Regulatory Control System Research Articles

Design and Implementation of a Biogas Pilot Plant for Bioaugmentation Strategies in a rural municipality

The transition towards renewable energy sources is imperative for achieving sustainability and mitigating climate change impacts. Among various renewable energies, biogas stands out for its dual role in waste management and energy production. This study introduces the design and implementation of a biogas pilot plant aimed at exploring bioaugmentation strategies to enhance biogas yield and quality. The pilot plant, located at Aras de los Olmos, features two independent 3.4m3 digesters, allowing for parallel comparison between standard anaerobic digestion and digestion with microbial enhancements. The plant is equipped with monitoring and control systems for precise regulation of environmental conditions, such as temperature, and for real-time measurement of biogas composition. Some initial experiments using a mix of agricultural wastes demonstrated the plant's capability to adapt to varied feedstock. Despite suboptimal temperature conditions, preliminary results indicated a high methane content, suggesting significant potential for bioaugmentation to improve biogas production efficiency. The study highlights the importance of controlled environmental conditions and introduces a novel bioaugmented digestion approach using selected microbial consortia. This research contributes to the broader goal of enhancing biogas technology's efficiency and sustainability, offering insights into the practical application of bioaugmentation in biogas production.

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).

Quadrotor height control system using LQR and recurrent artificial neural networks

The quadorotor is a type of unmanned flying vehicle known as Unmanned Aerial Vehicle (UAV). In recent years, quadrotors have attracted much attention from researchers around the world due to their excellent maneuverability. A good control system in this quadrotor system is needed for ease of use of this quadrotor. One control system that is often used is the Linear Quadratic Regulator (LQR) control system. This control system has challenges for dynamic system disturbances in quadrotor control. Researchers proposed a recurrent artificial neural network (RNN) system to address these challenges.RRN is used to change the value of the feedback component in the LQR control system. The nature of the feedback component in LQR, which is static, is changed based on the system error value based on changes in the error value entered into the RNN. The result of this RNN is a change in the value of the LQR feedback component based on the input of the system. The results of this research show that LQR control with RNN produces a faster system response of 0.075 seconds and a faster settling time of 0.221 seconds. Compensation for the system response speed produces a higher overshot value.

Adaptive temperature control of a reverse flow process by using reinforcement learning approach

This work focuses on the design of an optimal adaptive control system for temperature regulation in a catalytic flow reversal reactor (CFRR), utilizing a reinforcement learning (RL) approach. First, a policy iteration algorithm is introduced to learn the optimal solution of the associated linear-quadratic control problem online. It should be mentioned that this approach is not reliant on the internal dynamics of the CFRR system, which is a complex process and is most effectively modeled using Partial Differential Equations (PDEs). The convergence of the iteration algorithm is established, assuming the initial policy is stabilizing. Additionally, a second algorithm is presented to enhance the implementability of the reinforcement learning algorithm from a practical perspective. Numerical simulations are carried out to illustrate the efficacy of the proposed algorithm.

Research to Simulate the Ship’s Vibration Regeneration System using a 6-Degree Freedom Gough-Stewart Parallel Robot

This article presents research results on building a model to reproduce ship vibrations based on a Parallel robot with 6 degrees of freedom Gough – Stewart form. Vibration data at the ship’s center of gravity calculated by simulation software will be the input to the model. The regenerative control system uses a simple PID controller to control input trajectory tracking. Simulation results on Matlab/Simulink software have demonstrated the reproduction of ship vibrations within the allowable error.

Approach to Chemical Process Transition Control via Regulatory Controllers with the Case of a Throughput Fluctuating Ethylene Column

For chemical processes, dynamic optimization is employed for process transition. On the basis of the multilayer control structure, the employment of dynamic optimization is affected by the regulatory control system. To avoid the adjustment of the regulatory control system, set-point optimization is proposed. For comparison, two types of optimization models, namely direct optimization and set-point optimization, are formulated. The superiority of set-point optimization is rigorously proven. By simulating the commercial process of a throughput-fluctuating ethylene column, the integrated absolute error and maximum deviation of product quality are reduced by more than 150% with set-point optimization. The results indicate that the approach to process transition via regulatory controllers not only avoids the insecurity caused by the switching of set-point controllers but also improves the optimization performance. In conclusion, the proposed optimization structure, namely set-point optimization, is operable and stable for commercial chemical process transitions.

Introduction to PM 9 Standards on National regulatory control systems

Introduction to PM 9 Standards on National regulatory control systems

Development of an IoT-Monitoring and Control System for Solar Panel Surface Temperature Regulation Utilizing Water-Cooling Techniques

As the world's energy needs escalate and the availability of finite natural resources diminishes, there is an urgent need to explore sustainable alternatives. Renewable energy sources, including solar power, hold great promise due to their abundance, cost-effectiveness, and environmental friendliness. Solar panels, a cornerstone of renewable energy, have the potential to provide clean electricity, but their efficiency depends on temperature control. This research addresses this challenge by implementing an Internet of Things (IoT) monitoring and control system using the Blynk platform to regulate solar panel surface temperatures. The system's smart design uses water pumps to mitigate excessive temperatures, improving performance and energy efficiency. Extensive testing demonstrated the system's effectiveness, particularly in mitigating temperature spikes, improving system efficiency and sustainability. Our results demonstrate the remarkable potential of water-cooled systems and IoT technology to revolutionize solar energy harvesting, marking a significant step toward a sustainable energy future.

A Mathematical Model of an Automated Control System for Heat Regulation in a Building

In this study, a mathematical model of an automated control system for heat regulation in a building was developed. A method of mathematical modeling of the centralized heating control system based on mathematical models of distributed power systems and experimental studies has been developed, which allows for determining the parameters of the coolant when the outdoor temperature changes, qualitative regulation of heat in autonomous sources, quantitative regulation in automated individual heating devices, etc. The method makes it possible to study the interaction of an automated individual heating point to increase the efficiency of the management of distributed power systems of buildings. As a result of studying the controller created by the R2 control unit, for the PI controller, the calculated heat consumption of the building imperceptibly increases from 1.08502 kJ to 1.085888 kJ when an oscillatory transient occurs, and for the I controller, the calculated heat consumption of the building remains at the same level. The level, as for the PI controller, increases slightly during the oscillatory transition from 1.08456 GJ to 1.08535 GJ.

Design of a predictive control system for the smart regulation of renewable climatization systems

The objective of this Project is to design a predictive controller for Heating Ventilation and Air Conditioning in residential buildings is designed. A realistic residential home has been designed, establishing the dynamics of the temperature according to a theoretical model that has been elaborated, being the basis for the actuation of the temperature-regulation controller. Several simulations have been carried out, defining the objective function and the constraints associated, together with the controller parameters that allow an optimal performance, taking into account different criteria such as thermal comfort and reduction of power consumption for different scenarios. In addition, electricity selfgeneration has been also contemplated, integrating it into the controller actuation for leveraging the increase in economic savings.

Trade, Businesses, and Economy of U.K. Post-Brexit— A Quantitative Analysis

Many studies have been carried out on Brexit’s economic impact on the UK, EU27, the US, and the rest of the world. Depending on the assumption of whether Brexit will be a hard Brexit or a soft Brexit, almost all studies predicted Blows to the economies of the UK and the EU, with a more severe blow to the UK economy. With the Trade Co-operation Agreement signed by the end of the year 2020 and the actual divorce of the UK from the EU with effect from 01-01-2021, the actual effects of Brexit came to reflect in various economic data reported by various national and international agencies. This paper makes an effort to analyse these hard data and examine the Brexit impacts on various sectors. It has also taken clues from the various surveys on the problems faced by businesses on the border, shortage of labour, etc. In February 2023, a protocol on Northern Ireland was finalized which became a part of the EU-UK withdrawal agreement that now ensures that a hard border is avoided for the UK export items on the island. This protocol was agreed upon between the United Kingdom, Northern Ireland (UK), and the European Union (EU) as the final settlement designed to protect Ireland’s economy and Belfast Agreement. The study concludes that the UK has done a relatively good job of managing the inevitable Brexit disruptions, including transitional measures for border softening. In order to achieve the laudable goal of having the best border in the world by the year 2025, the UK will require streamlining the Regulatory Control Systems. The UK has also entered into a Comprehensive Agreement with Trans-Pacific Partnership. But much is still to be done on the Domestic Regulatory Reforms front. Unless the UK uses the coming years to engage in putting in place proper, meaningful, and comprehensive regulatory reforms, the opportunities for Brexit may be wasted.

Performance analysis on parallel operation of multimode droop controller doubly fed induction generator based wind energy conversion system with Other wind unit, solar units, loads and facts device

Due to their numerous advantages, wind turbines with changeable speed power production systems are increasingly being used. This study proposes the architecture and specifications of an induction turbine-generating wind system, as well as a PI controller-based DC voltage link regulator and optimal torque control system. The suggested control technique as stated in this paper allows the system to function in grid-linked mode as well as the islanded mode and also in parallel with other power generation units, loads, FACTS devices, etc. This paper involves the analysis of different test cases in grid-connected mode as well as an islanded mode with a PV generation unit, passive loads, induction motor loads, and other wind energy generation systems. The paper also includes an analysis of the response of the system with the switching on and off of the other units. MATLAB 2013a thereby validates the system findings and analysis.

Development of the automated temperature control system of the main gas pipeline

This article presents the results of a numerical experiment and an analysis of temperature fields (coolers for gas) using cooling elements in the case study gas pipeline. An analysis of the temperature fields demonstrated several principles for the formation of a temperature field, which indicates the need to maintain a relative temperature for gas pumping. The essence of the experiment was to install an unlimited number of cooling elements on the gas pipeline. The purpose of this study was to determine at what distance it is possible to install cooling elements for the optimal gas pumping regime, regarding the synthesis of the control law and the determination of the optimal location and assessment of control error depending on the location of the cooling elements. The developed technique allows for the evaluation of the developed control system's regulation error.

Comparing economic model predictive control to basic and advanced regulatory control on a simulated high-pressure grinding rolls, ball mill, and flotation circuit

Mineral processing plants remain nowadays infamous for their low energy efficiency. Economic model predictive control (EMPC), by directly considering the energy costs, could possibly help reduce their footprint, but its environmental benefits are yet to be clearly quantified. In an attempt to cast some light on this topic, this paper compares the response to a given ore feed size and hardness disturbance sequence of an EMPC to that of basic and advanced regulatory control systems using the profits and the specific energy (power draw/ore feed rate) as metrics. The simulated circuit comprises a high-pressure grinding rolls (HPGR), a ball mill, and a flotation circuit. It is based on population balance modeling and is an extension of previous works. The basic regulatory control (BRC) system comprises only single-input–single-output control loops with proportional–integral (PI) controllers and operates at a fixed feed rate. The advanced regulatory control (ARC) system consists of PI controllers maximizing the plant feed rate with override constraint handling. The results show that (1) ARC generates more revenue and maintains a lower circuit specific energy consumption than BRC, (2) ARC can produce the same economic performance as EMPC because the constraints of the system define the economic optimum, and (3) EMPC can trade revenues for a lower circuit specific energy with a hybrid criterion that penalizes power draw.

Nonlinear Predictive Control for Temperature Regulation of Solar Furnaces

In the context of material synthesis and thermal stress tests, solar furnaces play a fundamental role. These experimental systems are usually operated manually by trained operators. However, the use of automatic controllers can be essential to take into account the different dynamics of the treated materials, follow the different temperature profiles required in the tests, meet system security requirements, and face the intermittency of the main energy source, the solar energy. On these bases, the present work proposes a control system for temperature regulation in solar furnaces. The controller is based on a nonlinear model predictive control strategy that deals, in a single control layer, with the nonlinear behaviour of the system, the effect of disturbances, and the system's operating constraints. The controller was experimentally tested in the solar furnace SF60 of Plataforma Solar de Almería (southeast Spain), showing adequate performance against setpoint temperature changes, reaching a settling time of the order of 54 % faster than the open-loop system's time constant, and effectively rejecting irradiance disturbances. In addition, the operational constraints were ensured in almost all operating circumstances, observing only slight deviations of less than 2°C. These results allow us to position the proposed controller as a relevant tool for daily operation.

Simulation Research on Ship-borne PMSM Speed Regulation Control System Based on Fuzzy PID Control

As the important actuator of ship-borne electromechanical equipment such as offshore cranes, the control system of Permanent-magnet synchronous motor (PMSM) is a complex system that features nonlinearity, time-varying parameters, and multi-variable coupling. Due to working in a swing environment, the ship-borne PMSM speed regulation control system is confronted with some problems, such as abrupt load change, external interference signals, motor parameters change, and given signals change frequently. To improve the control performance, this study designs the 2-dimensional Fuzzy PID controller and builds the control system simulation model with a double closed-loop structure in the MATLAB/Simulink. By comparing the control system under various simulation situations, the simulation findings demonstrate that the control system using the Fuzzy PID controller far outperforms the PID controller in terms of control indicators such as stability, tracking ability, and anti-disturbance ability, which can better adapt to working in swing environment.

Balancing control of a motorcycle

Abstract This article deals with balancing an autonomous motorcycle model along a straight line and curve lines. The dynamic model of the motorcycle balancing is described with an inverted physical pendulum loaded with torque. The torque is provided by the inertia of a rotor driven by a direct current motor. The lean angle of the motorcycle is measured by a smart sensor, which is the feedback signal for the linear quadratic regulator control system. The main purpose of this study is to compensate the error of the smart sensor. Controlling the necessary lean angle of the motorcycle during cornering is also addressed.

A Coupling Analytical Method of a Fuel Control System under Electromagnetic Pulses

This study presents an electromagnetic coupling analytical method of a fuel control system under electromagnetic pulses. With the increasing complexity of the electromagnetic environment, improving the survivability of the aero-engine fuel control system is of great importance. By analyzing the electromagnetic interference of the aero-engine fuel control system under electromagnetic pulses, a coupling analytical method of an aero-engine fuel control system under electromagnetic pulses was proposed. The method tested the control system to obtain the coupling signal of the controller through the bulk current injection (BCI) test. Subsequently, the numerical model of the terminal coupling signal of the controller under an electromagnetic pulse was established, and the influence of the terminal coupling signal on the terminal circuit was investigated by numerical simulation. The method locates sensitive components of the control system and determines if the internal mechanism of the electromagnetic pulse effect is the interference of the pulse signal to control signal links. The coupling signal model is established to predict the coupling signal of the main fuel regulation control system. It identifies potential solutions to BCI method limitations that have an impact on reducing test costs.

Experimental Study on the Coupling Mechanism of Sensors under a Strong Electromagnetic Pulse.

This paper presents a study on the electromagnetic effects of a main fuel control system under the action of a strong electromagnetic pulse. It assesses the electromagnetic sensitivity of a speed sensor and a linear variable differential transformer (LVDT) sensor. This assessment focuses on the control system’s electromagnetic effects and the sensors’ coupling signals. The effects and signals were determined using radiation and pulse current injection tests. Analysis of the signal at the system power port shows that it is the same as those for the two test methods. Based on analysis of the working mechanism and terminal signals of the sensors, the electromagnetic sensitivity of the system is different under the different electromagnetic pulse conditions. The electromagnetic sensitivity characteristics of the sensors were verified, and the electromagnetic effects of the main fuel regulation control system were analyzed. Meanwhile, the degree of sensor coupling mechanism caused by the electromagnetic coupling effects of the main fuel regulation control system under strong electromagnetic pulses were studied. These findings have clear practical implications for electromagnetic pulse protection of aero-engine control systems.