Design of a Tuned Proportional-Integral-Derivative Water Level Controller for First-Order Automated Irrigation System in Rice Field

Some problems of Filipino farmers in Nueva Ecija are irrigation systems and labor shortage. Most of them are unable to work due to old age while others chose to stop because of the COVID-19 pandemic. Meanwhile, irrigation systems have been an issue due to the lack of resources such as continuous water supply and control. Fortunately, there is a progression of smart farming in the country which could assist in optimizing farming processes. This study presents a systematic literature survey on rice farming technologies and challenges. This study also aims to help address these problems by creating a rice irrigation system that introduces a water level control system. The system was comprised of a mobile application, Arduino ESP32 module, and a tank with water level sensors. The mobile application was used to set the desired water level while the proportional- integral-derivative (PID) controller adjusted the water level automatically. When current water level is lower than the setpoint, the valves to the tank will open. Tank specifications were used to come up with a transfer function for the system. The proposed design was simulated in MATLAB Simulink and PID parameters were tuned to enhance system performance. The tuned control system obtained an output response with less overshoot and faster settling time. © 2022 IEEE.

Determination of control area and design of fuzzy rule-tuned PID controller for LFC of multimachine power system

In load frequency control (LFC) study of a large power system, the key concept is control area, which is the segment of the system consisting of strongly interconnected buses, generator buses thereof working in unison. For accurate linearization of load frequency control problem, proper determination of control area is important. In the present work, a novel deterministic method is proposed and formulated to calculate the sharing of load changes by the generators to determine the control areas for LFC study of multimachine systems. This method is applied on a weakly interconnected two-area system and then on the 10-Machine New England Test System for area segmentation of each of the two systems. Furthermore, LFC studies are carried out with proposed Fuzzy Rule-tuned PID controllers (FRT-PID Controllers) for both the systems incorporated with Dish-Stirling Solar thermal system (DSTS) in each area. The scaling factors and the controller gains are optimized using Coronavirus Herd Immunity Optimizer Algorithm (CHIOA). Performance of the proposed FRT-PID controllers is compared with that of the Conventional PID controllers for the LFC studies of the systems. To test effectiveness of the FRT-PID controllers, effect of random step load perturbation (SLP) in load buses located in different areas are considered. © 2023 Elsevier B.V.

Trajectory Tracking Analysis of Fractional-Order Nonlinear PID Controller for Single Link Robotic Manipulator System

Increasing demand for automation is being observed especially during the recent scenarios like the Covid-19 pandemic, wherein direct contact of the healthcare workers with the patients can be life-threatening. The use of robotic manipulators facilitates in minimizing such risky interactions and thereby providing a safe environment. In this research work, a single link robotic manipulator (SLRM) system is taken, which is a nonlinear multi–input–multi–output system. In order to address the limitations like heavy object movements, uncontrolled oscillations in positional movement, and improper link variations, an adaptive fractional-order nonlinear proportional, integral, and derivative (FONPID) controller has been suggested. This aids in the effective trajectory tracking of the performance of the SLRM system under step input response. Further, by tuning the controller gains using genetic algorithm optimization (GA) based on the minimum objective function (JIAE ) of the integral of absolute error (IAE) index, the suggested controller has been made more robust for trajectory tracking performance. Finally, the comparative analysis of the simulation results of proportional & integral (PI), proportional, integral, & derivative (PID), fractional-order proportional, integral, & derivative (FOPID), and the suggested FONPID controllers validated that the FONPID controller has performed better in terms of minimum JIAE and lower oscillation amplitude in trajectory tracking of positional movement of SLRM system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Design of Auto-Tuning Nonlinear PID Tracking Speed Control for Electric Vehicle with Uncertainty Consideration

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.

Advanced Control for Hammerstein-bilinear HVAC System

The COVID-19 pandemic has influenced many aspects of human life, including working environments. Some research finds that there is a tendency to the increase of energy and CO2 emissions of large office buildings in developed countries, such as US and Europe's top five economics, post-pandemic. Therefore, advanced heating, ventilation and air-conditioning (HVAC) technology that can reduce energy consumption in the building sector will yield a significant impact on the total national energy consumption. Many buildings equipped with conventional control in their HVAC control systems, such as PI or PID controls. Such controllers have drawbacks like unable to handle cross-coupling nature and constraints in a HVAC system. Conversely, model predictive control (MPC) - which belongs to advanced control - has the advantages when dealing with the system with constraints and uncertainties as it can take into account them in its optimization control problem formulation. This paper derived mathematically an industrial HVAC system based on Hammerstein-bilinear model - a model consists of a static nonlinearity followed by a dynamic bilinear subsystem. The obtained linear output-error (OE) models are subsequently used as plant models in the MPC design. The MPC controller performance is quite superior and proven to be able to meet the desired control objective (keeping the zone temperature in range of . In addition, the MPC controller gives more economic energy consumption (about save) than the PI one both for temperature and humidity control loop. © 2022 ACM.

One Degree of Freedom Copter Design and Control using Smart and Simple PID Controller

A one-degree-of-freedom (1-Dol) copter is designed, implemented, and controlled by an electronically programmed PID controller. The control of (1-DOF) copter leads to rising of the required vision for controlling stability in the designing of (2-Dofs) quadcopter;were copters are used in many fields. Nowadays, the Covid-19 pandemic causes many challenges in health sectors, especially in patient's isolation centers, which forces the health team to take a lot of precautions when dealing with the patient, by using an optimally controlled quadcopter for dealing patients, one can prevent them from infection. The required dealing involves pharmaceutical submission and temperature monitoring which can be handled by these copters with specific sensors and vision. So, there is a need for high stability and accuracy in the movement with a high speed of balancing. This work is testing one axis of these copters by designing, implementing, and controlling a one-axis copter with a simple PID controller, the controller is implemented by using an Arduino controller, with a satisfaction measure for the required balancing of 97% accuracy. © 2022 IEEE.

Optimized PI Control with Tracking Differentiator for Negative Pressure Cabin Control

To block the epidemics like "Corona Virus Disease 2019(COVID-19)"spreading, an effective isolation of the infected patients during the transportation is an important issue, which makes the negative pressure cabin (NPC) become a key equipment. There exist some practical NPCs in service, whose pressures are mostly controlled using the conventional PID controller with parameters regulated by engineering methods. Until now, there is no report about the model of NPC system from the authors' best knowledge. In this paper, the model of the NPC system is reported, which is an inherent nonlinear system. Because of the nonlinear nature of the cabin pressure, the conventional PID controller cannot achieve desire performance to balance the transient and the steady state performance, even though the optimized PID parameters are chosen using the on-line optimization based on genetic algorithm. To solve such a problem, Tracking Differentiator (TD) and PI controller are combined to achieve the desire performance using the optimized parameters. The experiment results show the improvement of the proposed method. © 2022 IEEE.

Control of COVID-19 Outbreak for Preventing Collapse of Healthcare Capacity

Mathematical models are a powerful tool to study and predict he dynamic behaviour of processes and systems, physical and biological, as well as to assist in decision making, and to design control systems. In the case of the coronavirus pandemic, COVID-19, its dynamic behaviour is generally in line with traditional models proposed, such as the Susceptible-Infected-Recovered (SIR) or the (SEIR), that includes the Exposed, which are useful tools to estimate the spread of the virus, the number of infected, the recovered individuals, and amount of deaths, as well as finding the outbreak start, the rise time, the peak time and overshoot, and fading stage. In COVID-19, the knowledge of the maximum peak and its delay time are important to prepare the healthcare system capacity, and therefore have enough intensive care units (ICUs) with automatic ventilators. In this work, a simple but robust control strategy for sequencing social distancing and confinement is proposed. The main control objective is to control the COVID-19 outbreak to avoid the collapse of the healthcare system and saturation of ICUs capacity, generating a control action sequence of social distancing and confinement such as the number of new cases requiring ICU is below a threshold set-point. An On-Off control action is analysed, and a Proportional-Integral-Derivative (PID) controller is proposed to generate a public policy (a sequence of decisions) applied once a week or every fortnight. Simulation results showing the practical feasibility and performance of the approach are given, and somehow supporting and validating strategies carried out by many healthcare teams from many countries. © 2021 IEEE.