Closed-loop System Research Articles

Pole placement tuning of proportional integral derivative feedback controller for knee extension model

Functional electrical stimulation (FES) has shown potential in rehabilitative exercises for patients recovering from spinal cord injuries. In recent developments, conventional open-loop FES control techniques have evolved into closed-loop systems that employ feedback controllers for automation. However, closed-loop FES systems often face challenges due to muscle non-linear effects, such as fatigue, time delays, stiffness, and spasticity. Therefore, an accurate non-linear knee model is required during the design stage, and precise tuning of the feedback controller parameters is vital. A proportional– integral–derivative (PID) controller is commonly used as a feedback controller due to its simplicity and ease of implementation. However, most PID tuning methods are complex and time consuming. This paper investigates the viability of employing the pole placement technique for tuning a PID controller that regulates the non-linear knee extension model. The pole placement method aims to improve the control and adaptability of the PID controller in closed-loop FES systems, specifically by facilitating knee extension exercises. MATLAB Simulink was used to assess the effectiveness of this tuning approach. Results showed that the PID controller performed satisfactorily without non-linearities, but performance varied with the inclusion of specific non-linearities. The pole placement tuning method facilitated preliminary assessments of PID controller performance, preceding highly advanced optimization.

Robust optimal control for uncertain wheeled mobile robot based on reinforcement learning: ADP approach

This paper presents a robust optimal control approach for the wheel mobile robot system, which considers the effects of external disturbances, uncertainties, and wheel slipping. The proposed method utilizes an adaptive dynamic programming (ADP) technique in conjunction with a disturbance observer. Initially, the system's state space model is formulated through the utilization of kinematic and dynamic models. Subsequently, the ADP method is employed to establish an online adaptive optimal controller, which solely relies on a single neural network for the purpose of function approximation. The utilization of the disturbance observer in conjunction with the compensation controller serves to alleviate the effects of disturbances. The Lyapunov theorem establishes the stability of the complete closed-loop system and the convergence of the weights of the neural network. The proposed approach has been shown to be effective through simulation under the effect of the disturbances and the change of the desired trajectory.

Design and construction of chemical-biological module clusters for degradation and assimilation of poly(ethylene terephthalate) waste

The rising accumulation of poly(ethylene terephthalate) (PET) waste presents an urgent ecological challenge, necessitating an efficient and economical treatment technology. Here, we developed chemical-biological module clusters that perform chemical pretreatment, enzymatic degradation, and microbial assimilation for the large-scale treatment of PET waste. This module cluster included (i) a chemical pretreatment that involves incorporating polycaprolactone (PCL) at a weight ratio of 2% (PET:PCL = 98:2) into PET via mechanical blending, which effectively reduces the crystallinity and enhances degradation; (ii) enzymatic degradation using Thermobifida fusca cutinase variant (4Mz), that achieves complete degradation of pretreated PET at 300 g/L PET, with an enzymatic loading of 1 mg protein per gram of PET; and (iii) microbial assimilation, where Rhodococcus jostii RHA1 metabolizes the degradation products, assimilating each monomer at a rate above 90%. A comparative life cycle assessment demonstrated that the carbon emissions from our module clusters (0.25 kg CO2-eq/kg PET) are lower than those from other established approaches. This study pioneers a closed-loop system that seamlessly incorporates pretreatment, degradation, and assimilation processes, thus mitigating the environmental impacts of PET waste and propelling the development of a circular PET economy.

Insulin Requirements According to Sex and Weight in a Population of 9036 Adult Persons With Type 1 Diabetes Using Closed-Loop Insulin Delivery.

The prediction of the individual insulin needs may facilitate the initiation of insulin therapy. Our aim was to explore the relationships between body weight, sex, and daily amounts of insulin delivered by a hybrid closed-loop system. We performed a retrospective data collection of all consenting adult patients with type 1 diabetes who were equipped in Europe with the Diabeloop Generation 1 (DBLG1) hybrid closed-loop insulin delivery device between March 1, 2021 and February 28, 2023. A total of 9036 users (59% females, age 45.6 ± 14.3 years) were included, reaching a mean follow-up of 320 ± 143 days, an overall 2 887 188 days of data. We observed a mean insulin-weight ratio of 0.617 ± 0.207 U/kg (0.665 ± 0.217 for males and 0.584 ± 0.193 for females, P < .001). Exploratory analysis of a subset of 4066 patients reaching >70% Time in Range (70-180 mg/dL) showed a mean insulin-weight ratio of 0.55 ± 0.17 U/kg (P < .001) (0.59 ± 0.18 for the 1438 males and 0.53 ± 0.16 for the 2628 females). This large real-world analysis provides a quantitative estimation of the daily insulin requirements in adult patients with type 1 diabetes and shows significant differences between sex. These findings have relevant implications in the practical management of insulin therapy.

An adaptive backstepping control strategy based on radial basis function neural networks for the magnetorheological semi-active suspension

Owing to nonlinear issues such as external disturbances and uncertain parameters within the semi-active suspension system (SASS), the vibration amplitude of the suspension system tends to increase, and the time required for the suspension system to reach a steady-state response is prolonged. Hence, this paper proposes an adaptive backstepping control strategy based on radial basis function neural networks (RBF-NNs). Firstly, the damping force characteristics of the magnetorheological (MR) damper are tested, and the experimental data are utilized for parameters identification and fitting of the Bouc-Wen model. To establish a connection between the controller and the forward model of the MR damper, the forward model of the MR damper, the inverse model of the MR damper, and the model of the MR-SASS are constructed. Secondly, the backstepping controller and the adaptive backstepping controller based on RBF-NNs are designed. The stability and reliability of the closed-loop suspension system are verified through stability analysis using Lyapunov function. Finally, the dynamic characteristics of the passive control, backstepping control, and adaptive backstepping control strategies based on RBF-NNs applied to MR-SASS are analyzed under B-Class road excitation and speed bump road excitation. The acceleration, suspension dynamic deflection, and tire dynamic load are selected as the evaluation indices. The results demonstrate that the adaptive backstepping controller based on RBF-NNs significantly enhances the ride comfort of the SASS.

Transforming abandoned petroleum wells in the Nigerian sector of the Chad basin into triplet borehole heat exchangers for sustainable power generation

This study pioneers a transformative approach to sustainable energy recovery, repurposing abandoned petroleum wells in the Nigerian Chad Basin as a triplet-deep closed-loop heat exchanger. We employed a computational numerical approach to designed two deep closed loop systems, which share a common production well, and to evaluate the thermal performance as well as its sustainability over a period of 25 years. The geometrical configuration consists of two injection wells, which converge to the common production one doubling the flow rate at surface and minimising the heat loss during the ascent of the fluid. The availability of detailed abandoned well specifications enabled us to constrain three-dimensional geological and thermal models of the undisturbed underground and, subsequently, to simulate numerically the production temperature and the thermal disturbance in the surrounding rocks. A comprehensive sensitivity analysis optimized the best operational design for total recovered thermal energy and uninterrupted heat recovery. When the deep close loop heat system operates with a fluid circulation rate of 0.03 m³s⁻1 and an injection temperature of 20 °C, it sustains a production temperature of over 100 °C, which generates total recovered thermal energy of 9730 TWth and 817 TWe over 25 years (9000 days). The average annual thermal and electricity productions of 389 TWth and 33 TWe, respectively, are more than the demand of the entire population of Magumeri district. The study's findings offer practical implications for policymakers, industry stakeholders, and local communities, emphasising the potential for socio-economic development while fostering environmental stewardship in the Nigerian Chad Basin.

Expected performance of the Pyramid wavefront sensor with a laser guide star for 40 m class telescopes

Context. The use of artificial laser guide stars (LGS) is planned for the new generation of giant segmented mirror telescopes in order to extend the sky coverage of their adaptive optics systems. The LGS, being a 3D object at a finite distance, will have a large elongation that will affect its use with the Shack–Hartmann (SH) wavefront sensor. Aims. In this paper, we compute the expected performance for a Pyramid WaveFront Sensor (PWFS) using an LGS for a 40 m telescope affected by photon noise, and also extend the analysis to a flat 2D object as reference. Methods. We developed a new way to discretize the LGS, and a new, faster method of propagating the light for any Fourier filtering wavefront sensors (FFWFS) when using extended objects. We present the use of a sensitivity model to predict the performance of a closed-loop adaptive optic system. We optimized a point-source-calibrated interaction matrix to accommodate the signal of an extended object by computing optical gains using a convolutional model. Results. We find that the sensitivity drop, given the size of the extended laser source, is large enough to make the system operate in a low-performance regime given the expected return flux of the LGS. The width of the laser beam is identified as the limiting factor, rather than the thickness of the sodium layer. Even an ideal, flat LGS will have a drop in performance due to the flux of the LGS, and small variations in the return flux will result in large variations in performance. Conclusions. We conclude that knife-edge-like wavefront sensors, such as the PWFS, are not recommended for use with LGS for a 40 m telescope, as they will operate in a low-performance regime, given the size of the extended object.

Closed-loop insulin delivery systems in patients with pancreatitis or pancreatectomy-induced diabetes: A case series

Pancreatic diabetes is associated with glycemic variability, poor metabolic control, and reduced quality of life. Though hybrid closed-loop (HCL) insulin delivery systems were not originally developed for these types of diabetes, they could address the therapeutic challenge. We aimed to evaluate long-term metabolic control in ten adult patients (mean ± SD age: 59 ± 12) treated with HCL insulin delivery systems for pancreatitis or pancreatectomy-induced diabetes. After a median of 346 days (range 64 - 631) with HCL insulin delivery, continuous glucose monitoring showed 59±19 % time-in-range [70–180 mg/dl] (versus 49±24 % before HCL insulin delivery, P = 0. 049) and 0.8 ± 1.0 % time-below-range [< 70 mg/dl] (versus 2.2 ± 2.6 %, P = 0.142), with the coefficient of glucose variability at 35.4 ± 7.6 (versus 37.8 ± 7.1, P = 0.047). HbA1c decreased from 8.5 ± 1.7 % to 7.7 ± 1.3 % [69±18 to 60±14 mmol/mol] (P = 0.076). No patient experienced an acute adverse metabolic event.

Repolarization dynamics stability in Brugada type-1 pattern subjects with positive and negative genetics

Abstract Background Brugada type-1 pattern (Brgd1) risk stratification in asymptomatic subjects and its repolarization dynamics are complex. Purpose This study aims to analyze, from alternative standpoints, superficial 12-lead ECG V1 repolarization patterns (repol.). This method diverges from standard ECG pattern characterization. It rather exploits nonlinear dynamics and stability of ECG repol. to assess stability driving cardiac dynamics. This work consists in analyzing 2 subjects with Brgd1: Subject1 with negative genetics and negative EP study. Subect2 with positive genetics. Target To deepen knowledge/insight and applications of control-and-stability-theory applied to 12-lead ECG, aiming to eventually diminish the number of invasive EP studies. Methods A stability control closed loop system has been designed to model electrophysiology dynamics of cardiac conduction: ECG segments being the input-output of the system. (Figure). A sequence of V1 repol. have been scanned, digitized, and quantitatively processed yielding stability parameters (poles in S-plane). Scanning and signal processing performed by Matlab R_2023b. Results Figures. Conclusions Based on our data, 12-lead-ECG repol. seem to be associated with increasing stability in Subject1, exhibiting negative genetics. On the other hand, less stability seems to be associated with Subject2, reporting positive genetic tests. In conclusion, furthering control-and-stability-theory applied to 12-lead ECGs aims to deeper comprehension of physiological and pathological substrates of malignant arrhythmias, and to focus on noninvasive risk stratification strategies for ICD implantation indication in BrS. Further development of this technique will be largely facilitated by the implementation of AI methodologies in the near future.

Automated continuous rhythm monitoring with implantable cardiac monitor and real-time smartphone alerts during af episodes: SMART-ALERT study

Abstract Introduction The 'Pill-in-the-pocket' oral anticoagulation (OAC) strategy is based upon the concept of dynamic thromboembolic risk which increases during and shortly after an atrial fibrillation (AF) episode. Limiting OAC use in low-risk patients with infrequent AF may offer comparable stroke protection and reduce bleeding. However, this approach relies on precise continuous rhythm monitoring with real-time alerts to patients. LINQ II implantable cardiac monitor transmits regularly to Carelink via smartphone app, but lacks patient alerts. To address this limitation, we developed bespoke software that triages transmissions in Carelink and sends alerts via SMS to patients. Purpose This feasibility study evaluates the precision of the LINQ II in detecting AF and assesses the efficacy of bespoke software in delivering 'real-time' SMS alerts to participants' smartphones, and measures compliance with these alerts. Methods In this single-center feasibility study, individuals with frequent AF episodes underwent LINQII implantation. The bespoke software, operating in the cloud, systematically reviewed all Carelink transmissions at 5-min intervals. SMS alerts were triggered based on specific criteria: 1)AF &amp;gt;30 min; 2)only the initial AF episode &amp;gt;30 min within a 24h period was transmitted; and 3)AF episodes uploaded or detected after a 24h delay were disregarded. Participants confirmed receipt of the alert by responding to the SMS, and timestamps for these interactions were recorded in a database (Fig. 1). Results A total of 50 patients were prospectively enrolled, and LINQ II was implanted. The median age was 49 years, 62% male, 90% had paroxysmal AF. Over a 3-month mean follow-up, 4080 AF episodes &amp;gt;30 min occurred in 32 patients. Among these, 700 met the criteria for triggering an alert, with 72.14% sent to patients within 24 h. Alerts were not transmitted for 3 main reasons: smartphone failure to transmit to Carelink within a 24 h period, software issues connecting to Carelink (website maintenance), and updates in the webservers. The median time from an AF episode to the transmission of SMS alerts was 2.47 h, with 85.54% of alerts being sent within 12 hours. Once an SMS was sent, the median time for acknowledgment was 4.3 min. The median time from an AF episode to acknowledgment was 4.23 h (Fig. 2). Notably, 97.62% of episodes were acknowledged within 24 hours. Patients failed to acknowledge an SMS alert on only 3 occasions. Conclusions Safely delivering 'pill-in-the-pocket' OAC requires a closed-loop system where devices provide real-time alerts during during AF , thus minimising delays in initiating OAC. This feasibility study establishes that the integration of bespoke software with LINQ II exhibits promising efficacy with a high percentage of SMS alerts within 24 hours, exceptional patient compliance, and a median response time of only 4.3 min. Nonetheless, further efforts are needed for seamless integration with Carelink to enhance connectivity.

A robust, low-temperature, closed-loop anaerobic system for high-solid mixed farm wastes: advancing agricultural waste management solutions in Canada.

This study investigates the effectiveness of low-temperature (20 ± 1 °C) anaerobic digestion (AD) for two organic multiple farm substrate combinations: Set 1 comprising chicken manure (CM), dairy manure (DM), and waste corn silage (CS) and Set 2 comprising CM, DM, pig manure (PM), and CS. Inoculum adaptation steps were carried out using CM and CM+DM for Set 1 and Set 2, respectively. Over three consecutive operating cycles spanning 245 days with increasing organic loads, 4.3 and 2.8 g VS L-1 d-1 for Sets 1 and 2 during Cycles 1 to 5.1 and 4.6 g VS L-1 d-1for Sets 1 and 2 during Cycle 3, a closed-loop two-stage liquid-solid AD system was employed, with performance assessed via stability ratios of short-chain volatile fatty acids and alkalinity. Results demonstrate that mono-digestion of CM with adapted inoculum yielded the highest biogas production of 424 ± 4 L over 77 days, indicating superior performance by Set 1 during Phase I, whereas a similar performance was observed during Phase 2, where Sets 1 and 2 exhibited highest specific methane yields of 0.233 ± 0.028 and 0.262 ± 0.004 L g-1 VSfed, respectively, over 68 days. Analysis of heavy metal concentrations in digestates revealed a significant decrease compared to initial raw substrate concentrations, highlighting their role as nutrients for microbial growth. This study, the first of its kind, highlights the potential of low-temperature AD systems to manage diverse organic residues/byproducts and offers insights into effective performance monitoring without compromising system integrity.

Position Feedback-Control of an Electrothermal Microactuator Using Resistivity Self-Sensing Technique

The self-sensing technology of microactuators utilizes a smart material to concurrently actuate and sense in a closed-loop control system. This work aimed to develop a position feedback-control system of nickel electrothermal microactuators using a resistivity self-sensing technique. The system utilizes the change in heating/sensing elements’ resistance, due to the Joule heat, as the control parameter. Using this technique, the heating/sensing elements would concurrently sense and actuate in a closed loop control making the structures of microactuators simple. From a series of experiments, the proposed self-sensing feedback control system was successfully demonstrated. The tip’s displacement error was smaller than 3 µm out of the displacement span of 60 µm. In addition, the system was less sensitive to the abrupt temperature change in surroundings as it was able to displace the microactuator’s tip back to the desired position within 5 s, which was much faster than a feed-forward control system.

Neural adaptive dynamic surface control for position tracking of electrohydraulic servo systems based on extended state observer

High-performance motion tracking of electro-hydraulic servo systems plays an important role in developing industrial technology. However, the system itself has parameter uncertainty, uncertain nonlinearity, and measurement noise, significantly decreasing the performance of conventional controllers designed based on nominal models. To improve the tracking performance of electro-hydraulic servo systems, an adaptive dynamic surface control method combining extended state observer and radial basis function neural network is proposed. Firstly, an extended state observer combining neural network output and parameter adaptation technology is designed without the need for speed and pressure feedback to observe the system’s unknown state variables and nonlinear matched disturbance. The design of neural networks is used to approximate mismatched disturbance with significant nonlinearity online. Then, the proposed extended state observer is introduced into the neural adaptive backstepping design, effectively compensating for simultaneous matched and mismatched disturbances, thereby suppressing most of the uncertain nonlinearity of the system. Meanwhile, online update of uncertain parameters further improves the tracking performance of the controller. In addition, the introduction of dynamic surface overcomes the “explosion of complexity” issue in backstepping design. The rigorous stability of the closed-loop system is proved by the Lyapunov stability theory. Finally, the effectiveness of the proposed controller is validated through comparative experiments on valve-controlled hydraulic cylinder.

Performance-Based Hierarchical Fault-Tolerant Control for Closed-Loop Systems With Multiplicative Faults: A Data-Driven Design Method.

Fault-tolerant control (FTC) is vital for the safety and reliability of automatic systems. Most of the existing FTC methods are developed for open-loop systems subject to additive faults, regardless of the widely present control loops and multiplicative faults within systems. In this article, a performance-based FTC strategy is proposed for the closed-loop systems with multiplicative faults. Considering the high efforts in modeling complex systems, the proposed FTC strategy is realized in the data-driven context. Specifically, a nominal feedback-feedforward controller is first established for the fault-free systems. By selecting the system stability and reference tracking behavior as the key performance indices, two performance evaluators are constructed to detect and classify the occurred multiplicative faults based on the fault-induced effects on the system performance. Then, with the aid of the coprime factorization technique, the multiplicative faults, in the form of additive perturbations to the system coprime factors, are estimated utilizing the closed-loop process data. Furthermore, based on the fault knowledge, a hierarchical fault-tolerant tracking controller is developed according to the levels of system performance degradations, where the functional controller parameters are reconfigured with different priorities. Finally, case studies are provided to validate the effectiveness of the proposed method.

Model Predictive Control With Guaranteed Feasibility of Inequality Path Constraints.

This article concerns nonlinear model predictive control (MPC) with guaranteed feasibility of inequality path constraints (PCs). For MPC with PCs, the existing methods, such as direct multiple shooting, cannot guarantee feasibility of PCs because the PCs are enforced at finitely many time points only. Therefore, this article presents a novel MPC framework that is capable of not only achieving stability control but also guaranteeing feasibility of PCs during the rolling optimization stages of MPC. Under the above MPC framework, an algorithm is first proposed by applying the semi-infinite programming technique to the rolling optimization of MPC. However, it takes heavy computational time to achieve guaranteed feasibility of PCs. Therefore, to guarantee feasibility of PCs meanwhile effectively reducing the computation burden of the closed-loop system, an event-triggered sampling mechanism is constructed in the above path-constrained MPC algorithm. Moreover, sufficient conditions are given for asymptotic convergence of the closed-loop systems. Finally, the effectiveness of the proposed results is illustrated via a cart-damper-spring system.

A Proposal for a Solar Position Sensor System with Multifiber Optical Cable

A solar position sensor is an essential optoelectronic device used to monitor the sun’s position in solar tracking systems. In closed-loop systems, this sensor is responsible for providing feedback signals to the control system, allowing motor adjustments to optimize the angle of incidence and minimize positioning errors. The accuracy required for solar tracking systems varies depending on the specific photovoltaic concentration. In the case of the concentrator photovoltaic (CPV), it is normally essential to track the sun with a position error of less than ±0.6°. To achieve such precision, a proposed sensor configuration composed of low-cost embedded electronics and multifiber optical cable is subjected to characterization through a series of measurements covering range, sensitivity, and resolution. These measurements are performed in controlled indoor environments as well as outdoor conditions. The results obtained exhibit a resolution of 2.6×10−3 degrees when the sensor is illuminated within its designated field of view of ±0.1°, particularly in external conditions. Considering the performance demonstrated by the proposed solar position sensor, coupled with its straightforward modeling and assembly compared to position sensors documented in the literature, it emerges as a promising candidate for integration into solar tracking systems.

Efficacy and safety of advanced hybrid closed loop systems in children with type 1 diabetes younger than 6 years

BackgroundTight glycemic control is essential for the normal growth and development of preschool children. The aim of our study was to evaluate the impact of advanced hybrid closed loop (AHCL) systems in a real-life setting in children younger than 6 years.MethodsWe conducted a two-center prospective study. We enrolled 19 patients with a median age at disease onset of 2.6 years [interquartile range (IQR) 1.6; 4.4] and a median disease duration of 1.4 years (IQR 0.9; 2.8) who were switched to AHCL from multiple daily injections or open-loop insulin therapy and with a 6-month follow-up. Clinical data, sensor glycemic metrics, and pump settings were collected and analyzed.ResultsAfter 6 months of follow-up, there was a significant reduction in median HbA1c (p = 0.0007) and glucose management indicator (p = 0.03). A reduction in both mild (&amp;gt;180 mg/dL) (p = 0.04) and severe (&amp;gt;250 mg/dL) (p = 0.01) hyperglycemia was observed after 1 month of auto mode, and in mild hyperglycemia, it persisted up to 6 months (p = 0.02). A small increase in time below range (&amp;lt;70 mg/dL) was observed (p = 0.04) without a significant difference in time &amp;lt;54 mg/dL (p = 0.73). Time in range increased significantly, reaching a 10% increment (p = 0.03) compared with baseline. A significant reduction in the average sensor glucose was observed (p = 0.01) while coefficient of glucose variability (CV%) remained stable (p = 0.12). No episodes of ketoacidosis or severe hypoglycemia have been recorded.ConclusionAHCL systems are effective and safe for children younger than 6 years and should be considered as a valid therapeutic option from diabetes onset.

Asymptotic adaptive output-feedback stabilisation of nonlinear systems with unknown growth rate and sensor uncertainty

For a class of nonlinear systems with sensor uncertainty, the problem of adaptive output feedback stabilisation is investigated in this paper. It is assumed that only the output is available for feedback control, which suffers from sensor uncertainty. At the same time, the nonlinear function in the system model has an unknown growth rate. To solve this problem, a set of state observers is designed to estimate the unknown system states based on the uncertain output, and an adaptive output-feedback control is designed based on this. By using the corollary of Barbalet's Lemma, it is shown that the equilibrium of the closed-loop system is asymptotically stable. Finally, simulation results verify the effectiveness of the control scheme

Fuzzy control for networked systems with mixed data missing under quantization based event-triggered scheme

This paper presents an innovative event-triggered fuzzy control approach for networked systems operating over unreliable network channels. Traditional complicated modeling and analysis process of network induced issues is replaced by a bran-new logarithmic quantization based event-triggered scheme method. The joint characterization of mixed data missing, arising from the event-triggered mechanism and unreliable network channels, becomes a challenging issue due to disrupted data sequences and variable relations. Consequently, this paper contributes a formulated auxiliary stochastic sequence approach to overcome the difficulty of dynamics modeling. With an formulated event driven controller, the modeling and implementation of the closed-loop systems are constructed and further simplified. Considering the difference and relation between the membership functions of plant and controller, we present a new fuzzy output feedback controller design method to obtain feasible result via uncertainty based method. Finally, we verify the validity of the designed control policy via a simulation example.

Input-to-state stability of impulsive switched systems under mode-dependent event-triggered impulsive control

This paper aims to investigate input-to-state stability (ISS) of nonlinear impulsive switched systems under mode-dependent event-triggered impulsive control (MDETIC) method. A novel mode-dependent event-triggered mechanism (MDETM) is devised, where triggering impulsive instants are determined by some predesigned event conditions. Different from existing MDETM, there are two types of impulsive behavior involved, including the impulsive behavior of system itself and event-triggered one. The novel MDETM not only reduces communication cost and energy consumption but also excludes “Zeno behavior.” Then, the ISS criteria of the closed-loop system are established based on MDETIC strategy, admissible edge-dependent average dwell time (AED-ADT), and admissible edge-dependent average impulsive interval (AED-AII) methods. Finally, two examples are given to verify the effectiveness of the main results.