Online estimation of multicomponent heat flux using a system identification technique

In this work system identification techniques are used to map the two-dimensional heat flux into the temperatures through a linear model supported by theoretical and numerical results. The basis of this analysis is a discrete version of the Burggraf Method saying a single component heat flux is a linear combination of the temperatures around the time of its occurrence. Taking the same approach, a linear model (i.e. a linear artificial neural network (ANN)) is employed to estimate a multicomponent heat flux as a linear function of the temperatures. A known heat flux is imposed to the direct model, then the history of heat flux-temperature data are fit to the linear mathematical model (i.e. a linear ANN) using system identification techniques. The achieved model estimates the heat flux based on a series of past and future temperatures and the estimated heat flux components are in a good agreement with the exact ones. Finally, the effect of some important factors on the results is investigated. The proposed solution to inverse heat conduction problems does not need thermophysical and geometrical parameters of the system and is robust against noises. It merely needs some series of heat flux-temperature data from solution of a reliable direct numerical model or experiment. © 2013 Elsevier Ltd.Masoud Khorrami, Forooza Samadi, Farshad Kowsary, Morteza Mohammadzaher

Distributed active shock absorbers for flexible structures

A multi-degree-of-freedom (MDOF) distributed active shock absorber (DASA) for shock vibration suppression in flexible structures is investigated in this paper. The DASA is a simple first-order controller that is designed based on the modal positive position feedback strategy to suppress transient vibrations of flexible structures at various harmonics. The DASA can be constructed by using piezoceramic sensors and actuators that are controlled by micro-controller. The effectiveness of the DASA design is validated through multiple-mode control on a flexible cantilever beam system with a single sensor/actuator pair. The experimental results reveal that the proposed strategy is a potentially viable means for real-time control of vibration in large flexible structures.Lei Chen and Morteza Mohammadzaheri, Fangpo He and Karl Sammuthttp://isma2008.isma-conf.org

Simulation and experimental study of inverse heat conduction problem

In this paper, a neural network method is proposed to solve a one dimensional inverse heat conduction problem (IHCP). The method relies on input/output data of an unknown system to create an intelligent neural network model. Multi layer perceptrons with recurrent properties are utilised in the model. Prepared input/output data are used to train the neural network. Reliable checking processes are also offered to justify the robustness of the method. A numerical sequential function specification (SFS) method is used as another technique to solve the IHCP. The numerical result is compared with that of the proposed method and good agreement is shown between the two methods. However, the numerical method can be only used to solve the IHCP off-line due to the high computation requirement. The proposed neural network method can be used in real-time situations as shown in the experimental tests.Ley Chen, S Askarian, M Mohammadzaheri and F Samad

Double-command feedforward-feedback control of a nonlinear plant

In this paper, a design approach is proposed for feedforward-feedback control systems. As the basis of the proposed design approach, steady state control command is defined as the control command which maintains the desired situation of the system. Steady state control law is derived form system's mathematical model and employed as feedforward controller. Using such a feedforward controller, for a wide class of systems, the stability of system is proved if the feedback controller is a gain with an arbitrarily high value. That is, the only limit for the feedback (transient) control command is the actuator's practical limit; moreover, there will be no overshoot and control system is capable to damp sever disturbances. In this article, the proposed method has been applied on a Catalytic Stirred Tank Reactor (CSTR) with two control inputs leading to an excellent control response.Morteza Mohammadzaheri, Lei Chen, Fariba Behnia-Willison, Samin Askaria

A design approach for feedback-feedforward control systems

In this paper, a general design approach is proposed to derive the feedforward control law in feedback-feedforward control systems. This design approach is based on the concept of `control equilibrium point'. In this design approach, the feedback controller generates the transient control command and the feedforward controller generates the steady state one. Using the proposed feedforward controller, for a wide class of process plants, the stability of system is guaranteed if the feedback controller is a gain with an arbitrarily high value. That is, the only limit for the feedback (transient) control command is the actuator's practical limit; however, in this approach, a mathematical model of the system is needed to derive the feedforward control law. In order to remove this drawback, in case of having significant uncertainties, an artificial neural network, independent of mathematical model of the system, is designed to play the role of feedforward (steady state) control law.Morteza Mohammadzaheri, Lei Chen, Fariba Behnia-Willison and Pouria Arya

Parsing with GETARUN

GETARUNS, the system for text and reference understanding which is currently used for summarization and text generation has a highly linguistically sophisticated parser which implements a number of strategies to cope with ambiguity ensuing from PP attachment and other similar problems(see Delmonte & Dolci, 1997). In this paper we present the parser from a linguistic point of view and as such implementing LFG theoretical framework within a DCG, using Xtraposition Grammars to cope with Long Distance Dependencies. The parser is multilingual and contains a lookahead mechanism, which is then used by the Well-Formed-Substring-Table to recover wrongly parser attachment

Fuzzy modeling of a piezoelectric actuator

In this research, a piezoelectric actuator was modeled using fuzzy subtractive clustering and neuro-fuzzy networks. In the literature, the use of various modeling techniques (excluding techniques used in this article) and different arrangements of inputs in black box modeling of piezoelectric actuators for the purpose of displacement prediction has been reported. Nowadays, universal approximators are available with proven ability in system modeling; hence, the modeling technique is no longer such a critical issue. Appropriate selection of the inputs to the model is, however, still an unsolved problem, with an absence of comparative studies. While the extremum values of input voltage and/or displacement in each cycle of operation have been used in black box modeling inspired by classical phenomenological methods, some researchers have ignored them. This article focuses on addressing this matter. Despite the fact that classical artificial neural networks, the most popular black box modeling tools, provide no visibility of the internal operation, neuro-fuzzy networks can be converted to fuzzy models. Fuzzy models comprise of fuzzy rules which are formed by a number of fuzzy or linguistic values, and this lets the researcher understand the role of each input in the model in comparison with other inputs, particularly, if fuzzy values (sets) have been selected through subtractive clustering. This unique advantage was employed in this research together with consideration of a few critical but subtle points in model verification which are usually overlooked in black box modeling of piezoelectric actuators.Morteza Mohammadzaheri, Steven Grainger and Mohsen Bazghale

A comparative study on the use of black box modelling for piezoelectric actuators

In this article, different approaches of the use of black box modelling techniques for piezoelectric actuators are particularly addressed, regardless of the employed technique/algorithm. A modelling approach in this paper refers to two matters: the first, the role of black box techniques in modelling (i.e. if physics-based techniques are also involved in modelling; if so, how and to what extent). From this aspect, the spectrum of approaches ranges from those merged with/inspired by classical phenomenological models to an approach based on purely system identification-based techniques. The second aspect of modelling approaches, in this article, is the input variables to the model. Current and previous values of input voltage, previous values of the output (displacement), derivatives and extremum values of the system's input/output have been used as the inputs to the model so far. Both aforementioned aspects of modelling approaches are addressed appropriately in this article, and various modelling approaches in the literature are categorized and presented in a uniform and comparable manner, so that readers can easily identify research trends in this area and the gaps in the literature. One of the identified unanswered questions in the literature is whether the extremum values of the system's input/output should/should not be used as an input to black box models of piezoelectric actuators. There are works in the literature which have/have not used the aforementioned input variables, but there is no published investigation to evidently answer the proposed question. This article, in the last section, answers this question by reporting and discussing an experimental study.Morteza Mohammadzaheri, Steven Grainger and Mohsen Bazghale