Proportional And Integral Research Articles

An Alternative Reinforcement Learning (ARL) control strategy for data center air-cooled HVAC systems

Energy efficiency of data center is of great concern globally due to their large amount of energy consumption and the foreseeable growth in the demand of digital services in the future. Advanced control strategies are needed to reduce energy consumption. However, the optimization of data center HVAC control is a challenge task due to the complexity of the thermal dynamic models of buildings and uncertainties associated with both server loads and outdoor temperature. In this paper, we propose a new control strategy called Alternately-Reinforcement Learning-control(ARL), which realizes the alternating control of RL and proportional, integral and derivative (PID) for optimizing the control of air-cooled HVAC systems in data centers. The control object of the ARL is the speed set of the compressor and the condensing fan, and the control goal is to minimize energy consumption while maintaining temperature stability. The applied RL algorithm is Deep deterministic policy gradient (DDPG) and Proximal policy optimization (PPO). We pre-train the ARL strategy in offline environment firstly and deploy it in real data center environment for online testing. The test results show that the ARL has significant advantages in maintaining temperature stability while reducing energy consumption, and the PPO algorithm performs better than the DDPG algorithm. Compared with the PID algorithm, the PPO algorithm can save energy by 5.27%, and the temperature control effect can be improved by 3.27%,which indicates the feasibility of the ARL for implementation in real data centers.

A Wearable Dual-Mode Probe for Image-Guided Closed-Loop Ultrasound Neuromodulation.

Low-intensity focused ultrasound (FUS) is an emerging non-invasive and spatially/temporally precise method for modulating the firing rates and patterns of peripheral nerves. This paper describes an image-guided platform for chronic and patient-specific FUS neuromodulation. The system uses custom wearable probes containing separate ultrasound imaging and modulation transducer arrays realized using piezoelectric transducers assembled on a flexible printed circuit board (PCB). Dual-mode probes operating around 4 MHz (imaging) and 1.3 MHz (modulation) were fabricated and tested on tissue phantoms. The resulting B-mode images were analyzed using a template-matching algorithm to estimate the location of the target nerve and then direct the modulation beam toward the target. The ultrasound transmit voltage used to excite the modulation array was optimized in real-time by automatically regulating functional feedback signals (the average rates of emulated muscle twitches detected by an on-board motion sensor) through a proportional and integral (PI) controller, thus providing robustness to inter-subject variability and probe positioning errors. The proposed closed-loop neuromodulation paradigm was experimentally demonstrated in vitro using an active tissue phantom that integrates models of the posterior tibial nerve and nearby blood vessels together with embedded sensors and actuators.

Automatic Voltage Regulator Control System for Synchronous Generator

Presented in this paper is Automatic Voltage Regulator (AVR) Control System for Synchronous Generator. A nonlinear model of synchronous generator was developed in Simulink and was later linearized as a single input single output (SISO) transfer function model. A Proportional Integral and Derivative (PID) controller was designed and by using the MATLAB/Simulink PID tuner, the gains of the proportional, integral and derivative parameters were obtained. A Low Pass Filter, F(s) was designed and introduced as part of the input signal to eliminate any noise effect that may be introduced into the AVR control system through the input. Simulations were carried out considering basically three scenarios viz: the AVR control system without the proposed PIDf + F(s) control scheme, the AVR with the proposed technique, and the AVR with the PIDf + F(s) with the introduction of disturbance in form of load variation at 25 seconds. The performance of the proposed scheme was compared with conventional PID control AVR system without F(s). The results of the comparison indicated that the proposed technique provided superior performance in terms of percentage overshoot and settling time. Generally, the PIDf with F(s) control scheme was more stable than the conventional PID controller as indicated by the percentage overshoot, which was 4.58% for PIDf and 4.28% for PIDf + F(s).

Automatic Voltage Regulator Control System for Synchronous Generator

Presented in this paper is Automatic Voltage Regulator (AVR) Control System for Synchronous Generator. A nonlinear model of synchronous generator was developed in Simulink and was later linearized as a single input single output (SISO) transfer function model. A Proportional Integral and Derivative (PID) controller was designed and by using the MATLAB/Simulink PID tuner, the gains of the proportional, integral and derivative parameters were obtained. A Low Pass Filter, F(s) was designed and introduced as part of the input signal to eliminate any noise effect that may be introduced into the AVR control system through the input. Simulations were carried out considering basically three scenarios viz: the AVR control system without the proposed PIDf + F(s) control scheme, the AVR with the proposed technique, and the AVR with the PIDf + F(s) with the introduction of disturbance in form of load variation at 25 seconds. The performance of the proposed scheme was compared with conventional PID control AVR system without F(s). The results of the comparison indicated that the proposed technique provided superior performance in terms of percentage overshoot and settling time. Generally, the PIDf with F(s) control scheme was more stable than the conventional PID controller as indicated by the percentage overshoot, which was 4.58% for PIDf and 4.28% for PIDf + F(s).

DEVELOPMENT AND ASSESSMENT OF MANUAL AND AUTOMATED PID CONTROLLERS FOR THE OPTIMUM PRODUCTION OF ETHYLENE GLYCOL IN A CSTR

Industrially, one of the techniques used to enhance the optimum production of petrochemicals is the configuration of process control units such as gas chromatography (G.C. Analyzer) for concentration and thermocouple for temperature in the production system. This research focused on the application of the principles of mass and energy conservation in the development of dynamic or unsteady state models for predicting the behaviour of the system or process involved in the production of ethylene glycol from a reaction involving oxidation of ethylene-to-ethylene oxide which further undergoes hydrolysis to produce ethylene glycol in a continuous stirred tank reactor (CSTR). The high mathematical complexities of the mass and energy balance models of the Process as a result of the reaction kinetic scheme of the non-elementary reaction of the process which integrated both linear and non-linear terms into the models were resolved by the application of the principles of Taylor’s series expansion, Laplace Transform, partial fraction and matrix in the development of the dynamic models. Process simulation tool (Simulink) was utilized in the configuration of closed-loop systems with thermocouple and G. C. Analyzer, at the feed point of the reactor for process variables (temperature and concentration) control during the process using proportional, integral and derivative (PID) as controller parameters. The results of the process behaviour showed that manual tuning of different controller parameters experienced a high level of fluctuations and would not attain its stability or steady state even at a processing time above 16 seconds. Whereas, automatic tuning of desired controller gains of 1.361, 1.056 and 0.4109 for K P, K I and K D for temperature and pressure with a tuning time of 143.9 Seconds, requires a maximum time of 8 seconds for the system to attain stability. This study showed that automated tuning of the controller resulted in better performance characteristics for optimum production of ethylene glycol in a non-isotheral continuous stirred tank reactor within the shortest possible time.

Coot optimization algorithm-tuned neural network-enhanced PID controllers for robust trajectory tracking of three-link rigid robot manipulator

Robotic manipulators are nonlinear systems, multi-input multi-output, highly coupled and complicated whose performance is negatively impacted by external disturbances and parameter un-certainties. Therefore, the controllers designed for such systems must be capable of managing their complexity. The main aim of this study is to tackle the trajectory tracking issue of the three-Link Rigid Robot Manipulator (3-LRRM) based on designing three control structures using a combi-nation Neural Network (NN) with Proportional, Integral and Derivative (PID) actions named Neural Controller Like PIPD (NN-PIPD) controller, Neural Network plus PID (NN + PID) controller NN + PID controller and Elman Neural Network Like PID (ELNN-PID) controller. The parameters of the proposed controllers are adjusted utilizing the Coot Optimization Algorithm (COOA) in order to reduce the Integral Time Square Error (ITSE). A novel objective function for tuning process to produce a controller with minimum value of the chattering in the control signal is proposed. The performance of the proposed controllers is evaluated in terms of disturbance rejection, model uncertainty, fluctuating initial conditions and reference trajectory tracking. According to the simulation results proved that the suggested NN-PIPD controller outperforms all other proposed controller structures for tracking performance, stability, and robustness. As a result of the com-parison analysis the optimal controller was considered to be an NN-PIPD controller for tracking trajectory, rejecting disturbances, and parameter variation with minimizing ITSE of 0.001777.

Microsatellite Yaw-axis Attitude Control System Using Model Reference Adaptive Control Based PID Controller

This paper presents a Model Reference Adaptive Control (MRAC) based Proportional Integral and Derivative (PID) controller for microsatellite yaw-axis Attitude Control System (ACS). The objective is to combine the algorithm of MRAC with PID to improve the performance of a microsatellite system especially settling time. MRAC based PID controller for yaw-axis ACS was modelled and simulated in MATLAB/Simulink to meet transient response characteristics specifications. The performance of the system was evaluated in terms of rise time, settling time, maximum overshoot, and steady-state error including energy consumption measured based on armature voltage of the direct current motor. The simulation results revealed that the proposed system meets all the performance specifications and outperformed classical PID controller for adaption gain of 0.2 to 20. When compared with PID and Proportional Derivative (PD) based Controllers in previous study for adaption gain of 10, 15, and 20, the proposed system proved to be superior. Generally, the choice of the MRAC based PID controller considering the range of adaption gain (γ = 0.1 to 20) should be based on either transient response advantage or energy consumption or even both over PID controller. The significance of this study is that an MRAC based PID controller that offered wide range of adaption capability for microsatellite ACS has been proposed.

Charging delay elimination of solder impregnated HTS coils with specific excitation current

No-insulation (NI) coil has been recognized as the most practical solution at present to achieve ultra-high magnetic field with the REBCO high temperature superconductor thanks to its passive quench protection mechanism which is originated from the inter-turn current bypass. However, for the NI technique, one of the most important obstacles to a more general application is the field delay which is also a consequence of the lack of inter-turn insulation. The proportional and integral (PI) active feedback control of power supply has been developed to achieve a designed field ramping rate. The efficiency of this method could however be affected by the measurement accuracy of measuring equipment, sampling frequency, control accuracy of power supply and other factors. In this manuscript, we tried to use a more fundamental method to mitigate the field delay. The point is, though unlike in insulated coils the field generated is not proportional to coil current in NI coils, they do have a certain linear relation for a certain coil. Based on the lumped circuit model, the current charging curve corresponding to a desired field excitation could be calculated for a NI coil. We verified this method on several solder impregnated no-insulation coils (SINoInCs) to excite their field with different rates, for which the field delay with normal charging method could be very large because of the very low inter-turn resistance. The test results show that this kind of fast excitation method could successfully achieve the desired field with high accuracy and mitigate the field delay from 130 s to almost 0 s. Besides, the large overshoot current introduced by the fast charging does not quench the coils even with an overshoot current which is almost double of the coils’ operating current.

Mitigation of voltage sag and voltage swell by using dynamic voltage restorer

Recent power quality (PQ) research shows that the most common types of power quality disturbances are voltage sags and swells in medium and low-voltage distribution grids. This paper shows how to improve two significant power quality disturbances: sags and swells voltage. To find out what effect these two PQ issues have in real life, a study case based on real nonlinear loads data from large induction motors at Beshai Company in Sadat City in Egypt is investigated. The dynamic voltage restorer (DVR) has been suggested as a solution to the voltage swell and voltage sag issues. The point of common coupling (PCC) is linked with the dynamic voltage restorer to mitigate the PQ problems that have been found. The power network, loads, and DVR may all be modeled using the MATLAB/Simulink platform. The jellyfish search optimizer (JFS) is used to get the gain settings of the proportional and integral (PI) controller for the proposed DVR. MATLAB/Simulink's results show that the proposed device is effective, reliable, and has low latency.

PI-based simulation modeling for performance testing of the power transmission line

The transmission line is one vital component of electrical power system. It determines some fundamental characteristics such as transmission efficiencies, voltage drops and line losses which are important matters to be considered in system planning, design and maintaining. The so-called PI-based modeling refers to using basic PI (proportional and integral) elements as well as other basic elements to implement one specific simulation. Grounded on the distributed-element model and addressing complex-element modeling, one PI-based simulation method is introduced in this study for teaching purposes and applied to modeling and simulation for performance testing of the power transmission line. The proposed method is demonstrated in the Simulink simulation environment and verified by performance testing of the power transmission line including complex-element-based equivalent distributed-element modeling for (short, medium and long) transmission lines, load flow analysis, short circuit test, open circuit test and the “Ferranti-effect” phenomenon, SIL (surge impedance loading) and series and shunt compensation simulation. Results indicate workability of the proposed method that it provides one convenient and vivid way for complex-element-based simulation modeling and solving numerical solutions as well. The proposed PI-based method for complex-element modeling and its Simulink-based simulation approach may be useful for related electrical engineering simulations and testing.

Research on Maximum Power Control of Direct-Drive Wave Power Generation Device Based on BP Neural Network PID Method

Ocean wave energy is a new type of clean energy. To improve the power generation and wave energy conversion efficiency of the direct-drive wave power generation system, by addressing the issue of large output errors and poor system stability commonly associated with the currently used PID (proportional, integral, and derivative) control methods, this paper proposes a maximum power control method based on BP (back propagation) neural network PID control. Combined with Kalman filtering, this method not only achieves maximum power tracking but also reduces output ripple and tracking error, thereby enhancing the system’s control quality. This study uses a permanent magnet linear generator as the power generation device, establishes a system dynamics model, and predicts the main frequency of irregular waves through the Fast Fourier Transform method. It designs a desired current tracking curve that meets the maximum power strategy. On this basis, a comparative analysis of the control accuracy and stability of three control methods is conducted. The simulation results show that the BP neural network PID control method improves power generation and exhibits better accuracy and stability.

Bio-Inspired Jumping Spider Optimization for Controller Tuning/ Parameter Estimation of an Uncertain Aerodynamic MIMO System

The practical near impossibility of empirical attempts in estimating optimal controller gains makes the use of metaheuristics strategies inevitable to automatically obtain these gains by an iterative, heuristic simulation procedure. The convergence of the gains values to the local or global solutions occur with ease. In designing controllers for the Twin-Rotor MIMO System (TRMS), Jumping Spider Optimization Algorithm (JSOA), a novel neoteric population-based bio-inspired metaheuristic approach is used to obtain optimum values for the Proportional, Integral and Derivative (PID) controllers. With the k,p,i controller gains as the decision variables, the JSOA solution to a nonlinear multi-objective optimization problem subject to some intrinsic constraints spawned optimal values for the controllers’ variables. Counter to other algorithms (deterministic and stochastic) that get caught in local minima, JSOA evolved a solution after searchingly rummaging the entire solution search space in a vectorized fashion for an optimal value. Compared with several other versatile controllers (using GA, PSO, Pattern Search and Simulated Annealing), statistical results obtained showed JSOA technique provided a unique solution and found the gains of the PID controllers, marginally in relation to the others (optimization methods).

Analysis and Compensation of Phase Current Measuring Error Caused by Sensing Resistor in PMSM Application.

Field Oriented Control (FOC) effectively realizes independent control of flux linkage and torque, and is widely used in application of Permanent Magnet Synchronous Motor (PMSM). However, it is necessary to detect the phase current information of the motor to realize the current closed-loop control. The phase current detection method based on a sampling resistor will cause a measurement error due to the influence of parasitic parameters of the sampling resistor, which will lead to the decrease in PMSM control performance. This paper reveals the formation mechanism of the current sampling error caused by parasitic inductance and capacitance of the sampling resistor, and further confirms that the above error will lead to the fluctuation of the electromagnetic torque output by simulation. Moreover, we propose an approach for online observation and compensation of the current sampling error based on PI-type observer to suppresses the torque pulsation of PMSM. The phase current sampling error is estimated by the proportional and integral (PI) observer, and the deviation value of current sampling is obtained by low-pass filter (LPF). The above deviation value is further injected into the phase current close-loop for error compensation. The PI observer continues to work to keep the current sampling error close to zero. The simulation platform of Matlab/Simulink (Version: R2021b) is established to verify the effectiveness of online error observation and compensation. Further experiments also prove that the proposed method can effectively improve the torque fluctuation of the PMSM and enhance its control accuracy performance of rotation speed.

Controlling temperature using proportional integral and derivative control algorithm for hybrid forced convection solar dryer

Drying is one of the crucial processes in agricultural production, especially in grain processing. The drying process can improve grain quality and affect the grain content. However, maintaining the temperature is a challenge in the drying process. Because it can influence the drying performance and produce a low-efficiency reduction of water content, in this study, the hybrid drying system is proposed to improve the performance of the forced convection dryer system. The proposed system used a proportional integral and derivative (PID) control system to obtain the optimal temperature. The proposed system was compared with natural drying and forced convection methods. The experimental result showed that the proposed system performed excellently for three performance evaluations. The average temperature was obtained as the highest of the other methods, with 54.68 °C and 54.55 °C for coffee and cocoa beans. The water content can be reduced by an average of 27.38% and 42.67% for coffee and cocoa beans. Then, the proposed system also had the highest reduction efficiency of water content than the other methods, with 62.71% and 36.94% reductions for coffee and cocoa beans, respectively. The results indicate that the proposed hybrid system performs better than the other methods.

Development of a master–slave 3D printed robotic surgical finger with haptic feedback

Robotic surgery started nearly 30 years ago. It has achieved telepresence and the performance of repetitive, precise, and accurate tasks. The “master–slave” robotic system allows control of manipulators by surgeon at distant site. Robotic surgical fingers were developed to allow surgeons to move them with accuracy through sensors fixed on surgeon’s hand. Also, haptic sensors were developed to allow transmission of sensation from robotic finger to surgeon’s finger. A complete system of a, 3D printed by a stereolithography (SLA) 3D printer, robotic surgical finger with haptic feedback system is proposed. The developed system includes a master glove that controls the motion of a 3DOF robotic slave finger while getting haptic feedback of force/pressure exerted on it. The precise control of the slave robotic finger was achieved by applying a Proportional Integral and Derivative (PID), fast and robust, control algorithm using an Arduino based hardware and software module. The individual joint angles, metacarpophalangeal joint (MCP) and proximal interphalangeal joint (PIP), and wrist were measured using rotatory and inertial sensors respectively. The degree of movement for MCP, PIP, and Wrist joints were measured to be 0–86°, 0–71°, and 0–89° respectively. Motion to the robotic finger is mimicked by a glove motion requiring minimal learning curve for the device. The collected data for the slave motion is in good agreement with the master-glove motion data. The vibro-tactile haptic feedback system was developed to distinguish between three different materials to mimic human flesh, tumor, and bone. The master–slave system using robotic surgical finger with good simultaneous movement to surgeon’s finger and good haptic sensation will provide the surgeon with the opportunity to perform finger dissection in laparoscopic and robotic surgery, as it used to be in open surgery. 3D bio printing will make this process even cheaper with the added advantage of making surgical tools locally according to the need of the surgery. An ongoing work is to develop silicone based 8 mm robotic surgical finger with multiple type haptic feedback.

Prototipe Sistem Pencegah Banjir dengan Pengontrolan Pintu Air Waduk menggunakan Kontrol PID berbasis PLC & HMI

The purpose of research on this flood prevention system prototype design is to prevent flood caused by overflowing reservoir water. This system prototype uses the Modicon M340 Programmable Logic Controller as a controller and is equipped with a Human Machine Interface feature as a medium for managing and monitoring system performance virtually. This system is supported by a Water-Level Sensor to measure the water level in the reservoir and also the rate of addition of water in the reservoir. The sluice mechanism is driven by a Stepper Motor assisted by the ULN2003 Driver Module based on Proportional, Integral and Derivative (PID) control to maintain the water level in the reservoir. PID control in this system successfully runs optimally at constant KP = 3.5, KI = 2, and KD = 1, with an error result of 0,048%. This constant has the best response time compared to other constants, where rise time = 11.76 s, settling time = 13.95 s, and steady state time = 14.07 s.

Defect detection of metallic samples by electromagnetic tomography using closed-loop fuzzy PID-controlled iterative Landweber method

ABSTRACT Electromagnetic tomography (EMT) uses the mutual inductance of the coil to visualise the conductivity distribution of interesting regions. Since the conductivity of defects and metal samples are different, the metal samples with defects can be treated as binary-valued material distributions. This paper investigates the closed-loop fuzzy proportional, integral and derivative (PID)-controlled iterative Landweber method. The whole method includes fuzzy PID controller, the Landweber reconstruction method, and the Dirichlet-to-Neumann map. Specifically, the differential signal between the mutual inductance of the coil and the feedback signal is used as the input of the fuzzy PID controller. The fuzzy controller can automatically adjust three parameters ( K p , K i and K d ) of PID controller. Subsequently, the output of the PID controller can serve as the input of the Landweber algorithm to reconstruct the distribution of conductivity. Furthermore, the Dirichlet-to-Neumann map is used to calculate the mutual inductance, acting as the feedback signal based on the reconstruction conductivity distribution. Finally, both the numerical simulation and experiments are applied to verify the proposed method. The results indicate that the proposed method can reconstruct the image with a clear edge, and the average correlation coefficient can reach 0.792.

A New Design and Embedded Implementation of a Low‐Cost Maximum Power Point Tracking Charge Controller for Stand‐Alone Photovoltaic Systems

This article presents a low‐cost maximum power point tracking (MPPT) charge controller designed to efficiently charge solar batteries using a simple and robust MPPT method, while providing protection against over‐currents and over‐voltages. The proposed MPPT approach utilizes a modified Incremental Conductance (INC) algorithm adapted to low‐cost embedded controllers, as it avoids all the mathematical division calculations typically used in the conventional INC algorithm. It also introduces a modified step size based only on photovoltaic (PV) power change to enhance tracking accuracy and convergence speed. Furthermore, to reduce the stress and switching losses of DC–DC converter, a feedback control with two proportional and integral (PI) compensators is also used to control both the PV voltage and to protect the battery from over‐currents using PV power limitation technique. Simulation results, carried out under MATLAB/Simulink, demonstrate the good performance of the proposed control scheme regarding any variations in atmospheric conditions, both for the MPPT control and for the battery charge control. Finally, a processor‐in‐the‐loop (PIL) test using a low‐cost Arduino MKR ZERO board is also performed to verify the hardware implementation of the proposed method. PIL results are in totally accordance with MATLAB/Simulink simulation results, which further proves the effectiveness of the proposed method.

Design of control strategy for reactor power control system of LBE cooled Actinide Burner Reactor (ABR) using system analysis code NUSOL-LMR

The power control strategy for the Lead–Bismuth Eutectic (LBE) cooled Actinide Burner Reactor (ABR) has been designed to assess the closed-loop performance of newly developed control blocks that were not modeled in the NUSOL-LMR code before this research effort. After establishing a sustainable model of ABR in NUSOL-LMR, validation of the model in light of the already-published research is performed. The said closed-loop control strategy (consisting of the power and temperature control blocks) is evaluated under different transient scenarios (reactivity insertion, primary coolant pump fault, and change in demand power levels). The power and temperature control blocks concurrently control reactor power during any transient occurrence. The coupling effect of the primary coolant temperature deviation on the reactor power has been minimized by the proportional and integral (PI) controller in the temperature control block. The simulation results demonstrate that the closed-loop performance of the ABR under the controller action during transient events is quite satisfactory. The closed-loop power regulation performance of the conventional sliding mode controller (SMC) with a PI sliding surface (PISM) in the power control block of NUSOL-LMR is better than that of a simple proportional, integral and derivative (PID) controller. The asymptotic stability of the closed-loop system with the PISM controller has been ensured using the Lyapunov stability theory.

Human Heart Stabilization using Mathematical Based Model with Proportional Integral and Derivative Controller

This paper presents human heart stabilization using mathematical based with Proportional Integral and Derivative (PID) controller. In order to improve the Hydro Electromechanical System (HEMS) of human heart models found in prior studies, the present paper introduced a PID model that integrates a low pass filter (F) to give a PIDF that provides control signal to adjust the heartbeat rate if it is disturbed and to command the cardiovascular system. The entire system was built and simulated in MATLAB/Simulink environment. The heartbeat model has been applied for steady state study of cardiovascular system when a disease attacks the heart. The result obtained proves the effectiveness of the developed control strategy. Simulation result revealed that the introduction of the PIDF controller ensured the stabilization of the heart to its right working state when compared to the heartbeat response of normal heartbeat.