Output Control Research Articles

Effect of Row Spacing and Weed Management Practices on Growth and Yield Components of Tomato (Solanum Lycopersicum L.) in Yola, North-Eastern Nigeria

Field trial was conducted during 2020 and 2021 dry seasons at experimental farm site of the Department of Crop Production and Horticulture, Modibbo Adama University, Yola to study the Effect of row spacing and some weed management practices on growth and yield components of Tomato (Solanum lycopersicum L) in Yola north-eastern Nigeria. The experiment was layout in a split plot arrangement of a Randomize Complete Block Design (RCBD) with (5) treatments Zero weeding (Control), Weedy check (Weeding at 2 and 4 Weeks After Transplanting), Maize straw at 1.0 kg m-1, S-metolachlor at 1.5 kg ha-1 and Pendimethalin at 1.44 kg ha-1) replicated three (3) times. Row spacing of 40x40cm, 60x60cm and 80x80cm was assigned to main plot while the different weed management treatments were assigned to sub-plot. The parameters measured on the crop include tomato plant height, number of branches per tomato plant, number of tomato fruits per plant. And weed parameters measured were number of broadleaf weeds/m2, grasses/m2, sedges/m2, total weed density/m2, weeds dry weight/m2, weed control efficiency (%) and weed index at harvest. The data collected were analyzed statistically using analysis of variance (ANOVA) and Duncan’s Multiple Range Test to separate the means at 5% level of probability. The results shows significant differences on plant height of tomato. Weedy check and 40cm row spacing recorded the tallest tomato plant heights of (18.54) at 2 WAT in 2020 while the tallest plant, was recorded at the interaction between weedy check and 60 cm row spacing of (22.58 cm) in 2021. The highest number of branches for the two experimental years of 2020 and 2021, were recorded at the interaction between 40 cm row spacing and weedy check treatment of (7.17) and (11.50), compared with Pendimethalin that recorded the lowest tomato plant heights, number of branches of (1.00) and (2.00) at 4 & 5 WAT. Similarly, the result for weed parameters also indicated that weedy check and 40cm row spacing has the lowest weed density m-2 of (1.84) at 30 days after application in 2020 and (1.77) in 2021 compared to Zero weeding plot and 80cm row spacing that recorded with the highest weed density of (7.04) & (7.16) for both 2020 and 2021 experimental years, also the percentage of weed dry matter. Weedy check also recorded highest weed control efficiency and weed index compared with remaining treatments. Therefore, the finding of this work said “weedy check treatment and 40 cm x 40cm row spacing were the best among weed management practice and row spacing” and are recommended for use as an alternative to the use of herbicide and 60 cm x 60 cm row spacing for effective weed control and maximum yield output of the tomato production in Yola, Nigerian.

Low-Level Radio-Frequency system integrated with feed-forward control and vector modulation

To provide a more accurate and stable Radio-Frequency (RF) signal in conditioning and processing test progress, it is necessary to design a Low-Level Radio-Frequency (LLRF) control system which can provide high precision RF driving signal based on meeting the amplitude and phase stabilization requirement. Through Feed-Forward operation, accurate phase adjustment and amplitude adjustment are realized inside the pulse, to realize the precision and automation of phase-inversion, amplitude stabilization, phase stabilization, and wave-form adaptation matching. An LLRF System integrated with feed-forward control and vector modulation output was designed and built, and the long-term working stability of the LLRF system was verified during a new 50MW S-band Klystron conditioning progress.

Real-time Adaptive Control of Electric Vehicle Drives using Artificial Neural Networks

This study examines the use of artificial neural networks (ANNs) in real-time adaptive control for electric vehicle (EV) propulsion systems, with the goal of enhancing performance and efficiency. The neural network-based control system is developed and validated using experimental data that includes vehicle speed, battery temperature, battery voltage, and motor temperature. The neural network demonstrates precise control output predictions by effectively adapting to dynamic changes in input parameters, exhibiting a remarkable level of responsiveness to diverse operating settings. The analysis of the experimental findings reveals a strong correlation between the expected and actual control values, confirming the system's dependability and effectiveness in managing torque and voltage instructions for the electric vehicle (EV). The performance indicators, such as mean squared error (MSE), R-squared, mean absolute error (MAE), and root mean squared error (RMSE), demonstrate a small difference between the anticipated and actual values, indicating that the system has a high level of accuracy and predictive capacity. Furthermore, the system displays remarkable responsiveness to changes in velocity, battery temperature, and voltage, showcasing its capacity to adjust to different driving situations while still staying within acceptable levels of fluctuation. This research highlights the capacity of artificial neural networks (ANNs) to facilitate accurate and flexible control systems for electric vehicles (EVs), representing a substantial advancement in improving the performance, efficiency, and adaptability of electric vehicle propulsion in sustainable transportation systems. The neural network-based control system has been proven to be accurate, responsive, and reliable. This highlights its potential to revolutionize future electric vehicle (EV) technologies and contribute to advancements in real-time adaptive control strategies for environmentally friendly transportation systems.

Learning-based Integrated Cooperative Motion Planning and Control of Multi-AUVs

This paper introduces a learning-based solution tailored for the integrated motion planning and control of Multiple Autonomous Underwater Vehicles (AUVs). Tackling the complexities of cooperative motion planning, encompassing tasks such as waypoint tracking and self/obstacle collision avoidance, becomes challenging in a rule-based algorithmic paradigm due to the diverse and unpredictable situations encountered, necessitating a proliferation of if-then conditions in the implementation. Recognizing the limitations of traditional approaches that are heavily dependent on models and geometry of the system, our solution ofers an innovative paradigm shift. This study proposes an integrated motion planning and control strategy that leverages sensor and navigation outputs to generate longitudinal and lateral control outputs dynamically. At the heart of this cutting-edge methodology lies a continuous action Deep Reinforcement Learning (DRL) framework, specifically based on the Twin Delayed Deep Deterministic Policy Gradient (TD3). This algorithm surpasses traditional limitations by embodying an elaborated reward function, enabling the seamless execution of control actions essential for maneuvering multiple AUVs. Through simulation tests under both nominal and perturbed conditions, considering obstacles and underwater current disturbances, the obtained results demonstrate the feasibility and robustness of the proposed technique.

Conditions for uniform ensemble output controllability, and obstruction to uniform ensemble controllability

Conditions for uniform ensemble output controllability, and obstruction to uniform ensemble controllability

МЕТОД ИЗМЕРЕНИЯ ДИАМЕТРА ИЗДЕЛИЙ С ПОМОЩЬЮ СТЕРЕОЗРЕНИЯ ПРИ ИХ ИЗГОТОВЛЕНИИ НА ТОКАРНОМ СТАНКЕ

Output control of turning products is one of the most important production tasks. Typically, control is carried out manually using contact tools – calipers and micrometers, which reduces quality and slows down production. Also, contact control is not always possible due to the dimensions or characteristics of the product. The purpose of the article is to develop and describe a possible method for a noncontact detail measuring. The article discusses an optical method for measuring the diameter of a product made on a lathe using a stereo camera and a laser. Equipment calibration algorithms for the measurement process are described. An experiment was conducted to demonstrate the performance of the proposed algorithm.

Reinforcement Learning in the Task of Spherical Robot Motion Control

The output control algorithm is a pair of trained neural networks — actor and critic, where the actor-network is used to obtain the control torques applied to the robot wheel and the critic-network is only involved in the learning process. The results of the training are shown below, namely how the robot performs the motion along ten arbitrary trajectories, where the main quality functional is the average error magnitude over the trajectory length scale. The algorithm is implemented using the PyTorch machine learning library.

Resilient Output Control of Multiagent Systems With DoS Attacks and Actuator Faults: Fully Distributed Event-Triggered Approach

Resilient Output Control of Multiagent Systems With DoS Attacks and Actuator Faults: Fully Distributed Event-Triggered Approach

Admissible H$_\infty$ Control of Fuzzy Singular Fractional Order Multi-Agent Systems With External Disturbances

This brief consider the problem about admissible consensus of fuzzy singular fractional order multi agent systems (FSFOMAS). By designing a new distributed fuzzy dynamic output control strategy, the coupled system achieves admissible while satisfying <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty$</tex-math> </inline-formula> performance. Then, when the fuzzy models reduce to ordinary fractional order multi agent systems (FOMAS), a new sufficient condition for determining system consensus is given. The above results all depend only on the eigenvalues of the Laplace matrix and the state matrix of the system and consist of linear matrix inequalities (LMIs). Finally, a numerical example and a practical circuit example can demonstrate the feasibility and validity of the theorems. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Due to the unique memorability of fractional orders, their application to fuzzy multi-agent systems will bring system performance metrics closer to reality. This paper investigates the stabilization of singular fuzzy fractional-order multi-agent systems with the perturbation case, the pulse case. We know that in practical applications a single variable does not accurately describe the phenomenon. Therefore we have introduced the concepts of multi-agent, fuzzy, singular and fractional orders in order to describe the system model more accurately. The main objective is to bring the system into equilibrium in the closest possible approximation to reality. The performance metrics of the system are optimised to bring the system to an optimal state. Finally, two examples are used to illustrate the validity of our theorems.

THE SIMULATION MODEL OF AN AUTONOMOUS ENERGY SUPPLY SYSTEM FOR HIGHWAY INFRASTRUCTURE OBJECTS

The presence of a centralized power supply with the appropriate infrastructure and an extensive distribution network with significant technological losses not only causes increased risks, but also calls into question the quality and reliability of the energy supply of remote objects. The use of small power plants based on renewable energy sources can solve the problem of power supply of transport infrastructure objects (public transport stops, pedestrian crossings, traffic control elements, etc.). However, the expediency of using one or another energy source requires simulation modeling of the parameters of these power supply systems. The purpose of this study is to develop a simulation model of the autonomous energy supply system of road infrastructure objects and to check its functioning in real conditions. The article describes the structural simulation model and presents the characteristics of its components. The order of functioning of the constituent elements and the peculiarities of their interaction are given. Experimental modeling of the dependences of the output power of the photovoltaic module on the voltage maintained at its output was carried out, and the obtained results were summarized. The developed model makes it possible to implement the mode of maintaining maximum performance thanks to the introduction of feedback to control the value of the input voltage of the converter, which is compared with the calculated (set) value of the voltage, calculated from the data of the actual load current and short-circuit current of the photovoltaic module for different values of light flux. The result of the comparison, with the appropriate sign, is sent to the proportional-integral regulator, the output control effect of which is the regulation of the output voltage of the converter and, related to it, the charging current of the battery, which, therefore, leads to a change in the input current and ensures the maintenance of the set voltage at solar cell outputs. Under this condition, its output current is directly proportional to the amount of solar radiation. It is also established that the selection of the minimum required capacity of the photovoltaic panel must be carried out taking into account the most unfavorable scenario regarding weather conditions and the season of the year in order to ensure the maximum charge of the battery.

Development of an output management model for a branch of an engineering corporation

The model of output control in a corporation, carried out by its top manager (Chief), is considered. The head of the branch of the corporation (Head) controls the subordinate plant headed by the Director. A corporation’s branch output is affected by random external influences. The Head knows exactly the maximum possible volume of outsourcing production at the branch level. But he does not know the maximum possible volume of production (potential) in the plant. The Adviser helps the Head to eliminate this uncertainty. For his part, the Director knows exactly plant’s potential. At the same time, the Chief does not know this potential, nor the possibilities of outsourcing. Thus, the Head can manipulate branch output to influence the decisions of the Chief in order to increase his own promotion. Therefore, the Chief needs to learn how to control the Head in order to maximize branch output. Similarly, the Director can manipulate plant’s output to influence the Head’s decisions about his own denomination. Therefore, the Head needs to control the Director in order to increase plant’s output. A complex control mechanism has been found, in which total branch output is maximal. The use of such a mechanism is illustrated by the example of the modernization of freight railway platforms.

Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations

Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations

New event based timing system for the Taiwan Light Source

The Taiwan Light Source (TLS) is a third generation synchrotron light source that has been in operation since 1993. However, the legacy timing system is obsolete and needs to be upgraded to an event based timing system. This upgrade is intended to replace obsolete components and improve functionality. The new timing system must coordinate the operation of the linac, the White circuit based booster synchrotron, and the storage ring for beam generation, injection, extraction, and accumulation, while also supporting top up operation of the storage ring. To achieve this, a cPCI (CompactPCI) based EPICS IOC (Input Output Controller) and expandable fanless embedded computers have been adopted for the new TLS timing system, replacing the existing VME-based ILC (Intelligent Local Controller) to provide an easy to maintain control environment. However, the resonant excitation of the booster magnets with the event system requires special attention in the design and implementation phases. This paper summarizes the design ideas and implementation process for addressing this issue.

Influence of Wind-Turbine-Generator Power Control on the Performance of a Virtual Synchronous Machine

Implementation of renewable energy sources (RESs) in power systems can reduce the dependence on fossil-fuel-based thermal power generation systems. At the same time, however, the system inertia decreases as synchronous generators decrease; this is crucial for maintaining the stability of the power system. Virtual inertia control (VIC) can regulate the output of an inverter-based resource (IBR) by increasing the inertia. For a wind turbine generator (WTG), output control factors such as pitch angle control and maximum power point tracking (MPPT) significantly affect the performance of the VIC. This paper theoretically clarifies that the pitch angle control contributes to improvements in the performance of the VIC and helps avoid a loss of operation of the WTG in frequency drop events by analyzing the movement of the operational point of the WTG based on the physical characteristic of the WTG and control characteristics of the pitch angle control and MPPT; an electromagnetic transient (EMT) simulation, performed to verify the analysis, is also presented.

Optimization of load frequency control using grey wolf optimizer in micro hydro power plants

Micro hydro power plants (MHPP) is one of the renewable energy that can be utilized as a distributed generation with controllable power output. One common issue in MHPP systems is the non-constant rotation of the generator caused by load fluctuations. This instability leads to variable frequencies, which can potentially harm electrical equipment. To address this problem, the volume of water entering through the governor can be adjusted to synchronize the turbine and generator rotation with the load. This approach helps dampen frequency oscillations and ensures that the system operates within desired limits. Therefore, there is a need for technology that can enhance the performance of micro hydro power plant units, specifically load frequency control (LFC). This research proposes the application of the grey wolf optimizer (GWO) algorithm to optimize the PID controller parameters for MHPP LFC. MHPP has been modeled in both isolated and grid-connected modes using Simulink MATLAB R2020a. The best cost function value for an isolated mode system was obtained with ISEim, yielding a value of 0.067653, while for a grid-connected mode system, it was achieved with ISEgm, with a value of 0.015861. The results of the frequency deviation response performance of the LFC using GWO indicate that the fastest settling time was achieved with the cost function ITAEim in isolated mode, and with IAEgm in grid-connected mode. The cost function that produces the smallest peak overshoot and peak undershoot parameter values varied depending on changes in the system load.

Multifunctional optical logic device based on nanoscale rectangular ring resonator

Integrated optical logic devices are essential building blocks for implementing all-optical arithmetic and logic unit. In this paper, an ultra-compact multifunctional optical logic device consisting of a rectangular ring resonator coupled with two parallel metal–insulator–metal waveguides is presented. The transmission characteristics of the structure are analyzed in detail via temporal coupled-mode theory. The finite-difference time-domain simulation results reveal that multiple logic functions can be implemented with the aid of the wavelength division multiplexing technique at different output ports. Specifically, all seven basic types of logic gates, half-adder, half-subtractor, and 2*4 decoder can be implemented by monitoring the transmission of through and drop ports at different wavelengths. More importantly, among these functions, six logic gates (OR, XNOR, NAND, NOR, XOR, and AND) and half-adder functions can be performed simultaneously; the NOT logic operation is performed with controllable output ports and selectable working wavelengths; the half-subtractor and 2*4 decoder functions can be operated simultaneously. The proposed logic device is characterized by a small area overhead, multifunctionality, fast response time, and ultrahigh-speed information processing. It may potentially be applied in on-chip universal and parallel photonic computing units.

In-field experimental study and multivariable analysis on a PEMFC combined heat and power cogeneration for climate-adaptive buildings with taguchi method

Due to overwhelming advantages in high power density, stability in long-term storage and clear by-product water, application of hydrogen energy in buildings has attracted global interests for sustainable and low-carbon transformation, especially with the fast technology development of proton exchange membrane fuel cell (PEMFC) combined heat and power (CHP) cogeneration system. However, the cost-effective operating control of PEMFC CHP cogeneration system has not been investigated, comprehensively considering intermittence and stochasticity of building energy demands in different climate regions under extreme climates. In this study, in-field experimental study following the orthogonal method is conducted for underlying mechanism analysis of operating parameters on electric power, total power, and electric/thermal (E/T) power ratio of a PEMFC stack, considering energy losses by convection, radiation and exhausted reactant gas flow. Sensitivity analysis of operating parameters on PEMFC output performances is conducted based on Taguchi Method. For climate-adaptive applications of PEMFC CHP cogeneration systems in Guangzhou (cooling-dominated area) and Beijing (heating-dominated area), two operating strategies with electricity- and heat-dominated outputs have been proposed and compared. Results indicate that, the PEMFC output performances are influenced by internal factors, including reaction rate, substance transportation, membrane hydration level and energy losses. Electric power and total power are mainly dependent on coolant inlet temperature, inlet gas pressure and coolant flux, while E/T power ratio is mainly controlled by inlet coolant temperature, inlet gas pressure and cathode stoichiometric ratio. Furthermore, based on the proposed cost-effective operating control (the electricity-dominated output control strategy under extreme hot weather in Guangzhou and heat-dominated output control strategy under extreme cold weather in Beijing), the PEMFC could save 0.246 kg hydrogen with 2.137 × 103 kJ surplus thermal energy one day in Guangzhou, and save 2.763 kg hydrogen with 3.527 × 103 kJ surplus electric energy one day in Beijing. This study could provide a guideline for operating parameter selections of PEMFC CHP cogeneration system in variable climate areas.

HARDWARE DESIGN OF THE TOUCHLESS HAND CODE AND CONVOLUTIONAL NEURAL NETWORKS - BASED AUTOMATIC DOOR SECURITY SYSTEM

The spread of viruses and bacteria through touching door surfaces is essential in maintaining public hygiene and health. In this context, a hand-coded touchless automatic door hardware design has been developed to reduce the spread of diseases through touch. This research aims to create a plan that includes interface development and hardware design to open and close doors automatically without contact. In this research, the automatic door hardware response is tested based on the numeric input from the hand code represented by the numeric database. The input and output control is connected to Python's graphical user interface (GUI). The GUI system design involves tools to connect the Python programming language and the Arduino microcontroller. Based on the experimental results, the hardware design of the automatic door security system based on hand code and Convolutional Neural Networks functions appropriately.

Spatially Structured Optical Pump for Laser Generation Tuning.

The goal and essential parameter of laser light conversion is achieving emitted radiation of higher brightness. For many applications, the laser beam must have the highest available beam quality and highest achievable power. However, lasers with higher average power values usually have poorer beam quality, limiting the achievable brightness. Here, we present a method for improving the beam quality by using a spatially structured optical pump for a membrane external cavity laser resonator. An increase in brightness is achieved under fixed focusing conditions just by changing the pump intensity profile. A controllable output laser mode can be achieved by using a dynamically changing pump pattern.

Modelling, Simulation and Implementation on dSpace 1103 of the Direct Power Control in a Three-Phase Shunt Active Power Filter System

This article describes a control method called "direct power control" designed specifically for parallel active power filters. The purpose of this method is to attenuate harmonics in the supply current and offset reactive power problems. The main goal is to bring the active power and reactive power back to the reference values through hysteresis control. The output of the hysteresis controller is combined with the switching table to regulate active and reactive power in real time by determining the optimal switching configuration of the inverter. This study proposes a novel switching table design based on analyzing the impact of the inverter switching vector on the instantaneous reactive and active power derivatives. The goal is to reduce the number of commutations by eliminating zero vectors while maintaining the required DC bus voltage using anti-windup techniques based on PI controllers.