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Transportation problems have always been a global concern. The challenges in traffic congestion were easily observed during pre-pandemic times. However, traffic congestion still persists even during the COVID-19 pandemic (2020 and present) where there has been less number of vehicles because of travel restrictions. The emergence of wireless communication technologies and intelligent transportation systems (ITS) pave the way for solving some of the problems found in the transportation industry. Subsequently, traffic control systems are used at various intersections to manage the flow of traffic and reduce car collisions. However, some intersections are better off without these traffic control systems. The proposed study will analyze a T-junction road in five different setups using different types of traffic controllers. The simulation tool used is SUMO. The study found that an adaptive or vehicle-actuated traffic controller is the ideal method for regulating traffic flow in a T-junction with a one-way or two-way main road. It was observed in the simulation that it reduced the potential car collisions in the non-TL junction. However, the average speed and completion time of the road network was affected by the method. © 2022 IEEE.
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There are many inevitable disruptive events, such as the COVID-19 pandemic, natural disasters and geopolitical conflicts, during the operation of the container port supply chain (CPSC). These events bring ship delays, port congestion and turnover inefficiency. In order to enhance the resilience of the CPSC, a modified two-stage CPSC system containing a container pretreatment system (CPS) and a container handling system (CHS) is built. A two-dimensional resilience index is designed to measure its affordability and recovery. An adaptive fuzzy double-feedback adjustment (AFDA) strategy is proposed to mitigate the disruptive effects and regulate its dynamicity. The AFDA strategy consists of the first-level fuzzy logic control system and the second-level adaptive fuzzy adjustment system. Simulations show the AFDA strategy outperforms the original system, PID, and two pipelines for improved dynamic response and augmented resilience. This study effectively supports the operations manager in determining the proper control policies and resilience management with respect to indeterminate container waiting delay and allocation delay due to disruptive effects.
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This study presents a new auto-tuning nonlinear PID controller for a nonlinear electric vehicle (EV) model. The purpose of the proposed control was to achieve two aims. The first aim was to enhance the dynamic performance of the EV regarding internal and external disturbances. The second aim was to minimize the power consumption of the EV. To ensure that these aims were achieved, two famous controllers were implemented. The first was the PID controller based on the COVID-19 optimization. The second was the nonlinear PID (NPID) optimized controller, also using the COVID-19 optimization. Several driving cycles were executed to compare their dynamic performance and the power consumption. The results showed that the auto-tuning NPID had a smooth dynamic response, with a minimum rise and settling time compared to other control techniques (PID and NPID controllers). Moreover, it achieved low continuous power consumption throughout the driving cycles. © 2023 by the author.
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PurposeThis study aims to explore the effect of power-based behaviours on pharmaceutical supply chain (PSC) resilience.Design/methodology/approachThis study used a mixed-method approach to explore the role of power-based behaviours in PSC resilience. Qualitative interviews from 23 key PSC stakeholders, followed by thematic analysis, revealed the underlying perceptions regarding PSC resilience. Quantitative propositions were then developed based on the themes adopted from PSC resilience literature and the qualitative findings. These were tested via a survey questionnaire administered to 106 key stakeholders across the various levels in the PSC. Structural equation modelling with partial least squares was used to analyse the data.FindingsThe data analysed identified proactive and reactive strategies as resilience strategies in the PSC. However, power-based behaviours represented by quota systems, information and price control influenced these resilience strategies. From a complex adaptive system (CAS) perspective, the authors found that when power-based behaviours were exhibited, the interactions between PSC actors were mixed. There was a negative influence on reactive strategies and a positive influence on proactive strategies. The analysis also showed that PSC complexities measured by stringent regulations, long lead times and complex production moderated the effect of power-based behaviour on reactive strategies. Thus, the negative impact of power-based behaviours on reactive strategies stemmed from PSC complexities.Research limitations/implicationsThis research particularly reveals the role of power-based behaviours in building PSC resilience. By evaluating the nexus from a CAS perspective, the analysis considered power-based behaviours and the moderating role of PSC complexities in developing resilience strategies. This study considers the interactions of PSC actors. This study shows that power asymmetry is a relational concept that inhibits the efficacy of reactive strategies. This study thus advocates the importance of power in achieving a more resilient PSC from a holistic perspective by highlighting the importance of the decision-making process among supply chain (SC) partners. The findings are particularly relevant if PSC resilience is viewed as a CAS. All the interactions and decision-making processes affect outcomes because of their inherent complexities. Although this study focused on the PSC, its implications could be extended to other SCs.Practical implicationsThe authors identified that power-based behaviours influenced resilience strategies. It was detrimental to reactive strategies because of the complexities of the PSC but beneficial to proactive strategies through resource-sharing. PSC actors are therefore encouraged to pursue proactive strategies as this may aid in mitigating the impact of disruptions. However, power-based behaviours bred partner dissatisfaction. This dissatisfaction may occur even within strategic alliances indicating that power could be detrimental to proactive strategies. Therefore, it is pertinent to identify conditions that lead to dissatisfaction when pursuing strategic partnerships. This study provides insight into actual behaviours influencing resilience and quantifies their effects on the PSC. These insights will be valuable for all SC partners wanting to improve their resilience strategies.Originality/valuePrevious PSC management and resilience studies have not examined the role of power in building resilience in the PSC. This paper thus provides a unique contribution by identifying the role of power in PSC resilience, offers empirical evidence and a novel theoretical perspective for future practice and research in building PSC resilience strategies.
ABSTRACT
On August 6 every year, the Hiroshima Peace Memorial Ceremony is com-memorated in Hiroshima, Japan, to comfort the spirits of the atomic bomb victims and pray for the realization of permanent world peace. However, because various political marches are conducted in and around the venue, demonstrators' voices disturb the cer-emony. Hiroshima City has repeatedly requested that demonstrators lower their volume and change the demonstration route. However, there has been no improvement in this regard. Since 2015, there has been a considerable decrease in demonstrators' disruptions owing to crowds and tents set up as sound barriers. Since 2020, the number of attendees has declined by 90% owing to the COVID-19 pandemic;thus, demonstrators' voices are easily heard in the venue. Previous studies applied active noise control, including high frequencies, to solving this problem. Implementing ANC is difficult because controlling high-frequency sounds in wide-open spaces is complex. In this study, we attempted to reduce demonstrators' noise by masking it with noise acceptable to the ceremony atten-dees in order to keep solemnity. Brown noise was found to be effective in the selection of masking noise. The experimental results confirmed the effective masking of male demon-strators. Therefore, we introduced adaptive masker control to mask all demonstrators and confirmed its effectiveness. © 2023, ICIC International. All rights reserved.
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This article presents the development of a ventilator and its control algorithm. The main feature of the developed ventilator is compressed by a pneumatic drive. The control algorithm is based on the adaptive fuzzy inference system (ANFIS), which integrates the principles of fuzzy logic. The paper also presents a simulation model to test the designed control approach. The results of the experiment provide verification of the developed control system. The novelty of the article is, on the one hand, the implementation of the ANFIS controller, pressure control, with a description of the training process. On the other hand, in the article presented a draft ventilator with a detailed description of the hardware and control system. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Chaotic states of abnormal vasospasms in blood vessels make heart patients more prone to severe infections of COVID-19, eventually leading to high fatalities. To understand the inherent dynamics of such abrupt vasospasms, an N-type blood vessel model (NBVM) subjected to uncertainties is derived in this paper and investigated both in integer order (IO) as well as fractional-order (FO) dynamics. Active-adaptive controllers are designed to synchronize the chaotic turbulence responsible for undesirable fluctuations in diameter and pressure variations of the blood vessel. The FO-NBVM reveals insightful rich dynamics and faster adaptive synchronization compared to its IO model. The practical implications of this work will be useful in analysing chaotic dysfunctionalities of the blood vessel such as vasoconstriction, ischaemia, necrosis, etc. and help in developing control strategies and modular responses for COVID-19 triggered heart diseases. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with coronavirus disease (COVID-19) limitations. This article presents a taxonomy and review of sensing technologies based on the Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus/tram stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICTs) in order to: 1) monitor and predict crowding events;2) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs);and 3) inform in real time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus/tram stops/stations and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as online ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning. © 2001-2012 IEEE.
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This paper presents a new combination between the Model Reference Adaptive Control (MRAC) with several types of PID's controllers (PID, Fractional order PID (FOPID), and Nonlinear PID (NPID)) optimized using a new Covid-19 algorithm. The proposed control techniques had been applied on a new model for an electric-wind vehicle, which can catch the wind that blows in the opposite direction of a moving vehicle to receive wind;a wind turbine is installed on the vehicle's front. The generator converts wind energy into electricity and stores it into a backup battery to switch it when the primary battery is empty. The simulation results prove that the new model of electric-wind vehicles will save power and allow the vehicle to continue moving while the other battery charges. In addition, a comparative study between different types of control algorithms had been developed and investigated to improve the vehicle dynamic response. The comparison shows that the MRAC with the NPID compensator can absorb the nonlinearity (air resistance and wheel friction) where it has a minimum overshoot, rise time, and settling time (35 seconds) among other control techniques compensators (PID and FOPID). © 2022 Department of Agribusiness, Universitas Muhammadiyah Yogyakarta. All Rights Reserved.
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Irrigation has traditionally been managed as uniform applications where an entire field receives the same depth of water. Motivation to improve current irrigation practices has led to different approaches utilizing remotely-sensed images to inform variable rate irrigation management. This study conducted in 2019 and 2020 implemented the Spatial EvapoTranspiration Modeling Interface (SETMI), a remote-sensing-based evapotranspiration (ET) and water balance model, for managing variable rate irrigation of a maize and soybean field. This model tracked soil water content through the estimation of daily ET and tracking of various water fluxes entering and leaving a field. SETMI was used in two different irrigation treatments informed using Planet satellite (SETMI-SAT) and unmanned aerial system (UAS, SETMI-UAS) remotely-sensed images. A uniform irrigation approach managed by a professional crop consultant and a non-irrigated approach were used as the baseline in comparing irrigation management approaches. The irrigation treatments were evaluated on dry grain yield, gross irrigation, actual ET, deep percolation, change in soil water content, and water productivity. The uniform irrigation approach managed by the crop consultant applied the highest irrigation in 2019 and 2020 for maize (2019: 155 mm, 2020: 213 mm) and soybean (2019: 124 mm;2020: 183 mm) while the SETMI irrigation treatments applied less irrigation for maize (2019: 131, 132 mm;2020: 154, 140 mm) and soybean (2019: 116, 94 mm;2020: 154, 175 mm). Maize yield was highest for the uniform irrigation approach in 2019 (14.9 Mg ha−1) and 2020 (13.3 Mg ha−1). The highest soybean yield was produced by the SETMI-SAT irrigation management approach in 2019 (5.0 Mg ha−1) and 2020 (4.8 Mg ha−1). Significant differences (p-value < 0.05) in applied irrigation between the uniform and SETMI irrigation management approaches were observed while there were no significant differences in dry grain yield for both maize and soybean in 2019 and 2020. At least one of the SETMI irrigation treatments produced higher crop, irrigation, and ET water productivity values in comparison to those produced by the uniform irrigation treatment for all crop-years. A post-season analysis was completed using the SETMI-UAS and SETMI-SAT treatments to evaluate the accuracy of estimated rootzone soil water depletion provided by SETMI. Rootzone depletion calculated from neutron probe volumetric soil water content measurements were compared to the modeled depletion from the SETMI-UAS and SETMI-SAT treatments. The 2020 modeled and measured depletion comparison produced better agreement resulting in a root mean squared error (RMSE) < 17 mm compared to 2019 (RMSE < 27 mm). The VRI center pivot malfunctioned during the 2019 season which caused unresolved discrepancies between actually applied irrigation and what the system was programmed to apply. The VRI system was fixed before the 2020 season. • Remotely-sensing-based evapotranspiration model can improve irrigation management. • Variable rate irrigation can be effective informed through remote sensing. • Variable rate irrigation can decrease applied irrigation while maintaining crop yields. [ FROM AUTHOR] Copyright of Agricultural Water Management is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
With the growing interest in web services during the current COVID-19 outbreak, the demand for high-quality low-latency interactive applications has never been more apparent. Yet, packet losses are inevitable over the Internet, since it is based on UDP. In this paper, we propose Ivory, a new real-world system framework designed to support network adaptive error control in real-time communications, such as VoIP, using a recently proposed low-latency streaming code. We design and implement our prototype over UDP that can correct or retransmit lost packets conditional on network conditions and application requirements.To maintain the highest quality, Ivory attempts to correct as many lost packets as possible on-the-fly, yet incurring the smallest footprint in terms of coding overhead over the network. To achieve such an objective, Ivory uses a deep reinforcement learning agent to estimate the best coding parameters in real-time based on observed network states and experience learned. It learns offline the best coding parameters to use based on previously observed loss patterns and takes into account the round-trip time observed to decide on the optimum decoding delay for a low-latency application. Our extensive array of experiments shows that Ivory achieves a better trade-off between recovering packets and using lower redundancy than the state-of-the-art network adaptive streaming codes algorithms. © 2022 IEEE.
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The coronavirus pandemic has challenged the operation of municipal solid waste management systems (MSWMSs) in the United States and elsewhere. With the growing concern about the potential exposure to the coronavirus, people are spending more time in their homes while changing their waste generation behaviors. This phenomenon has changed not only how people produce waste but also how MSWMSs plan and adapt the operation of their facilities. Since solid waste management has been declared as an essential service in addition to public health, MSWMSs have faced new challenges and thus developed adaptive measures in order to keep their critical operations. This study (i) identifies a broad range of waste management and operational challenges and (ii) summarizes various adaptive measures taken by different MSWMSs. Ephemeral data were collected and analyzed on the longitudinal impact of the pandemic on multiple MSWMSs in severely affected U.S. states, such as Florida, California, and New York, over a nine-month period. Note that best management practices for such waste-related challenges and adaptive measures can vary across different MSWMSs and states. In order to facilitate the development of different MSWMSs’ plan for future pandemic events, this study will characterize the identified impact of the pandemic and its relevant adaptive measures in terms of system structure (i.e., what facilities exist [entity], how they interact with one another [interdependency], and who control which facilities [control]). © 2023, Canadian Society for Civil Engineering.
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[...]the following 13 conference papers have been selected for publication in this peer-reviewed special issue: Topczewski S., Żugaj M.;Bibik P., “Impact of Actuators Backlash on the Helicopter Control During Landing on the Moving Vessel Deck” Kopecki G., “Aircraft Control With the Use of Model Reference Adaptive Control” Rodzewicz M., “Comparative fatigue properties estimation of composite structural nodes” Kowalski M., Goraj Z.;Goliszek B., “The use of FEA and semi-empirical equations for weight estimation of a passenger aircraft” Olejnik A., Dziubiński, A.: Kiszkowiak. Ł., “CFD simulation of engine nacelle cooling on pusher configuration aircraft” Goraj Z., Kowalski M., Kiszkowiak Ł.;Olejnik A., “Simulation of a passenger aircraft flight with the wing tip cut” Bridel G., Goraj Z.;Kiszkowiak Ł., Brevot Jean-G. and Devaux J., Szczepański C., Vrchota P., “Air combat training - high energy at lowest cost” Kwiek A., Galiński C., Bogdański K., Hajduk J.;Tarnowski A., “Results of Simulation and Scaled Flight Tests Performed on a Rocket-Plane at High Angles of Attack” Rogalski T., Rzucidło P., Noga St.;Prusik J., “Unmanned Aircraft Automatic Flight Control Algorithm in an Immelmann Manoeuvre” Kretov A., “Sensitivity Factors of Aircraft Mass for the Conceptual Design” Noga St., Maciejowska K.;Rogalski T., “Vibration Analysis of an Aviation Engine Turbine Shaft Shield” Samolej S., Dec G., Rzońca D., Majka A.;Rogalski T., “Regular Graph-based Free Route Flight Planning Approach” Pieniążek J.;Cieciński P., “Safety analysis of the optionally-piloted airplane landing” The articles deal with different solutions for future aerospace challenges in the areas of novel configuration, aerodynamics, design methods, multidisciplinary optimization, UAV and stress analysis. [...]I would like to thank the Editor-in-Chief of the AEAT, Prof. Philip Webb, for his agreement, and support of all editorial team of AEAT in making this issue possible.
ABSTRACT
In an environment of education reformation aimed at transition of higher education to competence based and individual approaches, we face the need to construct individual learning path for every future maritime professional. In this respect technology of adaptive learning based on modern ICT becomes of high importance. At the same time COVID-19 pandemic has changed system of education at all its levels, but the issue of quality and efficiency is still to be considered and studied by scientists and practitioners. Under these conditions the issue of adaptive information environment creation becomes relevant for training modern and competitive specialists. This environment should be based on implementation of adaptive technologies for education and training of maritime students, therefore, article provides investigation of pedagogical problem of future navigators' professional culture building in training system of adaptive information environment of maritime educational establishment. Feasibility of adaptive learning technologies implementation is grounded as a tool for future navigators' professional culture building in the process of their fundamental education and training. Example of higher mathematics adaptive learning implementation for future navigators at Kherson State Maritime Academy is considered. Higher mathematics adaptive learning was introduced through: adaptive feeding of educational content of the course;problems solving support based on examples and pre-created typical algorythms;adaptive testing;analysis of test tasks answers;system teacher support;constant support conditions for individual tasks completion;adaptive course navigation, etc. As the result of experiment there was found out that higher mathematics adaptive learning for future navigators presupposes: individual learning path designing;possibility to timely provide advising and objective control as well as evaluation;enhancement of learning activity and motivation of through improved degree of autonomy;promotion of students' research skills development;creation of cooperation, partnership and maritime brotherhood atmosphere. © 2022 CEUR-WS. All rights reserved.
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This paper considers the control design for a low-cost ventilator that is based on a manual resuscitator bag (also known as AmbuBag) to pump air into the lungs of a patient who is physically unable to breathe. First, it experimentally shows that for accurately tracking tidal volumes, the controller needs to adjust to the individual patient and the different configurations, e.g., hardware or operation modes. Second, it proposes a set-point adaptation algorithm that uses sensor measurements of a flow meter to automatically adapt the controller to the setup at hand. Third, it shows in experiments on a mechanical lung simulator that such an adaptive solution improves the performance of the ventilator for various setups. One objective of this paper is to increase awareness of the need for feedback control using flow measurements in low-cost ventilator solutions in order to automatically adapt to the specific scenario.
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The emerging COVID-19 variants lead to a new wave of infections, spreading more rapidly with more severe illnesses. The adaptive immune system plays an essential role in the control and clearance of viral infection and influences clinical outcomes. However, the understanding of the adaptive immune responses to COVID-19 is not sufficient, which impedes the development progress of treatments and vaccines. To address this issue, we proposed a machine-learning-based method (termed as VDJ-Seg-Miner) to mine the underlying associations between the V(D)J gene segments of the T cell receptor in personalized immune repertoires and COVID-19 disease characteristics for immune system analysis. Our VDJ-Seg-Miner can interpretively reveal multiple associations between the V(D)J gene segments and COVID-19 disease characteristics and assign confidence scores to indicate its confidence in each revealed association. Furthermore, experimental results based on the real-world dataset suggested that the identified associations were highly consistent with those reported in previous work. © 2021 IEEE.
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Conventional streetlight’s constant need for high power and the ill effects it has spawned on the environmental ecosystem has led researchers to adopt the idea of smart lights in order to minimize energy consumption and maximize power efficiency. This paper proposes S-LIGHT, which is a PWM-based LED adaptive light controlling system that can be deployed at public parks and other outdoor recreational venues, which applies intelligent illumination control of an LED lights. The design is based on Pulse Width Modulation technique which optimizes the overall power consumption and simultaneously supporting a multi-functional and user-friendly post. Smart street lighting aims to make cities feel safer at night, make lights more efficient, and substantially reduce costs of maintenance and energy by integrating sensors and alternative technologies to automate the light. S-LIGHT uses an Arduino UNO board along with a Passive Infrared (PIR) sensor to swiftly increase the brightness of the high-power LED light during the night in the presence of human motion, and a Light Dependent Resistor (LDR) sensor to turn on/off the light by adapting itself to the time of night/day. S-LIGHT also provides a multi-functional post that supports an emergency button feature that easily initiates an Emergency call to the police, a surveillance camera that streams live footage of the area, and an LCD screen that displays to the public awareness messages about the COVID-19 pandemic. © 2021 IEEE.
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Classic Feedback and Control is an undergraduate course that introduces students to concepts and methods for modeling, analysis, and design of single-input-single-output feedback control systems in the Electrical and/or Computer Engineering majors. In addition to using lectures to explain theories and assigning homework assignments for students to practice their modeling and analyses skills, instructors would usually supplement the course by a series of hardware-based experiments and software-based simulation labs so that students can apply the acquired knowledge to physical systems and real-world control problems. Similar to many other institutions, our ECE program offers a Feedback and Control course to junior students in the Electrical Engineering and Electromechanical Engineering majors. This course is a 3-hour lecture, 2-hour lab, as a 4-credit course. Topics discussed include modeling in both the time and the frequency domains, time response, model reduction, stability, steady-state error, root locus, design via root locus, frequency response, and design via frequency response. Due to the COVID-19 pandemic, both students and faculty in our institution were forced to work and study from home in summer 2020. In order to engage students in distance learning, application-oriented and active-learning opportunities were created. A series of exclusively software-based labs and projects were designed to help students gain a better understanding of how the knowledge are useful in real-world situations. Particularly, nine simulation labs and two simulation projects were used in the class of summer 2020. In order to evaluate the effectiveness of the designed simulation labs and projects in helping students to grasp and then apply the control concepts and ideas, surveys were conducted in the summer 2020 class to collect students' opinions and feedbacks. Among the 27 participating students, 81.4% of students “agree” or “strongly agree” that simulation laboratory exercises increased their interest in the subject, 85.1% of students “agree” or “strongly agree” that simulation laboratory exercises helped them better to learn course content, and 77.7% of the students thought simulation laboratory exercises were excellent or very good. We also compared the percentage of students who performed at the A, A-, B+, B, and B- levels with past records (while teaching was in-person), which turned out to be comparable and similar. This indicates the effectiveness of these simulation-based labs & projects, and their contribution in helping to maintain the course standard. © American Society for Engineering Education, 2021
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This paper is a work-in-progress (WIP) paper. COVID19 pandemic profoundly changed the way educators teach and the way students learn. Our institution, the New York City College of Technology, abruptly switched to distance learning mode in Spring 2020 and continues to offer all courses online in Fall 2020. This paper presents the redesign and evaluation of an undergraduate Feedback Control System course to adapt to distance learning. Feedback Control System course is the last required course for the Bachelor of Technology (BTech) program in Computer Engineering Technology (CET), which has a 3-hour lecture lesson and a 3-hour lab session every week. Due to our BTech students' diverse mathematical backgrounds, students think this course is demanding even in the traditional face-to-face teaching mode. Teaching such a mathematically involved class in the distance learning mode poses significant challenges to both the instructors and the students. This paper documents our re-structure and redesign process of both the lecture and lab components to facilitate students' remote learning experience, satisfy the ABET accreditation criteria and maintain our pre-set learning standard. The online characteristic gives the instructors the freedom and a framework to teach classes in various delivery modes via synchronous lectures (like virtual meetings) and asynchronous online supplementary resources (for example, Blackboard). The arrangements we made to adjust to the distance learning mode include: a) decomposition of the course context into three modules and clear specification of the corresponding learning objectives of each module;b) combination of different technologies to create friendly and inclusive learning environment;c) frequent assessment of students' performance via online quizzes/tests;and d) carefully-designed laboratory assignments via MATLAB simulations that are able to demonstrate the entire feedback control process. A comparison of students' performance under the traditional face-to-face learning mode and the new distance learning mode is conducted. Based on assessment results, we will evaluate the effectiveness of our current teaching methodology/plan developed for distance learning and possibly identify potential areas for further improvement. © American Society for Engineering Education, 2021