Development Of New Control Algorithms Research Articles

Experimental evaluation for fluxes, currents and speed estimation of induction motor

Induction motor drive control and estimation is a wide subject. The market for variable speed drives has grown dramatically in the last few years. Manufacturers have recognized the importance of not only managing the speed or torque range, but also reducing power consumption. This necessitates the development of new control algorithms and schemes to include these solutions. Indeed, the speed estimate must be employed in one or more regions of the control scheme, depending on the control objective. This concept, as well as the most common speed estimation methodologies, is investigated. Currently, many tools can be used for the evaluation of the rotor speed without a speed sensor. By modern signal processing methods, it is possible to implement an estimation scheme with the possibility of monitoring currents and voltages. Therefore, in this paper, the concept of currents, speed and fluxes estimation based on the extended Kalman filter is proposed. By monitoring the ratio of the theoretical residual to the actual residual, the measured noise covariance matrix is recursively corrected online to make it gradually approach the real noise level. So that the filter performs the optimal estimation, improves the accuracy of the speed estimation. The effect of the load change on the currents, fluxes and speed estimation was also studied. Simulation and experimental results show that the proposed improved adaptive extended Kalman estimator has a strong ability to suppress random measurement noise. The experimental and simulation results prove the accuracy of the proposed scheme towards the state estimation of an induction motor at different load levels. It can accurately estimate the speed of the motor and has a good anti-error ability to meet the actual needs of the project.

Development of a method of multi-criteria evaluation under uncertainty

The object of research is decision-making support systems. Local wars and armed conflicts of recent decades are characterized by high dynamics of operations (combat operations) and a significant amount of diverse information circulating in information systems. These features determine the search for new approaches to increase the efficiency of decision-making support systems, given their reliability. This article solves the problem of developing a method of multicriteria evaluation in conditions of uncertainty. In the course of the research, the authors used the main provisions of the theory of artificial intelligence, automation theory, theory of complex technical systems and general scientific methods of cognition, namely analysis and synthesis. The proposed methodology was developed taking into account the practical experience of the authors of this work during the military conflicts of the last decade. The method of multicriteria evaluation is universal and can be used to assess the state of the objects of analysis of any architecture. The results of the research will be useful in: – development of new control algorithms in decision-making support systems; – substantiation of recommendations for improving the efficiency of operational management; – analysis of analysis (monitoring) objects in the course of hostilities (operations); – creation of perspective technologies to increase the efficiency of operational management; – assessment of the adequacy, reliability, sensitivity of the scientific and methodological apparatus of operational management in decision-making support systems; – development of new and improvement of existing management models. Areas of further research will be aimed at developing a methodology for intelligent management in special-purpose decision-making support systems.

Process control quality analysis

All production processes are controlled by control systems, in which several information flows are generated. However, operators only use a small percent of this information as the processing capacity of a human mind is limited. The paper demonstrates that production process control is to a great extent influenced by human factor. The paper describes a production data processing technique that enables the personnel to make a better use of their resources for operations control. An approach is considered to studying metallurgical processes through analysis of indirect indicators – i.e. the spectral density and autocorrelation function of the key process indicator signals. A method is described to check the efficiency of material flow control systems. The above techniques were applied to a big array of monitoring data collected during a 24-hour smelting operation for copper-nickel sulphide material. Data from three different shifts were used for this analysis. Different operators have different control patterns. The proposed technique, which enables to analyze big arrays of monitoring data, helps minimize the human factor. The adopted experimental data processing technique helps interpret the obtained results for further practical use, development of new control algorithms and optimization of the current control system.

Perspective on Commercial Li-ion Battery Testing, Best Practices for Simple and Effective Protocols

Validation is an integral part of any study dealing with modeling or development of new control algorithms for lithium ion batteries. Without proper validation, the impact of a study could be drastically reduced. In a perfect world, validation should involve testing in deployed systems, but it is often unpractical and costly. As a result, validation is more often conducted on single cells under control laboratory conditions. Laboratory testing is a complex task, and improper implementation could lead to fallacious results. Although common practice in open literature, the protocols used are usually too quickly detailed and important details are left out. This work intends to fully describe, explain, and exemplify a simple step-by-step single apparatus methodology for commercial battery testing in order to facilitate and standardize validation studies.

Prompt determination of the static stability margins in electrical energy systems equipped with distributed generation plants

The wide use of distributed generation (DG) technologies in electrical energy systems (EES) requires development of new control algorithms in normal, emergency and postemergency modes. The issues of determining the static aperiodic stability (SAS) margin in EES equipped with DG plants are of particular relevance. These plants can be removed from the consumption centers, which can lead to SAS reserves depletion. The article presents the results of studies aimed at the developing SAS reserves express calculation methods in EES equipped with DG plants. An effective technique to determine stability margins was proposed based on one of the modifications of limiting modes equations. The results of determining SAS for an electrical network with distributed generation plants are presented. Additionally, the simulation of transient processes in the studied EES for various points in the space of the mode’s controlled parameters has been carried out in the Matlab system.

Low-Cost FPGA-Based Electronic Control Unit for Vehicle Control Systems.

The development of new control algorithms in vehicles requires high economic resources, mainly due to the use of generic real-time instrumentation and control systems. In this work, we proposed a low-cost electronic control unit (ECU) that could be used for both development and implementation. The proposed electronic system used a hybrid system on chip (SoC) between a field-programmable gate array (FPGA) and an Advanced RISC (reduced instruction set computer) Machine (ARM) processor that allowed the execution of parallel tasks, fulfilling the real-time requirements that vehicle controls demand. Another feature of the proposed electronic system was the recording of measured data, allowing the performance of the implemented algorithm to be evaluated. All this was achieved by using modular programming that, without the need for a real-time operating system, executed the different tasks to be performed, exploiting the parallelism offered by the FPGA as well as the dual core of the ARM processor. This methodology facilitates the transition between the designing, testing, and implementation stages in the vehicle. In addition, our system is programmed with a single binary file that integrates the code of all processors as well as the hardware description of the FPGA, which speeds up the updating process. In order to validate and demonstrate the performance of the proposed electronic system as a tool for the development and implementation of control algorithms in vehicles, a series of tests was carried out on a test bench. Different traction control system (TCS) algorithms were implemented and the results were compared.

AVSF‐based control algorithm of DSTATCOM for distribution system

Recent trends have shown that the power quality has been adversely affected due to increased power electronics based devices at the utility grid in the distribution system. Suppression of harmonics and reactive power current compensation at point of common coupling (PCC) improve the power quality using distribution static compensator (DSTATCOM). The development of new control algorithm based on adaptive Volterra second-order filter (AVSF) for DSTATCOM to extract the fundamental power current components from the polluted load current of non-linear load in distribution system is presented in this study. The AVSF is a combination of linear and non-linear functions of the input signals. Both linear and quadratic functions optimise filter coefficients with fast convergence, which is quite important in the success of an adaptive solution. The proposed algorithm is also related to autocorrelation matrix and step size, which are used for rapid convergence. The performance of proposed algorithm for DSTATCOM is validated through experimental results for unity power factor of AC source and zero voltage regulation of the terminal voltage at PCC.

High-Level Synthesis for Accelerating the FPGA Implementation of Computationally Demanding Control Algorithms for Power Converters

Recent advances in power electronic converters highly rely on the development of new control algorithms. These implementations often require complex control architectures featuring microprocessors, digital signal processors, and field-programmable gate arrays (FPGAs). Whereas software implementations are feasible for most power electronics practitioners, FPGA implementations with ad-hoc digital hardware are often a challenging design task. This paper deals with the design and development of control systems for power converters using high-level synthesis tools. In particular, the Xilinx Vivado HLS tool is evaluated for the design of a computationally demanding application, the real-time load estimation for resonant power converters using parametric identification methods. The proposed methodology allows the designer to use a high-level description language, e.g., C, to describe the identification algorithm functionality, and the tool automatically generates the hardware floating-point data-path and the control unit. Besides, it allows a fast design-space exploration through synthesis directives, and pipelining and parallelization are automatically performed to meet timing constraints. The evaluation performed in the study-case control architecture shows a significant design complexity reduction. As a consequence, high-level synthesis tools should be considered as a new paradigm in accelerating digital design for power conversion systems.

Volkswagen’s new 2.0 l TDI engine for the most stringent emission standards — Part 1

Having already being launched in Europe in the VW Tiguan and Audi A4, Common Rail engines have been redeveloped to comply with the strictest exhaust fume limits in the world, namely the Tier 2 Bin5 emission legislation in the USA, and will consequently be launched in the VW Jetta there mid-2008. As well as internal engine features like an optimised injection system, a low-pressure exhaust gas recirculation system and a new method of cylinder pressure control, a technical highlight is the implementation of an NOx exhaust gas aftertreatment system. These new engine components require the development of new control algorithms and intensive coordination of parameters for this entirely new combustion process.

First results from the MAST digital plasma control system

The mega-amp spherical tokamak (MAST) has operated under a new digital plasma control system [Fusion Eng. Des. 66–68 (2003) 761]. The new system, based on commercially available VME hardware, has replaced most of the old analogue control electronics [Fusion Eng. Des. 56–57 (2001) 749] with algorithms implemented in the control software. General Atomics provided their PCS [B.G. Penaflor, J.R. Ferron, M.L. Walker, A structured architecture for advanced plasma control experiments, in: Proceedings of the 19th SOFT, vol. 1, Lisbon, Portugal, 1996, p. 965] software infrastructure as a generic framework for a plasma control system. A powerful configuration tool has been developed to generate the MAST-specific code from a set of structured documents written in extensible mark-up language (XML). This enables rapid development of new control algorithms and permits safe re-configuration of the code layout, whilst maintaining the coherence of multiple cross-references. The initial algorithm set emulates the behaviour of the original analogue control hardware where it is sensible to do so, but implements several new plant protection capabilities that were previously too difficult to provide with analogue electronics. Shots previously run with the old system can be converted to run in the new system, thus allowing previous campaigns to be continued without the need to develop new scenarios. During the present engineering break, a new suite of algorithms is being developed to provide plasma boundary reconstruction and control functions that fully exploit the capabilities of the digital system.