Control, performance management systems and identification processes

Is it possible to control identities using performance management systems (PMSs)? This paper explores the theoretical fusion of management accounting and identity studies, providing a synthesised view of control, PMSs and identification processes. It argues that the effective use of PMSs generates a range of obtrusive mechanistic and unobtrusive organic controls that mediate identification processes to achieve a high level of identity congruency between individuals and collectives—groups and organisations. This paper contends that mechanistic control of PMSs provides sensebreaking effects and also creates structural conditions for sensegiving in top-down identification processes. These processes encourage individuals to continue the bottom-up processes of sensemaking, enacting identity and constructing identity narratives. Over time, PMS activities and conversations periodically mediate several episode(s) of identification to connect past, current and future identities. To explore this relationship, the dual locus of control—collectives and individuals—is emphasised to explicate their interplay. This multidisciplinary approach contributes to explaining the multidirectional effects of PMSs in obtrusive as well as unobtrusive ways, in order to control the nature of collectives and individuals in organisations.

Control, performance management system and identification processes

Is it possible to control identities using performance management systems (PMSs)? This paper explores the theoretical fusion of management accounting and identity studies, providing a synthesised view of control, PMSs and identification processes. It argues that the effective use of PMSs generates a range of obtrusive mechanistic and unobtrusive organic controls that mediate identification processes to achieve a high level of identity congruency between individuals and collectives—groups and organisations. This paper contends that mechanistic control of PMSs provides sensebreaking effects and also creates structural conditions for sensegiving in top-down identification processes. These processes encourage individuals to continue the bottom-up processes of sensemaking, enacting identity and constructing identity narratives. Over time, PMS activities and conversations periodically mediate several episode(s) of identification to connect past, current and future identities. To explore this relationship, the dual locus of control—collectives and individuals—is emphasised to explicate their interplay. This multidisciplinary approach contributes to explaining the multidirectional effects of PMSs in obtrusive as well as unobtrusive ways, in order to control the nature of collectives and individuals in organisations.

System identification, estimation and control for a cost effective open-source quadcopter

This paper describes system identification, estimation and control of translational motion and heading angle for a cost effective open-source quadcopter — the MikroKopter. The dynamics of its built-in sensors, roll and pitch attitude controller, and system latencies are determined and used to design a computationally inexpensive multi-rate velocity estimator that fuses data from the built-in inertial sensors and a low-rate onboard laser range finder. Control is performed using a nested loop structure that is also computationally inexpensive and incorporates different sensors. Experimental results for the estimator and closed-loop positioning are presented and compared with ground truth from a motion capture system.

Identification of evidence-based biospecimen quality-control tools

Control of biospecimen quality that is linked to processing is one of the goals of biospecimen science. Consensus is lacking, however, regarding optimal sample quality-control (QC) tools (ie, markers and assays). The aim of this review was to identify QC tools, both for fluid and solid-tissue samples, based on a comprehensive and critical literature review. The most readily applicable tools are those with a known threshold for the preanalytical variation and a known reference range for the QC analyte. Only a few meaningful markers were identified that meet these criteria, such as CD40L for assessing serum exposure at high temperatures and VEGF for assessing serum freeze-thawing. To fully assess biospecimen quality, multiple QC markers are needed. Here we present the most promising biospecimen QC tools that were identified.

Pythium soft rot of ginger: Detection and identification of the causal pathogens, and their control

Ginger is considered by many people to be the outstanding member among 1400 other species in the family Zingiberaceae. Not only it is a valuable spice used by cooks throughout the world to impart unique flavour to their dishes but it also has a long track record in some Chinese and Indian cultures for treating common human ailments such as colds and headaches. Ginger has recently attracted considerable attention for its anti-inflammatory, antibacterial and antifungal properties. However, ginger as a crop is also susceptible to at least 24 different plant pathogens, including viruses, bacteria, fungi and nematodes. Of these, Pythium spp. (within the kingdom Stramenopila, phyllum Oomycota) are of most concern because various species can cause rotting and yield loss on ginger at any of the growth stages including during postharvest storage. Pythium gracile was the first species in the genus to be reported as a ginger pathogen, causing Pythium soft rot disease in India in 1907. Thereafter, numerous other Pythium spp. have been recorded from ginger growing regions throughout the world. Today, 15 Pythium species have been implicated as pathogens of the soft rot disease. Because accurate identification of a pathogen is the cornerstone of effective disease management programs, this review will focus on how to detect, identify and control Pythium spp. in general, with special emphasis on Pythium spp. associated with soft rot on ginger.

Distributed Optimal Control of Cyber-Physical Systems: Controller Synthesis, Architecture Design and System Identification

The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.

The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.

We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H-infinity optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H-infinity norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.

Identification of causes of Thai pangas mortality in ponds and their control strategies

Mass mortality of Thai pangas (Pangasius hypophthalmus) is reported to be a big threat to monoculture of the species in Bangladesh. Twenty affected and twenty control Thai pangas ponds were investigated around Mymensingh district in order to identify the causes of pangas mortality. Sixty affected and sixty unaffected fish samples were examined and compared to find the fish-level variables associated with the disease. A range of haemorrhagic signs on snout, skin and fins were recorded during examination with naked eyes. Aeromonas spp. and Edwardsiella spp. were isolated from 87% and 80% of the affected fish, respectively. Even 4% of the seemingly healthy fish carried Aeromonas spp. on their skin. Among the four water quality parameters monitored, remarkably higher total ammonia (1.5 ppm) was found in water of the affected ponds compared to that of the unaffected ones (0.4 ppm). High ammonia in affected water caused by excessive organic decomposition and poor pond management might have reduced the immunity of fish, which predisposed them for bacterial invasion and consequent disease outbreak.

Chemical control of psychrophilic bacterial spoilage of fish 1. Isolation and identification of psychrophilic bacteria from marine fish

Making use of the streak plate technique and low temperature incubation, 28 cultures belonging to six genera namely, Achromobacter, Flavobacterium, Pseudomonas, Micrococcus, Vibrio and Alcaligenes were isolated from different varieties of marine fish. The growth studies indicated that all of them were able to grow between -5 and +5°C within a week's time and none of them showed growth at 37°C. The optimum temperature of growth for all these cultures was in the range 25-28°C. Among these only one, i.e., a Vibrio sp., was found to be an obligate psychrophile.

Identification of the steering control behaviour of five test subjects following a randomly curving path in a driving simulator

The paper is concerned with the identification of theoretical preview steering controllers using data obtained from five test subjects in a fixed-base driving simulator. An understanding of human steering control behaviour is relevant to the design of autonomous and semi-autonomous vehicle controls. The driving task involved steering a linear vehicle along a randomly curving path. The theoretical steering controllers identified from the data were based on optimal linear preview control. A direct-identification method was used, and the steering controllers were identified so that the predicted steering angle matched as closely as possible the measured steering angle of the test subjects. It was found that identification of the driver's time delay and noise is necessary to avoid bias in identification of the controller parameters. Most subjects' steering behaviour was predicted well by a theoretical controller based on the lateral/yaw dynamics of the vehicle. There was some evidence that an inexperienced driver's steering action was better represented by a controller based on a simpler model of the vehicle dynamics, perhaps reflecting incomplete learning by the driver. Copyright © 2014 Inderscience Enterprises Ltd.