Preset Value Research Articles

An adaptive control strategy for grid-forming of SCIG-based wind energy conversion systems

One of the crucial issues in the expansion of isolated wind energy conversion systems (WECSs) is the design of a grid forming control structure that is robust to changes of the system’s operating point in the steady-state as well as transient conditions. This paper has addressed the voltage/frequency control of a local microgrid as well as flux and slip control of a squirrel cage induction generator that feeds the microgrid via a back-to-back converter in an isolated WECS. An adaptive nonlinear voltage control structure has been proposed for load side converter (LSC) consists of a constant frequency voltage regulator and a current controller based on the Lyapunov function method (LFM), which are connected in cascade. In an outer loop, the reference current of LSC is generated by the voltage regulator designated for maintaining the voltage/frequency of the microgrid. In an inner loop, the reference signals are robustly tracked by the current controller. In a novel reference frame that its angle difference with the stationary reference frame is determined by a dual loop DC link voltage controller, an LFM-based nonlinear flux controller is proposed for the machine side converter (MSC). Using the proposed flux control structure, in addition to maintaining the flux magnitude at a nominal value, by controlling the generator slip through adjusting the speed of the proposed reference frame, the power balance is established and the DC voltage is maintained at a pre-set value. The performance of the proposed controllers has been investigated through simulation in the MATLAB® software. The obtained results confirm the robustness and stability of the proposed control structure with respect to various disturbances and uncertainties.

Accuracy of the estimations of respiratory mechanics using an expiratory time constant in passive and active breathing conditions: a bench study

BackgroundRespiratory mechanics monitoring provides useful information for guiding mechanical ventilation, but many measuring methods are inappropriate for awake patients. This study aimed to evaluate the accuracy of dynamic mechanics estimation using expiratory time constant (RCexp) calculation during noninvasive pressure support ventilation (PSV) with air leak in different lung models.MethodsA Respironics V60 ventilator was connected to an active breathing simulator for modeling five profiles: normal adult, restrictive, mildly and severely obstructive, and mixed obstructive/restrictive. Inspiratory pressure support was adjusted to maintain tidal volumes (VT), achieving 5.0, 7.0, and 10.0 ml/kg body weight. PEEP was set at 5 cmH2O, and the back-up rate was 10 bpm. Measurements were conducted at system leaks of 25–28 L/min. RCexp was estimated from the ratio at 75% exhaled VT and flow rate, which was then used to determine respiratory system compliance (Crs) and airway resistance (Raw).ResultsIn non-obstructive conditions (Raw ≤ 10 cmH2O/L/s), the Crs was overestimated in the PSV mode. Peak inspiratory and expiratory flow and VT increased with PS levels, as calculated Crs decreased. In passive breathing, the difference of Crs between different VT was no significant. Underestimations of inspiratory resistance and expiratory resistance were observed at VT of 5.0 ml/kg. The difference was minimal at VT of 7.0 ml/kg. During non-invasive PSV, the estimation of airway resistance with the RCexp method was accurately at VT of 7.0 ml/kg.ConclusionsThe difference between the calculated Crs and the preset value was influenced by the volume, status and inspiratory effort in spontaneously breathing.

Artificial Intelligence Technologies in Criminal Procedural Proving

Objective: to summarize and analyze the approaches, established in criminal procedural science, regarding the use of artificial intelligence technologies, to elaborate an author’s approach to the prospects of transformation of criminal procedural proving under the influence of artificial intelligence technologies.Methods: the methodological basis of the research is integrity of general, general scientific and specific legal methods of legal science, including abstract-logical, comparative-legal and prognostic methods.Results: the main areas of using artificial intelligence technologies in the cri mi nal procedure are defined, such as prophylaxis and detection of crimes, organization of preliminary investigation, criminological support of crime investigation, and assessing evidences at pre-trial and trial stages. The author comes to a conclusion that the rather optimistic approach to this issue, established in the science of criminal procedure, significantly outstrips the actually existing artificial intelligence technologies. The main requirements are identified, which the activity of using artificial intelligence in collecting evidences in a criminal case should satisfy. The author pays attention to the problems of using artificial intelligence technologies in conducting expert assessments, requiring an improved methodology of forensic work. The issue is considered of the prospects of transforming the criminal-procedural proving process under introduction of artificial intelligence technologies. A conclusion is substantiated that the assessment of evidences with mathematical algorithms, in which preset values of each evidence quality are used, contradict to the principle of free assessment of evidences in the criminal procedure. The author comes to a conclusion that today there are no sufficient grounds for endowing artificial intelligence with legal personality during proving.Scientific novelty: the work presents an attempt to consider the role of artificial intelligence in the criminal-procedural proving; it specifies the requirements to be met by this technology during evidences collection and analyzes the prospects of transforming the proving process under the introduction of artificial intelligence technologies.Practical significance: the main provisions and conclusions of the research can be used to improve a mechanism of legal regulation of artificial intelligence technologies in the criminal procedure.

Low Power Forest Fire Detection

Abstract: Fire detection and warning systems are critical for ensuring the safety of people and property. We present an innovative system for detecting and alerting fires that employs a combination of an MQ135 gas sensor, Arduino Uno microcontroller, and SIM900A GSM module. Its purpose is to identify the existence of smoke and other types of gases that are emitted during a fire and to provide real-time alerts to a pre-programmed set of phone numbers through SMS using the SIM900A GSM module. The system also triggers an alarm to alert people and the forest department in the vicinity of the fire. The MQ135 gas sensor is used to detect the presence of smoke and other gases in the air. The sensor's output is fed into the Arduino Uno microcontroller, which processes the data and triggers the alarm if the concentration of smoke or other gases exceeds a pre-set threshold value. The SIM900A GSM module is used to send real-time alerts to pre-programmed phone numbers through SMS, enabling swift action to be taken in case of a fire. We also use deep sleep mode to save power. We have divided the forest into various zones according to activity in that area.

Combined application of EPANET and empirical model for possible formation of trihalomethanes in water distribution network of Chattogram city to identify potential carcinogenic health risk zone

The study identifies potential carcinogenic health risk-zone of Chattogram city for the occurrence of trihalomethanes (THMs) at its water distribution network. The EPANET-THMs simulation model along with an empirical model have been adopted in the study to predict THMs content of supply water of the distribution network of the city’s Karnaphuli service area. The empirical model has estimated THMs level of supply water based on influential water quality parameters, and few of these have been used as pre-set values for subsequent EPANET simulation. The simulation (R2= 0.7) shows that THMs’ concentrations throughout the network vary from 33 to 486 μg/L. Around 60% of total junctions showed THMs concentrations above 150 μg/L, while that is above 50 μg/L for most (99%) of the junctions. Residual Free chlorine, one of the precursors for the THMs formation in distribution line, has also been simulated by EPANET considering varying applied chlorine dose at the water purification unit and wall (Kw) and bulk (Kb) decay constants. The simulated free residual chlorine peaks are found to be closer to the actual values with chlorine dose of 2 mg/L, and decay constants, Kw = 1 d−1 and Kb = 1 d−1. A mean lifetime total risk of cancer due to the presence of THMs has been found to be very high. Spatial distribution of carcinogenic risk shows that the central zone of the service area is the most vulnerable zone, followed by the western and northern zone. The first ever zone wise risk identification could be used as baseline data for operational and regulatory purposes and may raise awareness among the city’s inhabitants. Furthermore, the application of EPANET in combination with an empirical model could be an effective tool for predicting THMs’ concentration in water distribution networks in developing countries like Bangladesh to minimize the expenses of measuring THMs.

A novel [formula omitted] control for T-S fuzzy systems with transform matching membership functions

This article studies H∞ optimization issue of Takagi-Sugeno (T-S) fuzzy systems with an improved transform matching membership functions (MFs) approach. Different from existing transform matching MFs control method, a polynomial disassembling strategy is first proposed for T-S fuzzy systems. Then, combining with parameterized linear matrix inequality (LMI) technique which can remove the inequality constraints between the MFs in systems and fuzzy controllers, sufficient conditions are presented to maintain asymptotic stability and desired H∞ performance for studied plants. Afterwards, a novel MFs online optimization algorithm is proposed for the first time to automatically adjust the values of scaling and bias parameters so as to realize better H∞ performance. In contrast to the traditional control using improved matching MFs, the practical behavior of disturbance attenuation index is reduced efficiently. Additionally, the proposed MFs online optimization algorithm is capable of sustaining the desired H∞ performance when the disturbance channels exist modeling errors, i.e., the practical disturbance attenuation index γ is still less than the preset value. For guaranteeing the convergence of cost function, sufficient condition is obtained based upon Lyapunov stability theory. Finally, two demonstrative simulations are presented to confirm the advantages and benefits of the novel MFs online optimization control strategy.

KTIG–MIG hybrid arc welding process

Metal-inert gas welding is an important welding process but the process instability easily induces spatter and undercut defects. To improve the welding process stability, a new hybrid arc welding process, named KTIG–MIG, was proposed in this paper. Arc characteristics were preliminarily studied. It is found that in KTIG–MIG hybrid welding, MIG arc is stable even it is shielded with pure argon gas; stable spray transfer is easily achieved in a much wider process window, especially the lowest voltage to achieve spray transfer is greatly reduced; KTIG arc voltage decreases than that in single KTIG arc, and MIG arc current is higher than the pre-set value. Cooling state of the KTIG tungsten plays a key role in slowing tungsten erosion.

Economic and Ecological Optimization of Thermal Insulation Depending on the Pre-Set Temperature in a Dwelling

Improvement of the energy efficiency of buildings contributes to energy savings. It is obvious that thermal modernization of a building reduces the demand for energy needed to heat it. The energy demand itself also depends significantly on the temperature maintained inside the building. The article proposes a methodology for determining the economic and ecological benefits of thermal insulation of a building and the optimal thickness of thermal insulation depending on the pre-set temperature. The analysis includes various types of heat sources and materials used for thermal insulation. A range of pre-set air temperature values in residential premises from 17 °C to 26 °C was analysed. Determining the optimal thickness of the external walls, in accordance with the preferences of building users, even at the level of designing the thermal insulation of the building, is of significant importance for economic and ecological benefits. The optimum thickness of thermal insulation in the case of the ecological assessment was much higher in each variant than in the case of the economic assessment.

Compensation Method for the Carrier Magnetic Interference of Underwater Magnetic Vector Measurement System

This paper proposed a new compensation method of underwater magnetic vector measurement system which innovatively using the geomagnetic total field as benchmark. Moreover, this method does not require the use of heading angle data in the calculation of the compensation parameters, which avoids errors caused by insufficient accuracy of underwater heading angle. The implementation of these features relies on the new objective function constructed according to the characteristics of the spatial projection of the magnetic vector field on the horizontal plane of the geographical coordinate. The core matrix of the geomagnetic vector ellipsoid model is used as a constraint to determine the range of function solutions. The Levenberg-Marquardt algorithm is used to find the optimal solution to the new objective function. Three experiments were carried out to verify the proposed method. In simulation experiment, the deviation between the calculated value and the preset value is less than 0.01%. In field experiment, the standard deviation value of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x, y, z</i> magnetic components and the root mean square error of magnetic total field after compensation are reduced from 1527.38nT, 1397.35nT, 1529.16nT, 574.94nT to 9.86nT (0.65%), 9.99nT (0.72%), 5.63nT (0.38%), 2.14nT (0.37%). The proposed method is finally verified by marine experiment. The standard deviation value of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x, y, z</i> magnetic components and the root mean square error of magnetic total field after compensation are reduced from 575.02 nT, 830.60 nT, 620.95 nT, 1702.35 nT to 17.43 nT (1.11%), 14.14 nT (1.70%), 25.17nT (4.10%), 7.18 nT (0.42%).

Modeling and Centralized-ZVS Control for Wireless Charging Electric Vehicles Supplied by Parallel Modular Multi-Inverters

In this paper, a parallel modular multi-inverter (PMMI) topology is proposed to supply high power for wireless charging electric vehicles (EVs). A major challenge in the implementation of PMMI topology is zero-voltage switching (ZVS) for all inverters to avoid high-frequency switching losses. Therefore, a centralized-ZVS control and master–slave frequency following (MSFF) strategy are presented to realize ZVS for all PMMIs by a single controller structure without extra controllers needed on the slave inverters. Meanwhile, a modeling method directly related to the ZVS angle and operating frequency for an arbitrary number of PMMIs is proposed and linearized to analyze the system dynamic characteristics at the operating point. Additionally, to obtain the desired dynamic performance, an optimal controller coefficient (OCC) configuration method is proposed for the design of controller parameters. Finally, a laboratory wireless power transfer (WPT) prototype supplied by three PMMIs is designed, built, and tested to verify the correctness of the theoretical analysis. Experimental results show that the ZVS angle of all PMMIs can maintain at the preset value with the desired settling time under designed the PI controller parameters. The measured whole system power transmission efficiency is 94.1% at a 10 Ω load.

Kuznetsov–Ma rogue wave clusters of the nonlinear Schrödinger equation

In this work, we investigate rogue wave (RW) clusters of different shapes, composed of Kuznetsov–Ma solitons (KMSs) from the nonlinear Schrödinger equation (NLSE) with Kerr nonlinearity. We present three classes of exact higher-order solutions on uniform background that are calculated using the Darboux transformation (DT) scheme with precisely chosen parameters. The first solution class is characterized by strong intensity narrow peaks that are periodic along the evolution x-axis, when the eigenvalues in DT scheme generate KMSs with commensurate frequencies. The second solution class exhibits a form of elliptical rogue wave clusters; it is derived from the first solution class when the first m evolution shifts in the nth-order DT scheme are nonzero and equal. We show that the high-intensity peaks built on KMSs of order n-2m periodically appear along the x-axis. This structure, considered as the central rogue wave, is enclosed by m ellipses consisting of a certain number of the first-order KMSs determined by the ellipse index and the solution order. The third class of KMS clusters is obtained when purely imaginary DT eigenvalues tend to some preset offset value higher than one, while keeping the x-shifts unchanged. We show that the central rogue wave at (0, 0) always retains its n-2m order. The n tails composed of the first-order KMSs are formed above and below the central maximum. When n is even, more complicated patterns are generated, with m and m-1 loops above and below the central RW, respectively. Finally, we compute an additional solution class on a wavy background, defined by the Jacobi elliptic dnoidal function, which displays specific intensity patterns that are consistent with the background wavy perturbation. This work demonstrates an incredible power of the DT scheme in creating new solutions of the NLSE and a tremendous richness in form and function of those solutions.

HydraMarker: Efficient, Flexible, and Multifold Marker Field Generation.

An n-order marker field is a special binary matrix whose n×n subregions are all distinct from each other in four orientations. It is commonly used to guide the composing process of position-sensing markers, which can be detected and identified in a camera image with very limited scope or severe visibility problems. Despite the advantages, position-sensing markers are rare and overlooked because generating marker fields is difficult. In this article, we broaden the definition of marker field, making it more powerful and flexible. Then, we propose bWFC (binary wave function collapse) and its high-speed version, fast-bWFC, to solve the generation problem. The methods are packaged into an open-sourced toolkit named HydraMarker, with which, users not only can generate marker fields on laptops within a short period of time, but also can highly customize them: preset values; fields and subregions in any shape; multifold local uniqueness. Comparative results indicate that the proposed method has superior efficiency, quality, and capability. It makes marker field generation accessible to common marker designers, opening up more possibilities for fiducial markers.

SARS-CoV-2 Serology Across Scales: A Framework for Unbiased Estimation of Cumulative Incidence Incorporating Antibody Kinetics and Epidemic Recency.

Serosurveys are a key resource for measuring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) population exposure. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce estimates of cumulative incidence from raw seroprevalence survey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a postinfection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce estimates of cumulative incidence from 5 large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identified substantial differences between raw seroprevalence and cumulative incidence of over 2-fold in the results of some surveys, and we provide a tool for practitioners to generate cumulative incidence estimates with preset or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.

Integrated intelligent tactile system for a humanoid robot

Tactile perception is the basis of human motion. Achieving artificial tactility is one of the challenges in the fields of smart robotics and artificial intelligence (AI), because touch emulation relies on high-performance pressure sensor arrays, signal reading, information processing, and feedback control. In this paper, we report an integrated intelligent tactile system (IITS) that is integrated with a humanoid robot to achieve human-like artificial tactile perception. The IITS is a closed-loop system that includes a multi-channel tactile sensing e-skin, a data acquisition and information processing chip, and a feedback control. With customized preset values of threshold pressures, the IITS-integrated robot can flexibly grasp various objects. The IITS has potential applications in the design of prosthetic hands, space manipulators, deep-sea exploration robots, and human-robot interactions.

Computed tomographic angular measurements using a bone-centered three-dimensional coordinate system are accurate in a femoral torsional deformity model and precise in clinical canine patients.

In small animal orthopedics, angular measurements in the canine femur are often applied in clinical patients with bone deformities and especially in complex and severe cases. Computed tomography (CT) has been shown to be more precise and accurate than two-dimensional radiography, and several methods are described. Measurement techniques evaluated in normal bones must prove accuracy in deformed bones in clinical settings. The goals of our study were to evaluate the accuracy of canine femoral torsion angle measurements in a femoral torsional deformity model and to test repeatability and reproducibility of canine femoral neck inclination, torsion, and varus angle measurements in CT datasets of dogs applying a CT-based technique using a three-dimensional (3D) bone-centered coordinate system. For precision testing, femoral torsion, femoral neck inclination, and femoral varus angles were measured in CT data of 68 canine hind limbs by two operators, and their results were compared. For accuracy testing, a femoral torsional deformity model was preset from 0° to +/-90° with a goniometer and scanned. Torsion angles were measured in the CT data and compared to the preset value. In the femoral torsion model, the Bland-Altman plots demonstrated a mean difference of 2.11°, and the Passing-Bablok analysis demonstrated a correlation between goniometer and CT-based measurements. In the clinical CT scans, intra- and interobserver agreement resulted in coefficients of variation for repeated measurements (%) between 1.99 and 8.26 for the femoral torsion, between 0.59 and 4.47 for the femoral neck inclination, and between 1.06 and 5.15 for the femoral varus angles. Evaluation of femoral malformations with torsional deformities is the target area of this technique. Further studies are required to assess its value in different types, degrees, and combinations of osseous deformities and to establish normal reference values and guidelines for corrective osteotomies. Based on the results of this study, the accuracy of the torsion angle measurements and the precision of inclination, torsion, and the varus angle measurements were considered acceptable for clinical application.

Icing detection method of 500 kV overhead ground wire with tangent tower under special terrain based on vertical tension measurement technology

The operation reliability of the power grid and the stability of social production are seriously threatened by the icing of the overhead line. The equivalent ice thickness (EIT) is to convert different densities and shapes of ice into the uniform annular ice with density of 0.9 g/cm3. Although many methods for calculating EIT of transmission line conductors have been proposed, there are lack an effective monitoring method of EIT for 500 kV ground wire with tangent tower under the special terrain where “the virtual lowest point” of the ground wire appears in the condition of large height difference. Therefore, a calculation method of EIT for 500 kV ground wire with tangent tower under the special terrain based on vertical tension measurement technology is proposed. That is the iterative method is used to preset different EITs. Then the calculated vertical tension under the preset values are solved by the established ground wire state equation and vertical tension equation. The EIT can be obtained when the calculated vertical tension is equal to the measured vertical tension. The comparison between the artificial observed EIT and the calculated EIT is carried out for two practical cases of 500 kV ground wire in the mountainous area of southern China. The results show that the absolute error is less than 2 mm, which verify the two values are in strong agreement. The corresponding finite element simulation models are established. A comparative study between the simulated EIT and the calculated EIT is carried out. The results show that the relative error is less than ±10% under severe icing from 10 mm to 30 mm and the absolute error is less than 1 mm under mild icing of 5 mm, which verify the two values are highly consistent. Finally, the application effect of this method in practical cases is analyzed.

Effect of Laser-Textured Surface of Ti6Al4V on Frictional Wear Behavior

The need for titanium and its alloys has led to a significant increase in commercial manufacturing, although this material’s poor tribological qualities have been a drawback. The present study was to determine the effect of laser-textured surfaces to enhance Ti6Al4V surface wear performance. The sample underwent laser texturing based on pre-set parameter values at 15 W power at a laser scanning speed of 200 mm/s with a frequency of 50 kHz. The surface morphological and topological profile of laser-textured Ti6Al4V was characterized with also the surface microhardness. A comparative appraisal of wear rate (WR) and coefficient of friction (COF) for related samples of as-received Ti6Al4V and laser-textured Ti6Al4V was performed under dry and oil sliding conditions. The results revealed that the formation of oxidation due to the frictional force and plastic displacement plays a role of abrasive to the laser-textured surface and may result in increasing the COF. The wear rate of the laser-textured surface of Ti6Al4V exhibited 88.31% improvement compared to the as-received Ti6Al4V in the dry sliding wear test. It was proved that Ti6Al4V could benefit from LST to gain effectively enhanced wear performance.

Design and Development of a Maximum Demand Controller for Energy Efficiency in a Smart Home Environment

Nowadays, number of energy efficiency measures are being implemented in the smart home environment to conserve the energy consumption. This research attempts to design and develop a solution for an effective energy consumption in a smart home environment. The microcontroller system monitors the electrical energy consumption in real time and to ensure the power consumption is within the limit or predefined maximum demand value. Once the real time power consumption reaches the pre-set value prior to reaching its maximum demand, there will be an alarm triggered to warn the user that the power consumption is about to reach the predefined value. Once the power consumption exceeds the predefined maximum demand, the connected load will be automatically switched off sequentially one by one based on the pre-planned look up table. Results obtained through simulation and practical are presented in this paper. Recommendations are given for further enhancement of the proposed design for the smart home applications.

Coordinated emergency control strategy of high‐voltage direct current transmission and energy storage system based on Pontryagin minimum principle for enhancing power system frequency stability

AbstractWith the increase of the proportion of renewable energy sources, the rotational inertia of the power system decreases, which results in the risk of frequency instability increasing. Based on Pontryagin minimum principle, this paper presents a systematic emergency control strategy by coordinating the active power of voltage source converter based high‐voltage direct current transmission (VSC‐HVDC) and energy storage system (ESS) to improve the system frequency stability, reduce the operation cost of VSC‐HVDC and ESS and implement energy management of ESS. In the stage of frequency fall, a hierarchical control strategy is proposed to prevent the frequency from dropping below the preset threshold value and achieve the optimal distribution of support power between VSC‐HVDC and ESS. For the system level, the total optimal power support trajectory of VSC‐HVDC and ESS is optimized by the Gaussian pseudospectral method with the minimum total control energy, considering the constraints of frequency. For the station level, the power references of VSC‐HVDC/ESS are determined by the model predictive controller (MPC), with the minimum frequency deviation of the non‐disturbed system connected to VSC‐HVDC, control cost of VSC‐HVDC and loss cost of ESS. In the stage of frequency recovery, an energy recovery control strategy is designed to aim at quickly recovering energy of ESS while considering the minimum frequency limit. Finally, the correctness and effectiveness of the proposed strategy are verified in the improved IEEE 39 bus system and a real‐power system.

Minimum Dynamic Cable Tension Workspace Generation Techniques and Cable Tension Sensitivity Analysis Methods for Cable-Suspended Gangue-Sorting Robots

The separation of gangues from coals with robots is an effective and practicable means. Therefore, a cable-suspended gangue-sorting robot (CSGSR) with an end-grab was developed in our early work. Due to the unidirectional characteristic, the flexibility of cables, and the dynamic impact of pick-and-place gangues, one of the significant issues with the robots is robustness under internal and external disturbances. Cable tensions, being the end-grab’s constraints, have a crucial effect on the robustness of the CSGSR while disturbances are on. Two main issues related to the CSGSR, as a result, are addressed in the present paper: minimum dynamic cable tension workspace generation and a sensitivity analysis method for the dynamic cable tensions. Firstly, the four cable tensions and minimum dynamic cable tension while the end-grab was located at an arbitrary position of the task space were obtained with the dynamics of the CSGSR. In addition, with the dynamics of the CSGSR, a minimum dynamic cable tension workspace (MDCTW) generating approach is presented, where the minimum dynamic cable tensions are greater than a preset value, therefore ensuring the robustness of the end-grab under the disturbances. Secondly, a method for dynamic cable tension sensitivity (DCTS) of the robots is proposed with grey relational analysis, by which the influence degree of the end-grab’s positions on the four dynamic cable tensions and the minimum dynamic cable tensions was considered. Finally, the effectiveness of the proposed MDCTW generation algorithm and the DCTS analysis method were examined through simulation on the CSGSR, and it was indicated that the proposed MDCTW generation algorithm and the DCTS analysis method were able to provide theoretical guidance for pick-and-place trajectory planning and generation of the end-grab in practice.