Simple Control Research Articles

Nature and structure of NTA Traditional Homeopathically Manufactured Medicines.

Background: Research using several different methods has demonstrated the materiality, including nanoparticles (NPs) and molecular shapes, in High Homeopathic Potentizations (HHPs). This presentation is a summary of all the evidence gathered by the DynHom research project. Methods: We used the Nuclear Magnetic Resonance (NMR), Nano Tracking Analyzer (NTA), Electronic microscopy (SEM-EDX), Infrared spectroscopy (FTIR), pH measurements to examine dilutions of commonly used homeopathic medicines and controls. The homeopathic medicines tested were specially prepared according to the European pharmacopoeia standards. We compared the homeopathic dilutions/dynamizations with simple dilutions and solvents controls. Results: We observed specific NMR profiles, the presence of particles with specific size distribution and electric fields, dry material (crystals) with a specific molecular structure even more obvious in HHPs. Conclusion: Homeopathic medicines do contain particles with a specific size distribution even in HHPs diluted beyond the Avogadro/Loschmidt limit. They also contain molecules in particular concentrations according to each source material. This specificity can be attributed to the manufacturing and potentization process. This material demonstrates that the step-by-step process (dynamized or not) does not match the theoretical expectations in a dilution process. The starting material, the type of containers and dilution/dynamization method influence the nature and concentration of these NPs.

Mechanical intelligence simplifies control in terrestrial limbless locomotion.

Limbless locomotors, from microscopic worms to macroscopic snakes, traverse complex, heterogeneous natural environments typically using undulatory body wave propagation. Theoretical and robophysical models typically emphasize body kinematics and active neural/electronic control. However, we contend that because such approaches often neglect the role of passive, mechanically controlled processes (those involving "mechanical intelligence"), they fail to reproduce the performance of even the simplest organisms. To uncover principles of how mechanical intelligence aids limbless locomotion in heterogeneous terradynamic regimes, here we conduct a comparative study of locomotion in a model of heterogeneous terrain (lattices of rigid posts). We used a model biological system, the highly studied nematode worm Caenorhabditis elegans, and a robophysical device whose bilateral actuator morphology models that of limbless organisms across scales. The robot's kinematics quantitatively reproduced the performance of the nematodes with purely open-loop control; mechanical intelligence simplified control of obstacle navigation and exploitation by reducing the need for active sensing and feedback. An active behavior observed in C. elegans, undulatory wave reversal upon head collisions, robustified locomotion via exploitation of the systems' mechanical intelligence. Our study provides insights into how neurally simple limbless organisms like nematodes can leverage mechanical intelligence via appropriately tuned bilateral actuation to locomote in complex environments. These principles likely apply to neurally more sophisticated organisms and also provide a design and control paradigm for limbless robots for applications like search and rescue and planetary exploration.

Hybrid Energy Generation System with Brushless Generators

Important technical and financial hurdles exist when attempting to extend the power system to remote areas. Decentralized power generation utilising renewable energy sources (RES) has been promoted and is being further investigated as a result. This project showcases a microgrid architecture that uses brushless generators and a single voltage source converter (VSC). Wind and solar photovoltaic arrays are two of the renewable energy sources that power the microgrid system. But to keep the system reliable, there is also a battery energy storage system (BESS) and a diesel generator set. The simplified control and decreased number of switching devices are two benefits of the suggested architecture. In the current architecture, DG is configured as an AC source. The DC connection of the VSC is connected to the wind generator and the solar PV array, both of which are DC sources. Additionally, the BESS is utilised at the DC connection to assist with the dynamic instantaneous power balancing. In addition to integrating systems, VSCs may reduce power quality issues including harmonic currents, imbalance loads, and regulate voltage. To showcase all the aspects of the proposed system, we offer a diverse range of matlab/simulink simulation results.

Analysis and Control of Chaos in Permanent Magnet Synchronous Motor

This paper explores the chaotic dynamics exhibited by a Permanent Magnet Synchronous Motors (PMSM) through an analysis of Lyapunov exponents and equilibrium points. Subsequently, the study focuses on controlling the motor's chaotic behavior under specific parameter conditions using a straightforward controller. The approach employed in this paper involves utilizing a single-state feedback controller as the resolution method. The derived control law enables the stabilization of the motor's state around a reference state, even in the presence of parameter uncertainties, thereby preventing chaotic behavior. To illustrate the proposed method, numerical simulations were conducted in MATLAB, showcasing the practical application of this approach. The simulation results demonstrate the success of the controller used.

The Role of PLC in Automation, Industry and Education Purpose: A Review

Programmable logic controller (PLC) plays a significant role in every era, either it is in field of automation, industry or educational purposes. As the demand for automation grows exponentially, control systems need to be easy to program, flexible, reliable, and cost-effective. This article provides an overview of PLC implementation in automation, industry, and education. This article reviews an investigation into the role of PLC in automation, industrial, and educational goals. PLC has its own limitations, but research shows that it has more benefits than limitations. After survey it will see that the PLC can be used in any application, either it is simple or complex control systems. The analysis conducted and focuses on the concept, operation, advantages and practical applications of PLC, as well as comparison with other control systems.

Research on Teleoperated Virtual Reality Human-Robot Five-Dimensional Collaboration System.

In the realm of industrial robotics, there is a growing challenge in simplifying human-robot collaboration (HRC), particularly in complex settings. The demand for more intuitive teleoperation systems is on the rise. However, optimizing robot control interfaces and streamlining teleoperation remains a formidable task due to the need for operators to possess specialized knowledge and the limitations of traditional methods regarding operational space and time constraints. This study addresses these issues by introducing a virtual reality (VR) HRC system with five-dimensional capabilities. Key advantages of our approach include: (1) real-time observation of robot work, whereby operators can seamlessly monitor the robot's real-time work environment and motion during teleoperation; (2) leveraging VR device capabilities, whereby the strengths of VR devices are harnessed to simplify robot motion control, significantly reducing the learning time for operators; and (3) adaptability across platforms and environments: our system effortlessly adapts to various platforms and working conditions, ensuring versatility across different terminals and scenarios. This system represents a significant advancement in addressing the challenges of HRC, offering improved teleoperation, simplified control, and enhanced accessibility, particularly for operators with limited prior exposure to robot operation. It elevates the overall HRC experience in complex scenarios.

Extending Closed-Loop Control of Two-Dimensional Supersonic Boundary-Layer Instabilities Beyond a Single Operating Point

This paper investigates two control strategies to maintain low perturbation amplitudes of second Mack mode instabilities in a two-dimensional boundary layer with freestream velocity variations of ±5% around M∞=4.5: the multimodel synthesis and the gain scheduling method, both based on the structured mixed H2/H∞ synthesis to handle simultaneously, in an optimal way, the problems of nominal performance, stability, and performance robustness. The multimodel synthesis is based on a single linear-time invariant (LTI) controller optimized over multiple operating points, whereas the gain scheduling method results in a control law based on the interpolation of multiple LTI controllers designed at the various operating points. Both methods are compared with simple LTI controllers based solely on the nominal operating point in two sensor–actuator architectures: in feedforward (respectively, feedback) the estimation sensor is located upstream (respectively, downstream) of the actuator. In the feedforward case, significant performance loss is observed in off-design conditions, regardless of the method used. In the feedback case, multimodel synthesis enhances slightly performance robustness (but improvement is weak because of the wide range of freestream velocity variation), while the gain scheduling approach succeeds in strongly reducing the perturbation amplitude over the entire range of variation.

Time-Delay Control Scheme with Adaptive Fixed-Time Convergent Super-Twisting Fractional-Order Nonsingular Terminal Sliding Mode for Piezoelectric Displacement Amplifier

Piezoelectric displacement amplifiers (PDAs) have been widely used in precision positioning fields. However, the inherent hysteresis and creep nonlinear effect of piezoelectric actuators (PEAs) and time-varying lumped disturbances bring extreme challenges to the precise motion control of PDAs. Although various control schemes based on PEAs have been developed and have shown significant results. However, due to the high sensitivity of precision positioning to environmental variations, the development and identification of accurate models and the control timeliness often become obstacles in engineering. To realize precise motion control of PDAs under complex lumped disturbances, a new time-delay control scheme (AFSTA-FONTSM) using an adaptive fixed-time convergent super-twisting algorithm (AFSTA) and a fractional-order nonsingular terminal sliding mode (FONTSM) is proposed. Specifically, the time-delay information obtained by time-delay estimation technology is used to estimate the lumped dynamic characteristic of the system, thus establishing a simple control framework without a system dynamic model. FONSTM is constructed as a sliding mode manifold, and satisfactory error dynamic characteristic is obtained. A new AFSTA is designed as the reaching law in the sliding mode phase. AFSTA has fixed-time convergence when the upper bound of lumped disturbances exists, which ensures the control timeliness. Benefiting from the newly designed adaptive algorithm, the upper bound value of lumped disturbances is no longer needed to determine the control gains, which effectively prevents overestimation of the control gains. Correspondingly, the convergence time of AFSTA is estimated, and the stability of the closed-loop system is analyzed by the Lyapunov theory. Three existing time-delay control schemes, namely MSTA-FONTSM, AMSTA-FONTSM, and ASTA-FONTSM are selected, and four scenes are designed for comparative experiments. The experimental results show that MSTA-FONTSM has the worst control performance among the four control schemes. For the step, and continuous cosine trajectories with periods of T=1s and T=2s, the root-mean-square error of the proposed AFSTA-FONTSM is reduced by 56.86%, 54.03%, and 50.24% compared with MSTA-FONTSM. For disturbance experiments under different loads, the control performance of the proposed AFSTA-FONTSM is still superior to the other three control schemes without load.

Economic Model-Predictive Control of Building Heating Systems Using Backbone Energy System Modelling Framework

Accessing the demand-side management potential of the residential heating sector requires sophisticated control capable of predicting buildings’ response to changes in heating and cooling power, e.g., model-predictive control. However, while studies exploring its impacts both for individual buildings as well as energy markets exist, building-level control in large-scale energy system models has not been properly examined. In this work, we demonstrate the feasibility of the open-source energy system modelling framework Backbone for simplified model-predictive control of buildings, helping address the above-mentioned research gap. Hourly rolling horizon optimisations were performed to minimise the costs of flexible heating and cooling electricity consumption for a modern Finnish detached house and an apartment block with ground-to-water heat pump systems for the years 2015–2022. Compared to a baseline using a constant electricity price signal, optimisation with hourly spot electricity market prices resulted in 3.1–17.5% yearly cost savings depending on the simulated year, agreeing with comparable literature. Furthermore, the length of the optimisation horizon was not found to have a significant impact on the results beyond 36 h. Overall, the simplified model-predictive control was observed to behave rationally, lending credence to the integration of simplified building models within large-scale energy system modelling frameworks.

Cyclic Impact Test with the Hopkinson Bar: Application to Granite

A laboratory scale cyclic impact loading test was developed by modifying a Hopkinson Bar test setup. The modifications involve placing a special shank piece between the striker and the rest of the setup. The shank transmits the impact loading and enables the use of compressed air for rapid reloading of the striker. The short shank is in direct contact with the specimen, i.e., there is no long input bar. With this configuration residual wave motion and reloading of the specimen is avoided. Behind the striker an output bar and momentum trap bar are placed for specimen loading measurement and removal of the wave motion in the system, respectively. The trap bar is stopped by a pneumatic actuator, which also resets the bars and the specimen before the next impact loading. The compressed air flow driving the striker is controlled by high-speed electropneumatic valves connected to a control unit and operated in simple open-loop control. Numerical simulations of both the striker motion by compressed air and dynamic loading wave propagation during impact were used in the design phase as well as setting up the test parameters. The test setup is able to produce stable cyclic impact loading at a frequency of up to 10 impacts per second with striker velocity up to 9 m/s. The feasibility of the test method is demonstrated by providing data from cyclic Brazilian disc experiments on Balmoral Red granite at both impact and quasi-static cyclic loading.

A Real-Time Control Policy to Achieve Maximum Throughput of an Online Order Fulfillment Network

Several major companies operate large online order fulfillment systems to ship goods from fulfillment centers through a distribution network to customer destinations in response to purchase orders. These networks make several types of decisions in real-time to serve customers. First, when a customer places an order, when and where (which fulfillment center) is it fulfilled from? Second, once an order has been packaged, how is it moved through the network to get to the customer? Making optimal decisions can yield significant cost savings or improvements in customer service. Unfortunately, these are large optimization problems, and are furthermore subject to uncertainty in the products and destinations of customer orders and the inventory replenishment of the fulfillment centers. This uncertainty makes the problem difficult to solve to optimality. Although the problem can be modeled as a Markov decision process, solving it exactly using standard computational methods is not possible due to the curse of dimensionality. We propose an alternative approach to this problem. We define a relatively simple real-time control policy and prove that it serves all customer demand if at all possible. This proof is achieved using Lyapunov drift techniques to relate the real-time control performance to the average performance necessary to serve all customers on average. Correspondingly, we characterize the average network performance, which may be used for network topology design while the control policy adapts to real-time stochasticity. We demonstrate the performance and stability properties on a numerical example based on hundreds of Amazon facility locations in the United States. The max-pressure control and greedy policies perform similarly at low demands, but at higher demand the throughput properties of the max-pressure control manifest as improvements in throughput and customer service metrics. Funding: Financial support from the National Science Foundation [Grant 1935514] is gratefully acknowledged. Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2023.0096 .

Design of Digital Control System for Line Following Robot

Design of mobile robots has become an increasingly growing trend in the technology of modern times. They are very attractive engineering systems, not only because of many interesting theoretical aspects concerning kinematics, intelligent behavior and autonomy, but also because of applicability in many human activities. A typical example is the line following robot (LFR). In order for a LFR to function effectively, it must demonstrate excellent line tracking control. This is achieved by having accurate and responsive control algorithms as well as high precision color sensor systems. This paper proposes a system to show that good line tracking performance can be achieved with moderately simple digital control algorithms. The platform used is a differentially driven wheeled robot constructed using the Lego Mindstorms components. The simulation models are presented and analyzed using MATLAB Simulink . The main programming environment is the EV3 Software.

Design, development, integration and evaluation of hybrid fuel cell power systems for an unmanned water surface vehicle

When fuel cells are used to power mobile applications, such a vehicles, hybridization with batteries is normally required. Depending on the electronic coupling between the energy sources the power plants can have passive or active configurations. Hybrid fuel cell-battery power plants with active power control flow have some advantages. For example, they can decrease the total energy losses, while improving the fuel cell performance, extending its lifetime. Power plants with DC/DC converters show low specific energy ratios, but with a superior energy management. In the present research, the hybrid power plant for an unmanned aquatic surface vehicle (USV) based on a PEM fuel cell and a Li-ion battery is developed. Active (with DC–DC converters) or passive architectures are analyzed by numerical simulations and experimental tests. Good results are obtained for the active power plant, where the peak power demands are managed by the battery pack while the fuel cell power remains constant thanks to the DC-converter control. The study shows that a simple control algorithm (no optimal) can help to extend the USV autonomy above 12h in calm waters with a specific energy of 85.6Whkg-1.

Facile Fabrication Technique of Polymeric Ionic Liquids‐Coated Core–Shell Nanoparticles for Polymer Electrolyte Membranes

AbstractNanoparticles and nanofibers are widely used as components of polymer electrolytes for membranes in fuel cells, and many surface modification methods are reported. However, some fabrication techniques are complicated, and it is necessary to develop a simplified and precise control method. Herein, a facile fabrication method is reported for core–shell nanoparticles hierarchically coated with polymeric ionic liquids (PIL) and hydrophobic polymers as a material for polymer electrolytes. A hierarchical polymer layer on the surface of the SiO2 nanoparticles is easily constructed by repeating the facile polymer‐coating technique based on precipitation polymerization several times. The highest proton conductivity of the core–shell nanoparticles is 1.3 × 10−2 S cm−1 at 80 °C and 95% relative humidity. Although the hydrophobic polymers coated as a protective layer reduce the proton conductivity, the formation of the PIL enhances the proton conductivity in various temperature and humidity environments. Therefore, the proposed method enables the facile fabrication of polymer layers with multiple functions, such as a proton‐conductive PIL layer and hydrophobic polymer layers as protective layers on the surface of the nanoparticles. Furthermore, they are expected to be applied to energy supply and gas separation, including polyelectrolytes, for the realization of a sustainable society.

Laser beam steering of 532 nm using a power-efficient focal plane array

Laser beam steering is important for classical and quantum information processing. On-chip beam steering is a major motivation for developing large-scale photonic integrated circuits such as optical phased arrays. A major challenge for such arrays is to simultaneously control a large number of on-chip phase shifters, which requires a complicated analog control algorithm and rapidly increasing power consumption. We report a green light (532 nm) 1 × 16 focal plane array photonic integrated circuit with simple control and low power consumption. Fabricated on a silicon nitride platform, the focal plane array achieves angular beam steering over a 10° field of view, with ultra-low electrical power consumption (4 × 3.1 mW).

An Advanced Solution Based on Machine Learning for Remote EMDR Therapy

For this work, a preliminary study proposed virtual interfaces for remote psychotherapy and psychology practices. This study aimed to verify the efficacy of such approaches in obtaining results comparable to in-presence psychotherapy, when the therapist is physically present in the room. In particular, we implemented several joint machine-learning techniques for distance detection, camera calibration and eye tracking, assembled to create a full virtual environment for the execution of a psychological protocol for a self-induced mindfulness meditative state. Notably, such a protocol is also applicable for the desensitization phase of EMDR therapy. This preliminary study has proven that, compared to a simple control task, such as filling in a questionnaire, the application of the mindfulness protocol in a fully virtual setting greatly improves concentration and lowers stress for the subjects it has been tested on, therefore proving the efficacy of a remote approach when compared to an in-presence one. This opens up the possibility of deepening the study, to create a fully working interface which will be applicable in various on-field applications of psychotherapy where the presence of the therapist cannot be always guaranteed.

Optical switching will innovate intra data center networks [Invited Tutorial

Reflecting the recent slow-down in Moore’s law and the proliferation of artificial intelligence/machine learning workloads, the performance and energy consumption of networks are becoming barriers in high-performance computing (HPC) and data centers. Optical switches are expected to break these barriers, and indeed their introduction has recently commenced in data centers. This paper discusses how optical switching technologies can innovate future intra data center networks. Hyperscale data centers are much bigger in scale, and network requirements are slightly different from those of HPC. This paper focus on data center networks, since the impact of optical technologies will be more significant in data centers than in HPC. In addition to the scale issue, important metrics to be considered for network design are traffic characteristics and latency, both of which are highlighted in this paper. For hybrid (electrical packet and optical circuit) switching networks, the target latency for the optical circuit switch network (connection setup/teardown time) is shown to be around 10 µs, and the needed technologies are clarified and verified by experiments. The optical switch can simplify the present multi-tier switching network above tier-1 switches into a single tier configuration, which is possible with the development of efficient large port count optical switches. Among the different switching architectures, combining the different dimensions of space and wavelength is shown to be one of the best solutions. Fast switching needs fast device response time. Si photonics devices using Mach–Zehnder interferometers or ring-resonator-based switches and tunable filters are the most promising candidates; they offer cost-effective mass-production and fast operation and so are excellent candidates for the optical switches envisaged. Another critical technology to maximize the benefits of optical switches is a simple and low-latency control mechanism. Different approaches have been suggested as summarized in this work. Among them, harnessing optical switch parallelism is a unique technique that matches recent advances in electrical switch chips. A fast control network is realized by using a fully decentralized and asynchronous control mechanism. A hyperscale data center offers a wide variety of services, and no one system fits all needs. Optimization of parameters is an important task for maximizing the impact of optical switching in different kinds of data centers.

Dual magnet solenoid actuator: Practical applications

We demonstrate several practical applications of a novel linear solenoid actuator design previously proposed to create a solenoid micropump which can be used in portable microfluidic systems. The proposed solenoid actuator design is extended to a system that can apply a constant force with a longer stroke and apply a higher force. It also demonstrates effective mini-train operation with easy and simple control, a spring-loaded linear servo system that solves the classic non-linear control problem, and droplet dispensing with accurate and fast control, showing its potential as a compact microfluidic solenoid micropump capable of precisely handling small volumes of liquid. Applications to digital microfluidic and flow-focusing microchannel systems have also been successfully demonstrated. We hope that this study will promote the development of various actuators for microfluidics and contribute to the broader application of microfluidics in more fields.

Anchoring single-atom Cu on tubular g-C3N4 with defect engineering for enhanced Fenton-like reactions to efficiently degrade carbamazepine: Performance and mechanism

Efficient construction of the active site is crucial for Fenton-like reactions. In this study, tubular carbon nitride with different vacancies (V-TCN) was prepared by simple temperature control. The affinity of the nitrogen atom generated by the carbon vacancy was used to anchor single-atom Cu, which achieved the precise regulation of Cu, reduced agglomeration, and maximally exposed the active site to enhance the activation of H2O2. Density functional theory calculations revealed that the single-atom Cu anchored in the C2 vacancy exhibited the lowest formation energy and the shortest Cu-N bonds. The results showed that Cu/V550-TCN had excellent degradation performance for the hard-to-degrade carbamazepine over a wide pH range (pH = 5–11), and singlet oxygen was the main active species during the degradation process. Additionally, the redox cycles of Cu(I)/Cu(II) and Cu(II)/Cu(III) accelerated the Fenton-like reaction. Five possible degradation pathways for carbamazepine were proposed based on liquid phase mass spectrometry analysis. This study provides a new insight into the role of surface defects in regulating the active site to promote the Fenton-like reaction for the degradation of stubborn pollutants.

Energy Efficiency Improvement Using Simplified Dynamic Direct Voltage Maximum Torque Per Ampere Control for Interior PMSMs

An energy efficiency strategy is developed in this article using a simplified dynamic direct voltage MTPA speed control method for interior permanent magnet synchronous motors (IPMSMs). Finding an exclusive pair of the motor voltage angle and amplitude attains the MTPA trajectory tracking for each reference speed and/or torque condition, maintaining minimum current/power consumption and higher energy efficiency. This improvement is realized by taking into account the dynamic model of the motor, which makes the technology more precise in various operating conditions as contrary to existing literature. Further, the simplified dynamic strategy needs tuning of only couple of parameters compared to three times as much with the classical MTPA FOC technique. Moreover, a comparative study of the simplified dynamic direct voltage MTPA control methodology and the FOC strategy is carried out. Experimental outcomes and quantitative assessment prove that the simplified dynamic direct voltage MTPA control strategy is a worthy approach. Also, it is a substitution to the current MTPA methods and delivers higher efficiency for the IPMSMs' drive in modern industrial applications.