Developments in real-time control with Ethernet

Modern neuroscience research often requires the coordination of multiple processes such as stimulus generation, real-time experimental control, as well as behavioral and neural measurements. The technical demands required to simultaneously manage these processes with high temporal fidelity is a barrier that limits the number of labs performing such work. Here we present an open-source, network-based parallel processing framework that lowers this barrier. The Real-Time Experimental Control with Graphical User Interface (REC-GUI) framework offers multiple advantages: (i) a modular design that is agnostic to coding language(s) and operating system(s) to maximize experimental flexibility and minimize researcher effort, (ii) simple interfacing to connect multiple measurement and recording devices, (iii) high temporal fidelity by dividing task demands across CPUs, and (iv) real-time control using a fully customizable and intuitive GUI. We present applications for human, non-human primate, and rodent studies which collectively demonstrate that the REC-GUI framework facilitates technically demanding, behavior-contingent neuroscience research.Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Real-time pollution-based control of urban drainage and sanitation systems for protection of receiving waters The LIFE RUBIES project aims to develop an operational tool to reduce urban wastewater's impact on the natural envi-ronment by controlling water pollution in real time and deploying that tool in 2 cities. Real-time control will make it possible to direct and store urban wastewater to avoid pollution by relying on the coupling of sensors, models, and controllers.

This study proposes two contrasting neural control architectures that rely on the use of input–output information to compensate for the lack of knowledge about the robot model to achieve the prescribed tracking performance in the presence of joint angle and velocity constraints. First, an observer–controller zeroing neural network framework is formulated, which combines online estimation of the unknown model’s Jacobian with a trajectory tracking controller that implements joint angle and velocity constraints via a nonlinear map. Further, prescribed performance constraints are embedded within this architecture to achieve the desired transient and steady-state performance. This allows for the implementation of state and input constraints with the added benefits of superior transient and steady-state performance. Alternatively, a Koopman operator theoretic framework is also considered for real-time control of redundant manipulators subject to input constraints. An autoencoder-based neural architecture is employed to discover the bilinear Koopman model for manipulator dynamics in joint space using input–output data. This architecture is subsequently integrated with a feedforward neural network that maps the joint coordinates to end-effector Cartesian coordinates, which allows for the learning of highly accurate models with a significantly lower number of observable states compared to the previous studies. The learning architecture is then coupled with a zeroing dynamics neural controller, which offers a computationally inexpensive alternative to state-of-the-art nonlinear model predictive controllers whose computational burden might render real-time control infeasible. The low-dimensional learned model, when combined with the computationally inexpensive control policy, facilitates real-time control applications with improved tracking accuracy. Simulation studies of trajectory tracking are used to verify the efficacy of the proposed schemes.

In real-time wireless control systems, the freshness of information is crucial since performance highly depends on timely exchange of information between the plant and the controller. In this study, the age metric, Age of Control Process (AoCP), is proposed for real-time wireless control systems which is different from traditional Age of Information (AoI). The First Generate First Serve (FGFS) M/M/1/1 → M/M/1/1 tandem queue model is considered to present a closed form expression for computation of AoCP and testbed environment is employed for the analysis of AoCP measure. Our experiment results show that FGFS M/M/1/1 → M/M/1/1 queuing model is suitable to represent real-time control systems. In addition, the proposed definition provides closer results to the experiment results when compared with the traditional AoI definition. To the best of our knowledge, this is the first study that conducts information freshness measurements on real-time control testbed.

Additive Manufacturing is increasingly used in the development of new products: from conceptual design to functional parts and tooling. However, today, variability in part quality due to inadequate dimensional tolerances, surface roughness, and defects, limits its broader acceptance for highvalue or mission-critical applications. While process control in general can limit this variability, it is impeded by a lack of adequate process measurement methods. Process control today is based on heuristics and experimental data, yielding limited improvement in part quality. The overall goal is to develop the measurement science 1 necessary to make in-process measurement and real-time control possible in additive manufacturing. Traceable dimensional and thermal metrology methods must be developed for real-time closed-loop control of additive manufacturing processes. As a precursor, this report presents a review on the additive manufacturing control schemes, process measurements, and modeling and simulation methods as it applies to the powder bed fusion process, though results from other processes are reviewed where applicable. The aim of the review is to identify and summarize the measurement science needs that are critical to real-time process control. We organize our research findings to identify the correlations between process parameters, process signatures, and product quality. The intention of this report is to serve as a background reference and a go-to place for our work to identify the most suitable measurement methods and corresponding measurands for real-time control.

Real-time pollution-based control of urban drainage and sanitation systems for protection of receiving waters The LIFE RUBIES project aims to develop an operational tool to reduce urban wastewater’s impact on the natural environment by controlling water pollution in real time and deploying that tool in two cities. Real-time control will make it possible to direct and store urban wastewater to avoid pollution by relying on the coupling of sensors, models and controllers.

Real-time control is the trend for photoresist processing in the advanced lithography. In this paper we develop an in-situ ellipsometer integrated with a programmable thermal heating system, which could perform real-time monitoring and control for critical dimension (CD) latent image through the entire post-exposure bake (PEB) process. The inline ellipsometry measurements are fitted into an electromagnetic wave model built on the rigorous coupled-wave analysis (RCWA) theory for CD latent image characterization. Thereafter a real-time control scheme is proposed by applying the programmable thermal bake-plate. The experimental outcome demonstrates a significant improvement on the final CD result comparing to the conventional baking method.

We address the real-time robot control using Linux. The RT-Preempt Patch [1][2] renders Linux with a fully preemptible kernel. We call the system Realtime Linux. The advantages of Realtime Linux is that we can use most of the Linux libraries and create a real-time program API based on POSIX. The aim of this paper is confirming multithread real-time robot control using a multicore processor, considering processor affinity, i.e. each task is allocated to kin processor in preference to others at allocation time. More specifically, we consider an eye-in-hand robot system comprising a PA-10 robot arm and a USB camera under real-time control with a multicore processor by efficiently assigning the processor affinity. Results are demonstrated with data from a face tracking experiment.

On the basis of the rapidly increasing power, speed, and decreasing cost of the personal computer (microcomputer) it was felt that a real time data acquisition and control system could be configured quickly and very cost effectively. It was further felt that by using a high level or object-oriented programming language that considerable time and expense could be saved and at the same time increase system flexibility. This paper will attempt to address the desired system requirements and performance for both the control of the high power transmitters and for the data acquisition and presentation of the information.

A new Brushless Real Time Control (RTC) method for electric motors or generators is an evolution in Sensor-less control. Very different from any derivative of Field Oriented Control (FOC), RTC uniquely eliminates all control uncertainty, including the extraneous shaft connected resolver for the specific purpose of measuring speed-position (i.e., Sensor-less). Although modified versions of RTC can be used for control of any type of electric machine, the variable speed Brushless Wound-rotor [Synchronous] Doubly-fed Electric Machine System (BWRSDF) with its symmetrical circuit topology best explains the attractive attributes of RTC but more importantly, the BWRSDF has been theorized by experts to provide the highest efficiency, highest power density, highest torque density, and lowest cost of any electric machine with practical solutions for known issues of instability and a multiphase slip-ring assembly that only RTC successfully provides. In addition, BWRSDF uses off-the-shelf technology and readily available materials without precious rare earth permanent magnets.

Для адаптации систем водоотведения к условиям совокупного влияния урбанизации и изменения климата в мировой практике применяются традиционные статические способы, которые базируются на использовании «серо-зеленых» технологий, включая разделение общесплавных систем на раздельные, а также динамические решения с помощью контроля в режиме реального времени – Real Time Control (RTC). Опыт внедрения показывает, что ни одно из адаптационных мероприятий не может обеспечить 100%-ной эффективности. Следовательно, переливы в системах водоотведения не могут быть запрещены (это положение закреплено в законодательстве практически всех стран мира). При этом стратегия RTC является наиболее экономически выгодной мерой, но ограниченной по эффективности (20–30%). Поэтому в тех случаях, когда эффективности мероприятий RTC недостаточно, их целесообразно сочетать с регулирующими резервуарами. В связи с этим проведена оценка экономической эффективности применения автоматизированной системы управления водоотведением Санкт-Петербурга в режиме реального времени. Основным способом исследований являлось гидравлическое динамическое моделирование, с применением которого оценивались: эффективность управления в режиме реального времени регулирующими резервуарами; эффективность управления в режиме реального времени перебросками сточных вод между тремя бассейнами водоотведения Санкт-Петербурга с учетом параметра, характеризующего неравномерность распределения дождей по площади. In order to adapt wastewater disposal systems to the joint effect of urbanization and climate change, traditional static measures are applied in global practice based on the use of «gray-green» technologies inclusive of dividing combined systems into separate ones, as well as dynamic solutions using real-time control – Real Time Control (RTC). The experience of implementation shows that none of the adaptation measures can provide for 100% efficiency. Therefore, overflows in wastewater disposal systems cannot be prohibited (this provision is enshrined in the legislation of almost all countries of the world). At the same time, the RTC strategy is the most cost-effective measure, however, limited in efficiency (20–30%). Therefore, in case the efficiency of RTC measures is insufficient, combining them with intermediate storage tanks is advisable. In this regard, an estimation of the economic efficiency of using an automated system for wastewater disposal management in St. Petersburg in real time was carried out. The main method of research was hydraulic dynamic modeling, with estimating: the efficiency of the storage tank control in real time; the efficiency of transferring wastewater between three sewer zones of St. Petersburg in real time, taking into account the parameter characterizing the uneven rainfall distribution areally.

This paper explores numerically the benefits of water discharge prediction in the real time control (RTC) of water distribution networks (WDNs). An algorithm aimed at controlling the settings of control valves and variable speed pumps, as a function of pressure head signals from remote nodes in the network, is used. Two variants of the algorithm are considered, based on the measured water discharge in the device at the current time and on the prediction of this variable at the new time, respectively. As a result of the prediction, carried out using a polynomial with coefficients determined through linear regression, the RTC algorithm attempts to correct the expected deviation of the controlled pressure head from the set point, rather than the currently measured deviation. The applications concerned the numerical simulation of RTC in a WDN, in which the nodal demands are reconstructed stochastically through the bottom-up approach. The results prove that RTC benefits from the implementation of the prediction, in terms of the closeness of the controlled variable to the set point and of total variations of the device setting. The benefits are more evident when the water discharge features contained random fluctuations and large hourly variations.

Here we report novel micro-PIV measurements around micron-sized objects that are trapped at the centre of a stagnation point flow generated in a cross-slow microchannel using real-time control. The method enables one to obtain accurate velocity and strain rate fields around the trapped objects under straining flows. In previous works, it has been assumed that the flow field measured in the absence of the object is the one experienced by the object in the stagnation point flow. However, the results reveal that this need not be the case and typically the strain rates experienced by the objects are higher. Therefore, simultaneously measuring the flow field around a trapped object is needed to accurately estimate the undisturbed strain rate (away from the trapped object). By combining the micro-PIV measurements with an analytical solution by Jeffery (Proc R Soc Lond A 102(715):161–179, 1922), we are able to estimate the velocity and strain rate around the trapped object, thus providing a potential fluidic method for characterising mechanical properties of micron-sized materials, which are important in biological and other applications. A novel combination of classical micro-PIV and real-time flow control setups enabled us to measure the velocity field around a target trapped in the extensional flow, which opens up new vistas of characterisation of the mechanical properties of micron-sized objects.

This study presents a field-programmable gate array (FPGA)-based mechatronic design and real-time fuzzy control method with computational intelligence optimization for omni-Mecanum-wheeled autonomous vehicles. With the advantages of cuckoo search (CS), an evolutionary CS-based fuzzy system is proposed, called CS-fuzzy. The CS’s computational intelligence was employed to optimize the structure of fuzzy systems. The proposed CS-fuzzy computing scheme was then applied to design an optimal real-time control method for omni-Mecanum-wheeled autonomous vehicles with four wheels. Both vehicle model and CS-fuzzy optimization are considered to achieve intelligent tracking control of Mecanum mobile vehicles. The control parameters of the Mecanum fuzzy controller are online-adjusted to provide real-time capability. This methodology outperforms the traditional offline-tuned controllers without computational intelligences in terms of real-time control, performance, intelligent control and evolutionary optimization. The mechatronic design of the experimental CS-fuzzy based autonomous mobile vehicle was developed using FPGA realization. Some experimental results and comparative analysis are discussed to examine the effectiveness, performance, and merit of the proposed methods against other existing approaches.

Artificial intelligence and expert systems techniques, coupled with historical signal analysis and optimization methods, provide a novel approach to monitoring process dynamics and performance and learning knowledge about how to do a production job better based on past experience. An expert system-based supervisor is proposed to provide such a tool for a simple tank level control problem which adjusts the schedule for supply purchase to attempt to minimize the average cost of operation over time. This research provides a prototype for the applications of expert systems in real-time process supervision and control; however, the result is primitive. The underlying modeling and optimization methods only work for simple situations.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>