Design methodology of a reliable control system using a structural analysis approach

: Minnesat is the micro-satellite that was designed by the University of Minnesota as part of UNP-4. The mission of Minnesat was to validate the use carrier phase GPS technology to mechanize a compact and accurate attitude determination system. In a broader sense, the objective of this work was to also demonstrate a design methodology for miniature spacecraft navigation, guidance and control systems which integrate the vehicle design process with that of the process of designing the avionics. Minnesat was presented to the US Air Force at the UNP-4 flight competition review. Although Minnesat was not the winning design, it accomplished its scientific and educational goals. The research work of designing compact GPS attitude determination systems continues at the University of Minnesota building on the success of Minnesat. On the other hand, students that were participants in the UNP-4 competition are now employed by various aerospace corporations, are enrolled in aerospace engineering graduate programs or are completing advanced degrees in engineering and science programs.

This paper reviews the state of the art of field- programmable gate array (FPGA) design methodologies with a focus on industrial control system applications. This paper starts with an overview of FPGA technology development, followed by a presentation of design methodologies, development tools and relevant CAD environments, including the use of portable hardware description languages and system level programming/design tools. They enable a holistic functional approach with the major advantage of setting up a unique modeling and evaluation environment for complete industrial electronics systems. Three main design rules are then presented. These are algorithm refinement, modularity, and systematic search for the best compromise between the control performance and the architectural constraints. An overview of contributions and limits of FPGAs is also given, followed by a short survey of FPGA-based intelligent controllers for modern industrial systems. Finally, two complete and timely case studies are presented to illustrate the benefits of an FPGA implementation when using the proposed system modeling and design methodology. These consist of the direct torque control for induction motor drives and the control of a diesel-driven synchronous stand-alone generator with the help of fuzzy logic.

An agent-oriented design methodology for production control is found at the intersection of a new software technology, namely software agents, and an application domain, in this case production control. In order to understand the motivation for this particular design methodology, it is necessary to answer a set of questions: 1. What is production control? Why is it important and what is challenging about designing production control systems? 2. What is agent technology? And why does it help to meet the challenges in production control? 3. How is agent technology applied to production control? And why is it necessary to develop a design methodology for agent-based control systems?

It is time consuming to design a complex system which has multi-function and mutual exclusion. In this paper, the design which flows of complex control system with Mutual Exclusion is divided into abstraction route and embodiment route. In the abstraction route, functions of the system are transferred to processes by using obtained or innovated algorithms and the processes are divided into modules by hardware/software partitioning. In the embodiment route, these modules are transferred to hardware objects which execute the modules. The whole design methodology is illustrated by the hardware implementation of the Philosophers’ dining question. The hardware object is designed and is simulated by using FPGA. The emphasis is focused on the design of a hardware system with distributed mutual exclusion.

Purpose The paper presents the results of work on control systems of bearingless electric motors. Authors proposed the applications of bearingless electric machines for aircraft actuation system. Suggested solution characterizes novel concept of on-board equipment design such as More Electric Aircraft. Magnetic suspension technology allows elimination of friction force and the negative performance features of classic bearing system. However, to achieve all these purposes appropriately, dedicated control system must be also applied. Design/methodology/approach The development of a control system of bearingless electric machine is presented in detail. Mathematical model and construction of induction bearingless motor are widely discussed. Then, proportional–integral-derivative controller algorithm designing for BEM control system was presented using the well pole placement method. Simulation model of BEM control system with use of Matlab-Simulink software was shown. Finally, experimental studies on laboratory stand were introduced. The paper presents design methodology of conventional and advanced control system of bearingless motor. Findings The presented concept of the bearingless electric machines could be applied in the on-board actuation system. During research, full control system of bearingless electric motor was designed and tested. This system consisted of two subsystems. The first responded for rotary speed stabilization and second one was designed for position control of the rotor in the air gap. Practical implications The presented concept of the bearingless electric machines could be applied in the on-board actuation system. During research, full control system of bearingless electric motor was designed and tested. This system consisted of two subsystems. The first responded for rotary speed stabilization and second one was designed for position control of the rotor in the air gap. Originality/value The idea of active magnetic suspension system will be implemented for aviation on technology readiness level V. The paper presents unique laboratory stand with bearingless electric motor and experimental studies. The stable time responses of designed control system were presented and discussed. In addition, preliminary considerations of advanced control system with robust controller were introduced as well.

The paper presents proof of concept design and validation methodology of the flight recovery control system. The flight recovery control system algorithm is based on the model predictive control. Adaptive control is considered for situations where the airplane changes its parameters during the flight. The acceptability of maneuvers automatically conducted by flight recovery control system by pilots can be validated in the hardware in the loop simulation on the aircraft stand with the projection of the pilot view from the cabin. Matlab Simulink is used for models and the control law design. A special block set has been designed for interface Simulink models to the hardware in the loop simulator.

The issues of ensuring the reliability of the control system of a biogas plant should be given special attention in the design of the system, in the manufacture of all hardware, in the development of mathematical and software, in the creation of information support, during installation and commissioning, during the technical operation of the system. A research aim is development of measures on providing of operating reliability of the systems of automatic control by biogas plants due to their optimal service. The choice of the optimal strategy allows you to achieve the best results from the operation of biogas plants without attracting additional resources. The importance of the early resumption of the operation of control systems after failures, as well as planning and organizing their effective preventive maintenance, is noted. The need for collection, processing, analysis and use of data on the reliability of control systems is noted. According to the obtained values of failure time and recovery time, the values of the readiness factor for devices of each type and for the control system as a whole are determined. Analysis of the obtained data on failure time, recovery time after failure, readiness factor will allow to develop organizational and technical measures, the implementation of which will increase the operational reliability of the control system of the biogas plant. To assess the reliability, a complex integral indicator is proposed that characterizes the state of normal functioning of the system. Changing the strategy of preventive maintenance and the organization of work to restore the operation of system devices after failures, based on the analysis of the value of the coefficient of normal functioning, it is possible to obtain the necessary values of the reliability of automatic control systems for biogas plants.

A combined experience and model based design methodology of a fuzzy control system for mean arterial pressure and cardiac output

Input-output-linearization via state feedback offers the potential to serve as a practical and systematic design methodology for nonlinear control systems. Nevertheless, its widespread use is delayed due to the fact that developing an accurate plant model based on physical principles is often too costly and time consuming. Data-based dynamic modeling using neural networks offers a cost-effective alternative. The work describes the methodology of input-output-linearization using neural process models and gives an extended simulative case study of its application to trajectory tracking of a batch polymerization reactor.

In today's world, renewable is the important source and in renewable energy plays vital role. Where wind turbines are placed in remote places and the operation and maintenance services (OMS) are plays key role to getting maximum availability and minimum breakdowns of wind turbine. To minimize the breakdowns in wind turbine, it is important to provide reliable and robust control system. Where communication between controllers plays key role in control system. In wind turbine, the frequency of occurrence of communication failed errors between rotating Hub and stationary Nacelle is causes of increase in breakdown in Wind Turbine. So, to implement W-CAN (Wireless Controller Area Network), where the CAN protocol gives reliable and robust communication between pitch controllers in HUB and Wireless Bluetooth over CAN protocol provide communication between Rotating hub and stationary nacelle which minimizes the communication failed errors. This system is implemented by using LPC1769, FreeRTOS, CAN (Controller Area Network), Bluetooth Protocol, LwIP (Light Weight Internet Protocol) Protocol and Motors. Today real-time communication is one of the key features in distributed embedded control systems. Using FreeRTOS, control system performance will be improved. FreeRTOS comprises CAN & LwIP protocol stack which transfer real time data from hub microcontroller node to nacelle microcontroller node. The Sensor acts as input source to this hub node and microcontroller nodes in compliance of FreeRTOS that includes the Real Time CAN driver which is used for secured and robust data transfer. Real-Time LwIP protocol stack is implemented on top of FreeRTOS to transfer the data to supervisory control and data acquisition (SCADA) System Application on Host PC. In this system, based on LwIP stack the data will be transferred from Turbine nacelle microcontroller Node to the PC Host SCADA application. SCADA application is used for data monitoring and controlling the operation. Hence with the help of this proposed system data acquisition and control of distributed embedded applications will be improved.

In preliminary design, the details of a structure are insufficient to warrant the use of numeric tools traditionally used in structural analysis. However, an accurate prediction of the behavior of a structure and its components in the preliminary design phase can have a significant effect on the final design process in reducing the number of alternative solutions, avoiding the costly design revisions, and improving the quality of design. Presently, there are few tools available for preliminary analysis of structures. This study represents an initial effort towards the development of a tool that can be used in the conceptual design stage to qualitatively evaluate the behavior of a structure.This paper describes a prototype system, QStruc, for qualitative structural analysis, which combines first principles in structural engineering and experiential knowledge of structural behavior. The purposes of QStruc are: (1) to generate qualitative models from the schematics of a structure; and (2) to infer the qualitative response of the structure in terms of deflected shape, moments, and reactions. The qualitative analysis strategy employs: (1) a greedy depth-first approach that tries to expand the derived response as much as possible from known parameter values; (2) a causal ordering mechanism, which enables the system to identify the solution path for the qualitative analysis; (3) qualitative calculus, which enables the qualitative evaluation of the physical quantities of the causal model that describes the behavior of the structure; and (4) Quantity Lattice (Simmons, 1986) which enables the system to reason about partial ordering among physical quantities and to reduce some of the ambiguous conclusions caused by the impreciseness of the information. Examples are provided to illustrate the effectiveness and limitations of the prototype system.

Modern complex and flexible manufacturing systems require new types of control system architectures and design methodologies. An essential new applied architectural approach is the distributed control architecture and an essential new methodology within automation is model-based engineering. There is a wide range of modeling approaches available from traditional automation, domain-oriented systems engineering, and software engineering. Unfortunately, there are very few reports on the pros and cons of these modeling approaches for the practical design tasks along the engineering process for distributed control systems (DCSs). This paper gives a first evaluation for the suitability of models for engineering DCSs to provide the researcher and practitioner with combinations of models that are well suited for their engineering projects.

The insertion of communication networks in closed-loop of digital control systems makes the system synthesis and analysis complex. In this paper, we consider the combination of classical reliability, risk and safety evaluation with typical control system through digital networked control systems. The main purpose is to study the influence of transmission delays and packet dropouts on the reliability of digital networked control systems by using a modified statistical method-Monte Carlo simulation. The behaviors of two types of fault are modelled by different statistical distribution. The control strategies we apply for digital control systems are Proportion Integration Differentiation control strategies, generated by Genetic Algorithm. In terms of a realistic system model, we evaluate and compare the influences on the reliability of digital networked control systems with different control strategies from quantitative aspect. Numerical examples are presented to illustrate the effectiveness and correctness of the approach.

Digital Controller Implementation for Electrohydraulic Motion Simulator Based on MAS and RCP

Fast transient and smooth steady state performance of wind energy generators is essential for sustained power conversion and grid code fulfilment. In this paper, a profound analysis of permanent magnet synchronous generators under vector control (VC) and direct torque control (DTC), by a deviation modelling, provides the basis for combining salient features of these two control methods into a reliable and effective control system to provide the desired machine performance. Accordingly, a hysteresis current vector control and an inverter-switching table are set together to form the core of control system, while it gets rid of problematic parts of the two conventional control systems. The core is used to design two alternative combined control systems with and without an explicit torque control loop. The control systems are then applied to a 2 MW PMSG connected to a power network. Extensive simulation of the system operation at different conditions confirms improved system performance under a designed control, which is collectively superior to DTC.