An ANN-based temperature controller for a plastic injection moulding system

This paper proposes an approach to an ANN-based temperature controller design for a plastic injection moulding system. This design approach is applied to the development of a controller based on a combination of a classical ANN and integrator. The controller provides a fast temperature response and zero steady-state error for three typical heaters (bar, nozzle, and cartridge) for a plastic moulding system. The simulation results in Matlab Simulink software and in comparison to an industrial PID regulator have shown the advantages of the controller, such as significantly less overshoot and faster transient (compared to PID with autotuning) for all examined heaters. In order to verify the proposed approach, the designed ANN controller was implemented and tested using an experimental setup based on an STM32 board

Variable structure controller for plastic injection moulding system

This paper discusses the approach to design of combined ANN and PID temperature controller for a plastic injection moulding system. The proposed method is based on integration of a conventional PID (PI) controller and a multilayer ANN. At the initial stage of operation, the ANN is trained in offline mode to approximately identify the dynamic parameters of the regulator optimised in terms of speed of response and overshoot. Under routine operation mode the ANN control structure is responsible for the fast transients whereas PID (PI) controller provides the high accuracy at the steady state condition. The paper focuses on the structure switching mechanism and the influence on the transient accuracy. In order to verify the proposed approach, the control system having various types of heaters has been modelled and simulated in Matlab/Simulink. The data obtained from the experiment verified the developed model and confirmed the results of simulations

Improved and innovated universal DAQ microcontroller unit

This paper is aimed at the description of hardware design, software equipment and the functionality of the second evolution of the intelligent multipurpose input/output microcontroller converter and control unit designed and assembled by the authors. Preceding stages of the unit development are concisely overviewed first, the deficiencies of which give rise to the primary motivation of this contribution. Then separate hardware parts of the novel unit are described in detail including electronic schematic diagrams. The device firmware and software capabilities are introduced as well. The advantages of the unit are highlighted compared to older versions. Its functionality, performance and efficiency are then verified by a laboratory control-related dynamic responses measurement example. In the contrary to previous evolutions, a more compact hardware design, increased A/D and D/A converter resolutions, added USB communication capability, better and more accurate analog circuits with more advanced operation amplifiers, the use of OLED instead of LCD display, the pulse-width modulated signal generated by the microcontroller unit itself can be considered among the most important improvements. Moreover, the direct use of the serial link may reduce noise significantly and makes the device more universal

Thermal management of micro gas chromatographs

Gas chromatography is an analytical technique for separating and analyzing individual components in a gas mixture. Applications of gas chromatographs (GCs) include chemical analysis, environmental maintenance, green house gases monitoring, and forensic analysis when used in conjunction with mass spectrometry. There has been a tremendous interest in miniaturization of gas chromatograph systems because of significantly reduced size, portability, fast response times, low power consumption and low cost. Isothermal analysis is a chromatographic analysis at one column temperature. In temperature programming, a linear increase of column temperature with time is used during the course of the analysis. Temperature programming facilitates separation of a wider range of components, when compared to isothermal analysis, in less time. Though a few miniaturized gas chromatograph systems with temperature programming capability have been reported, all reported findings until now demonstrate very slow heating ramp rates(~5oC/sec). To enable faster analysis and to analyze a wider ranger of chemicals, higher heating rates (of the order of ~40oC/sec) have yet to be achieved. A heater was designed to implement different temperature programming cycles for a LiGA fabricated nickel micro GC. The thermal behavior of the device was modeled using an energy-based approach to determine the thermal power requirements. Thermal stress analysis was carried out to determine the thermal stresses in the system. The heaters were fabricated by electrodepositing nickel and copper on a polyimide insulating layer on top of the nickel micro GC column. Heating ramp rates from 5oC/sec to 50oC/sec were obtained with the aid of a PID controller. The heaters were also able to maintain the column at different elevated temperatures, which showed that the heaters could be used to achieve a variety of temperature programming profiles and they offered flexibility in selecting different ramp rates and soak temperatures

Analytical design of a generalised predictor-based control scheme for low-order integrating and unstable systems with long time delay

In this study, the problem of controlling integrating and unstable systems with long time delay is analysed in the discrete-time domain for digital implementation. Based on a generalised predictor-based control structure, where the plant time delay can be taken out of the control loop for the nominal plant, an analytical controller design is proposed in terms of the delay-free part of the nominal plant model. Correspondingly, further improved control performance is obtained compared with recently developed predictor-based control methods relying on numerical computation for controller parameterisation. The load disturbance rejection controller is derived by proposing the desired closed-loop transfer function, and another one for set-point tracking is designed in terms of the H-2 optimal control performance specification. Both controllers can be tuned relatively independently in a monotonic manner, with a single adjustable parameter in each controller. By establishing the sufficient and necessary condition for holding robust stability of the closed-loop control system, tuning constraints are derived together with numerical tuning guidelines for the disturbance rejection controller. Illustrative examples taken from the literature along with temperature control tests for a crystallisation reactor are used to demonstrate the effectiveness and merit of the proposed method.This work was supported in part by the National Thousand Talents Program of China, NSF China Grants 61473054, the Fundamental Research Funds for the Central Universities of China, and the Grants TIN2014-56158-C4-4-P and PROMETEOII/2013/004 from the Spanish and Valencian Governments.Chen, Y.; Liu, T.; García Gil, PJ.; Albertos Pérez, P. (2016). Analytical design of a generalised predictor-based control scheme for low-order integrating and unstable systems with long time delay. IET Control Theory and Applications. 10(8):884-893. https://doi.org/10.1049/iet-cta.2015.0670S88489310

A Smart Products Lifecycle Management (sPLM) Framework - Modeling for Conceptualization, Interoperability, and Modularity

Autonomy and intelligence have been built into many of today’s mechatronic products, taking advantage of low-cost sensors and advanced data analytics technologies. Design of product intelligence (enabled by analytics capabilities) is no longer a trivial or additional option for the product development. The objective of this research is aimed at addressing the challenges raised by the new data-driven design paradigm for smart products development, in which the product itself and the smartness require to be carefully co-constructed. A smart product can be seen as specific compositions and configurations of its physical components to form the body, its analytics models to implement the intelligence, evolving along its lifecycle stages. Based on this view, the contribution of this research is to expand the “Product Lifecycle Management (PLM)” concept traditionally for physical products to data-based products. As a result, a Smart Products Lifecycle Management (sPLM) framework is conceptualized based on a high-dimensional Smart Product Hypercube (sPH) representation and decomposition. First, the sPLM addresses the interoperability issues by developing a Smart Component data model to uniformly represent and compose physical component models created by engineers and analytics models created by data scientists. Second, the sPLM implements an NPD3 process model that incorporates formal data analytics process into the new product development (NPD) process model, in order to support the transdisciplinary information flows and team interactions between engineers and data scientists. Third, the sPLM addresses the issues related to product definition, modular design, product configuration, and lifecycle management of analytics models, by adapting the theoretical frameworks and methods for traditional product design and development. An sPLM proof-of-concept platform had been implemented for validation of the concepts and methodologies developed throughout the research work. The sPLM platform provides a shared data repository to manage the product-, process-, and configuration-related knowledge for smart products development. It also provides a collaborative environment to facilitate transdisciplinary collaboration between product engineers and data scientists

Novel analysis and modelling methodologies applied to pultrusion and other processes

Often a manufacturing process may be a bottleneck or critical to a business. This thesis focuses on the analysis and modelling of such processest, to both better understand them, and to support the enhancement of quality or output capability of the process. The main thrusts of this thesis therefore are: To model inter-process physics, inter-relationships, and complex processes in a manner that enables re-exploitation, re-interpretation and reuse of this knowledge and generic elements e.g. using Object Oriented (00) & Qualitative Modelling (QM) techniques. This involves the development of superior process models to capture process complexity and reuse any generic elements; To demonstrate advanced modelling and simulation techniques (e.g. Artificial Neural Networks(ANN), Rule-Based-Systems (RBS), and statistical modelling) on a number of complex manufacturing case studies; To gain a better understanding of the physics and process inter-relationships exhibited in a number of complex manufacturing processes (e.g. pultrusion, bioprocess, and logistics) using analysis and modelling. To these ends, both a novel Object Oriented Qualitative (Problem) Analysis (OOQA) methodology, and a novel Artificial Neural Network Process Modelling (ANNPM) methodology were developed and applied to a number of complex manufacturing case studies- thermoset and thermoplastic pultrusion, bioprocess reactor, and a logistics supply chain. It has been shown that these methodologies and the models developed support capture of complex process inter-relationships, enable reuse of generic elements, support effective variable selection for ANN models, and perform well as a predictor of process properties. In particular the ANN pultrusion models, using laboratory data from IKV, Aachen and Pera, Melton Mowbray, predicted product properties very well

Time Localization of Abrupt Changes in Cutting Process using Hilbert Huang Transform

Cutting process is extremely dynamical process influenced by different phenomena such as chip formation, dynamical responses and condition of machining system elements. Different phenomena in cutting zone have signatures in different frequency bands in signal acquired during process monitoring. The time localization of signal’s frequency content is very important. An emerging technique for simultaneous analysis of the signal in time and frequency domain that can be used for time localization of frequency is Hilbert Huang Transform (HHT). It is based on empirical mode decomposition (EMD) of the signal into intrinsic mode functions (IMFs) as simple oscillatory modes. IMFs obtained using EMD can be processed using Hilbert Transform and instantaneous frequency of the signal can be computed. This paper gives a methodology for time localization of cutting process stop during intermittent turning. Cutting process stop leads to abrupt changes in acquired signal correlated to certain frequency band. The frequency band related to abrupt changes is localized in time using HHT. The potentials and limitations of HHT application in machining process monitoring are shown