Temperature and concentration control of exothermic chemical processes in continuous stirred tank reactors

Exothermic chemical reaction taking place in continuous stirred tank reactor is considered. Heat release from the chemical reaction, non-linear dynamic behavior of the process and uncertainty in parameters are the main factors motivating the use of robust control design. Viewing temperature and molar concentration as variables both accessible in real time, PI and optimal state-feedback controllers driven by temperature and concentration error signals are proposed to regulate the system over reactor’s steady-state working points by counteracting undesired disturbances. Since access to concentration value has proved beneficial for the reactor’s performance, estimation techniques are examined to compensate for the problematic nature of the concentration’s measurement. A linear reduced-order observer is first proposed to estimate the concentration value using temperature measurements. In addition, assuming concentration measurement is available with a relatively short delay via sample analysis, a linear and non-linear discrete-time predictor is constructed to estimate the concentration’s real-time value. A linear combination of the two estimation schemes (observer, predictor) is proposed resulting in a combined estimator, in which the emphasis between the two individual schemes can be controlled via a scalar parameter. The work presented in this paper was supported by the GLOW project – New weather-stable low gloss powder coatings based on bifunctional acrylic solid resins and nanoadditives – as part of the development of novel and efficient processing technologies regarding the production of new families of powder coatings, responding to industrial requirements for quality improvement at lower cost and shorter development cycles

Performance analysis of distributed control configurations in LQR multi-agent system design

The paper considers a distributed Linear Quadratic Regulator (LQR) design framework for a network of identical dynamically decoupled multi-agent systems. It is known that in this case a stabilizing distributed controller for the network can be obtained by solving a centralized LQR problem whose size depends on the maximum vertex degree of the graph. A systematic method is presented for computing the performance loss of various distributed control configurations relative to the performance of the centralized controller. A procedure is developed for analyzing the performance loss for general distributed control configurations and state-space directions. It is also shown that by removing a single link we can always define a control configuration for which there is no performance loss, provided the initial state of the aggregate system lies in a particular direction of state-space which is identified. The results are illustrated by an exhaustive analysis of the network consisting of six identical agents

Effects of dynamic and non-dynamic element changes in RLC networks

The paper deals with the redesign of passive electric networks by changes of single dynamic and non-dynamic elements which may retain, or affect the natural topology of the network. It also deals with the effect of such changes on the natural dynamics of the network, the natural frequencies. The impedance and admittance modeling for passive electrical networks is used which provides a structured, symmetric, integral-differential description, which in the special cases of RC and RL networks is reduced to matrix pencil descriptions. The transformations on the network are expressed as those preserving, or modifying the two natural topologies of the network, the impedance graph and the admittance graph topologies. For the special cases of RC and RL networks we consider the problem of the effect of changes of a single dynamic, or non-dynamic element on the natural frequencies. Using the Determinantal Assignment Framework, it is shown that the family of single parameter variation problems is reduced to equivalent Root Locus problems with the possibility of fixed modes. An explicit characterization of the fixed modes is given and a number of interesting properties of the spectrum are derived such as the interlacing property of poles and zeros for the entire family of Root Locus problems

New insights on robust control of tilting trains with combined uncertainty and performance constraints

A rigorous study on optimized robust control is presented for non-preview (nulling-type) high-speed tilting rail vehicles. The scheme utilizes sensors on the vehicle’s body, contrary to that of preview tilt (which uses prior rail track information). Tilt with preview is the industrial norm nowadays but is a complex scheme (both in terms of inter-vehicle signal connections and when it comes to straightforward fault detection). Non-preview tilt is simple (as it essentially involves an SISO control structure) and more effective in terms of (the localization of) failure detection. However, the non-preview tilt scheme suffers from performance limitations due to non-minimum-phase zeros in the design model (due to the compound effect of the suspension dynamic interaction and sensor combination used for feedback control) and presents a challenging control design problem. We proposed an optimized robust control design offering a highly improved non-preview tilt performance via a twofold model representation, i.e., (i) using the non-minimum phase design model and (ii) proposing a factorized design model version with the non-minimum phase characteristics treated as uncertainty. The impact of the designed controllers on tilt performance deterministic (curving acceleration response) and stochastic (ride quality) trade-off was methodically investigated. Nonlinear optimization was employed to facilitate fine weight selection given the importance of the ride quality as a bounded constraint in the design process

Distributed LQR Design for a Class of Large-Scale Multi-Area Power Systems

Load frequency control (LFC) is one of the most challenging problems in multi-area power systems. In this paper, we consider power system formed of distinct control areas with identical dynamics which are interconnected via weak tie-lines. We then formulate a disturbance rejection problem of power-load step variations for the interconnected network system. We follow a top-down method to approximate a centralized linear quadratic regulator (LQR) optimal controller by a distributed scheme. Overall network stability is guaranteed via a stability test applied to a convex combination of Hurwitz matrices, the validity of which leads to stable network operation for a class of network topologies. The efficiency of the proposed distributed load frequency controller is illustrated via simulation studies involving a six-area power system and three interconnection schemes. In the study, apart from the nominal parameters, significant parametric variations have been considered in each area. The obtained results suggest that the proposed approach can be extended to the non-identical case

Hankel-norm approximation of FIR filters: a descriptor-systems based approach

We propose a new method for approximating a matrix finite impulse response (FIR) filter by an infinite impulse response (IIR) filter of lower McMillan degree. This is based on a technique for approximating discrete-time descriptor systems and requires only standard linear algebraic routines, while avoiding altogether the solution of two matrix Lyapunov equations which is computationally expensive. Both the optimal and the suboptimal cases are addressed using a unified treatment. A detailed solution is developed in state-space or polynomial form, using only the Markov parameters of the FIR filter which is approximated. The method is finally applied to the design of scalar IIR filters with specified magnitude frequency-response tolerances and approximately linear-phase characteristics. A priori bounds on the magnitude and phase errors are obtained which may be used to select the reduced-order IIR filter order which satisfies the specified design tolerances. The effectiveness of the method is illustrated with a numerical example. Additional applications of the method are also briefly discussed

A quantitative approach to behavioural analysis of drivers in highways using particle filtering

The analysis of the driving behaviour is a challenging area in transport that has applications in numerous fields ranging from highway design to micro-simulation and development of advanced driver assistance systems (ADAS). There has been evidence suggesting changes in the driving behaviour in response to changes in traffic conditions, and this is known as adaptive driving behaviour. Identifying these changes, the conditions under which they happen, and describing them in a systematic way would contribute greatly to the accuracy of micro-simulation and more importantly to the understanding of the traffic flow, and will therefore pave the way for introducing further improvements in the efficiency of the transport network. In this paper adaptive driving behaviour is linked to changes in the model parameters for a given car-following model. These changes are tracked using a dynamic system identification method, namely unscented particle filtering

Facilitating organisational decision making: a change risk assessment model case study

Purpose: This paper aims to take the challenge to propose a novel modelling approach named Change Risk Assessment Model (CRAM), which will contribute significantly to the missing formality of business models especially in the change risk assessment area and decision-making. Organisational change risks are assessed with the aid of analytic hierarchy process (AHP) in an attempt to define the internal dynamics of organisational change management within project management eliciting also risk cause-and-effect relationships. Design/methodology/approach: The study discusses interviews/survey/AHP. Findings: The study presents the following findings. Change risk factors assessment (identification and prioritisation) recommendations (see Case Study) integration of change management; project management; risk management top four risk factors, namely, leadership, communication, project management team and culture. Research limitations/implications: As projects can be different in a variety of factors (quality, scope), an exhaustive list of risk factors cannot be identified. There is a continuous risk identification process throughout the projects’ life cycle. For example, many risks can be classified initially as unknown and can be refined after the initiation phase of the project. AHP factors limitation (eight per level) possible bias (survey analysis). Practical implications: With the aid of modelling and especially CRAM, business change risks can be assessed numerically and prioritised. Several risk factors and related attributes were identified and categorised. This empowers project managers or other stakeholders to make proper decisions about whether to take on or abandon respective organisational or project changes. Social implications: One of the values of CRAM is that it can be regarded as a global change risk assessment method that can be applied regardless of project type, size or organisation. Moreover, it has the advantage that it can be used by any kind of project, as the method is designed to be tailored to specific needs, taking significant environmental change risk factors into account. AHP has numerous uses in operational research, in project management and in general in areas where decisions (evaluation and selection) have to be made. The analysis of the case study presented, indicated that it is vital to assess the degree (impact) that each risk attribute poses to address complex organisational decisions. Originality/value: CRAM aims to bridge the gap between theoretical and applied work in the integrated research field of change management, project management and risk management. Furthermore, the approach attempts to develop a novel systematic methodology (model) for assigning probabilities in attributes (criteria) pair-wise comparison and more specifically, modelling and assessing change management risks, adding a different perspective and technique to the research area