances.

Robust Data-Driven Design for Fault Diagnosis of Industrial Drives

Due to the presence of actuator disturbances and sensor noise, increased false alarm rate and decreased fault detection rate in fault diagnosis systems have become major concerns. Various performance indexes are proposed to deal with such problems with certain limitations. This paper proposes a robust performance-index based fault diagnosis methodology using input–output data. That data is used to construct robust parity space using the subspace identification method and proposed performance index. Generated residual shows enhanced sensitivity towards faults and robustness against unknown disturbances simultaneously. The threshold for residual is designed using the Gaussian likelihood ratio, and the wavelet transformation is used for post-processing. The proposed performance index is further used to develop a fault isolation procedure. To specify the location of the fault, a modified fault isolation scheme based on perfect unknown input decoupling is proposed that makes actuator and sensor residuals robust against disturbances and noise. The proposed detection and isolation scheme is implemented on the induction motor in the experimental setup. The results have shown the percentage fault detection of 98.88%, which is superior among recent research.

The sustainability opportunity study (SOS) – diagnosing by operationalising and sensemaking of sustainability using Total Quality Management

PurposeA key issue to manage sustainability is to be able to operationalise it. Relevant indicators require an appropriate definition of sustainability and sustainable development for the studied organisation. A common problem is inadequate understanding of what sustainability is from an organisational perspective. The purpose of this paper is to propose how to understand, define and measure diagnosing of sustainability from an outside-in perspective.Design/methodology/approachThe building, health care, education and tourism value chains are studied. Based on interpreted stakeholder sustainability needs the stages of understanding, defining and measuring of diagnosing are reviewed, and interpretations proposed. This is with focus on identifying the vital few sustainability impacts in the studied value chains.FindingsThe resulting definitions and proposed performance indicators for the chosen areas indicate that the approach works resulting in proposed definitions and indicators for sustainability and sustainable development based on stakeholders need focus. Having clear definitions and performance indicators will support working effectively with sustainable development.Research limitations/implicationsThe resulting definitions and proposed performance indicators for the chosen areas indicate that the approach works. Further, proposed definitions and indicators for sustainability and sustainable development based on stakeholder needs focus is useful. Having clear definitions and performance indicators will help an organisation engage with sustainability and be sustainable within an organisational context.Practical implicationsThe proposed approach enables using quality management for sustainable development.Social implicationsSocial sustainability is viewed from a poverty and affordability perspective.Originality/valueResults indicate that there is a value in using an outside-in approach with focus on stakeholder needs in connection with a process-based approach. The approach is in contrast with the customary way of defining sustainability which mostly is based on an inside-out approach identifying several indicators and then adding these to a measure of sustainability.

Performance-based optimum seismic design of cable tray system

This study aims to develop a simple yet efficient performance-based design optimization methodology for cable tray systems in building structures. In the paper, the drift ratio between adjacent supports is proposed as a performance index and the acceptable threshold values are specified based on experimental results of shaking table tests for cable tray systems. The seismic performance levels of cable tray systems are presented according to current seismic design codes. A performance-based optimum seismic design procedure for cable tray systems is given and verified by three studied cases. The results show that the proposed performance index (drift ratio between adjacent supports) for cable tray systems is a reasonable criterion for performance-based seismic design and is much more practical and rational than the typical criterion recommended in seismic design codes. The cable tray systems designed according to the proposed procedures can derive the cost-efficient solution and meet the expected seismic performance objectives for cable tray systems as well as control the damage development of the cable tray.

Performance assessment of ensembles of in situ workflows under resource constraints

SummaryScientific breakthroughs in biomolecular methods and improvements in hardware technology have shifted from a long‐running simulation to a large set of shorter simulations running simultaneously, called an ensemble. In an ensemble, simulations are usually coupled with analyses of data produced by the simulations. In situ methods can be used to analyze large volumes of data generated by scientific simulations at runtime (i.e., simulations and analyses are performed concurrently). In this work, we study the execution of ensemble‐based simulations paired with in situ analyses using in‐memory staging methods. Using an ensemble of molecular dynamics in situ workflows with multiple simulations and analyses, we first show that collecting traditional metrics such as makespan, instructions per cycle, memory usage, or cache miss ratio is not sufficient to characterize complex behaviors of ensembles. We propose a method to evaluate the performance of ensembles of workflows that captures multiple resource usage aspects: resource efficiency, resource allocation, and resource provisioning. Experimental results demonstrate that the proposed method can effectively distinguish the performance of different component placements in an ensemble with up to 32 ensemble members. By evaluating different co‐location scenarios, our proposed performance indicators demonstrate benefits of co‐locating simulation and coupled analyses within a compute node.

A new performance index for measuring the effect of single target tracking with Kalman particle filter

In dealing with the problems of nonlinear and non-Gaussian systems, the Kalman particle filter (KPF) algorithm has been widely used for the aerial and underwater target tracking system, which is vulnerable to environmental interference in recent years, especially in military fields. However, in most of the target tracking research, the indexes used by researchers to evaluate tracking algorithms are usually limited to the state difference or the root mean square error in the tracking process, and the overall tracking effect is only evaluated by the tracking time. These indexes cannot be evaluated for the algorithm that does not have obvious error optimization performance in the tracking process but actually improves the overall tracking effect. Therefore, this paper proposes to evaluate the tracking effect of different tracking algorithms by using the mean square error of relative points in the plane control network of engineering survey. Simulation results show that the proposed performance index combined with the tracking sampling time and the mean square error of tracking position can effectively evaluate the local and global tracking performance of different algorithms.

Distributed model predictive control based on neighborhood optimization for thickness and tension control system in tandem cold rolling mill

The control precision of thickness and tension is a crucial indicator for evaluating a tandem cold rolling control system. However, the control mode for field application cannot meet the actual quality requirements. Therefore, a distributed model predictive control (DMPC) strategy combined with neighborhood optimization is proposed to decrease the strip thickness deviation and tension change in this paper. First, a cold rolling model describing the relationship among the process parameters is established for the multi-stand cold rolling system. Then, according to the neighborhood optimization theory, the state evolution equation of the output system on each stand is derived. Furthermore, through proper consideration of the input and state information during optimization, optimal control variables are obtained using the proposed performance index to improve the system performance. A series of simulations were carried out with actual rolling data to analyze and validate the capability of the designed control system. The statistical data show that as roll speed disturbance occurs, the thickness and tension deviations can be controlled within respective ranges of 6 × 10 −5mm and 0.012 kN with the DMPC control strategy. In addition, each scan cycle calculation only takes 0.0085 s in such a strategy. Compared with the conventional control method, the thickness and tension DMPC control system provides excellent performance and can effectively enhance the strip product quality.