Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.

Differential inclusions and robust control theory

Uncontrolled systems (x) over dot is an element of Ax, where A is a non-empty compact set of matrices, and controlled systems (x) over dot is an element of Ax + Bu are considered. Higher-order systems 0 is an element of Px - Du, where and are sets of differential polynomials, are also studied. It is shown that, under natural conditions commonly occurring in robust control theory, with some mild additional restrictions, asymptotic stability of differential inclusions is guaranteed. The main results are variants of small-gain theorems and the principal technique used is the Krasnosel'skii-Pokrovskii principle of absence of bounded solutions.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

The calibre of the Foramen of Panizza in Crocodylus porosus is variable and under adrenergic control

The foramen of Panizza is located within the outflow tract of the crocodilian heart, between the left and right aortas. It has been suggested that the foremen of Panizza has a variable calibre, which could explain the profound changes in the distribution of flows and pressure profiles recorded in the right and left aortas. We investigated this possibility using a modified in-situ perfused heart preparation in combination with isolated strip preparations from the outflow tract. In the perfused heart preparation, bolus injections of adrenaline increased the resistance in the foramen of Panizza, indicating a decrease in its diameter. Isolated strip preparations from the outflow tract showed a concentration-dependent increase in tension in response to adrenaline, while vasoactive intestinal polypeptide caused a relaxation in adrenaline pre-contracted strip preparations. We propose that an increase in the diameter of the foremen of Panizza may be important during pulmonary to systemic shunts to allow blood to flow from the left to right aorta (reverse foramen flow) in order to supply the carotid and coronary arteries. During non-shunting conditions, a constricted foramen may prevent excess flow from the right to left aorta during diastole.

A hedging point strategy - balancing effluent quality, economy and robustness in the control of wastewater treatment plants

An operational space map is an efficient tool to compare a large number of operational strategies to find an optimal choice of setpoints based on a multicriterion. Typically, such a multicriterion includes a weighted sum of cost of operation and effluent quality. Due to the relative high cost of aeration such a definition of optimality result in a relatively high fraction of the effluent total nitrogen in the form of ammonium. Such a strategy may however introduce a risk into operation because a low degree of ammonium removal leads to a low amount of nitrifiers. This in turn leads to a reduced ability to reject event disturbances, such as large variations in the ammonium load, drop in temperature, the presence of toxic/inhibitory compounds in the influent etc. Hedging is a risk minimisation tool, with the aim to "reduce one's risk of loss on a bet or speculation by compensating transactions on the other side" (The Concise Oxford Dictionary (1995)). In wastewater treatment plant operation hedging can be applied by choosing a higher level of ammonium removal to increase the amount of nitrifiers. This is a sensible way to introduce disturbance rejection ability into the multi criterion. In practice, this is done by deciding upon an internal effluent ammonium criterion. In some countries such as Germany, a separate criterion already applies to the level of ammonium in the effluent. However, in most countries the effluent criterion applies to total nitrogen only. In these cases, an internal effluent ammonium criterion should be selected in order to secure proper disturbance rejection ability.

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.

Robust multivariable control of complex biological processes

This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that, performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible. (C) 2003 Elsevier Ltd. All rights reserved.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focussed recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the best choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy. (C) 2004 Elsevier B.V. All rights reserved.

Co-opting conservation: Migrant resource control and access to national park management in the Philippine uplands

The history of political and economic inequality in forest villages can shape how and why resource use conflicts arise during the evolution of national parks management. In the Philippine uplands, indigenous peoples and migrant settlers co-exist, compete over land and forest resources, and shape how managers preserve forests through national parks. This article examines how migrants have claimed lands and changed production and exchange relations among the indigenous Tagbanua to build on and benefit from otherwise coercive park management on Palawan Island, the Philippines. Migrant control over productive resources has influenced who, within each group, could sustain agriculture in the face of the state's dominant conservation narrative - valorizing migrant paddy rice and criminalizing Tagbanua swiddens. Upon settling, migrant farmers used new political and economic strengths to tap into provincial political networks in order to be hired at a national park. As a result, they were able to steer management to support paddy rice at the expense of swidden cultivation. While state conservation policy shapes how national parks impact upon local resource access and use, older political economic inequalities in forest villages build on such policies to influence how management affects the livelihoods of poor households.

A bang-bang PLL employing dynamic gain control for low jitter and fast lock times

Bang-bang phase detector based PLLs are simple to design, suffer no systematic phase error, and can run at the highest speed a process can make a working flip-flop. For these reasons designers are employing them in the design of very high speed Clock Data Recovery (CDR) architectures. The major drawback of this class of PLL is the inherent jitter due to quantized phase and frequency corrections. Reducing loop gain can proportionally improve jitter performance, but also reduces locking time and pull-in range. This paper presents a novel PLL design that dynamically scales its gain in order to achieve fast lock times while improving fitter performance in lock. Under certain circumstances the design also demonstrates improved capture range. This paper also analyses the behaviour of a bang-bang type PLL when far from lock, and demonstrates that the pull-in range is proportional to the square root of the PLL loop gain.

'Looking good, feeling better': Consumption, Control and the Aesthetics of Exclusivity in the Service Encounter

The majority of ‘service’ literature has focused on the production side of service work (i.e. employees and management), while treating the role of the customer and/or consumer as secondary (Korczynski and Ott, 2004). Those authors who have addressed the role consumption plays in shaping and maintaining individuals' self- identity have tended to overemphasize the dominance of consumer culture in shaping ‘our consciousness’ (Ritzer, 1999), with little in the way of empirical evidence to support these assertions. This paper develops the conceptualization of service work and consumer culture literature, by placing more emphasis on the customer in the service encounter. Using an ethnographic study of a ‘high class’ department store, this paper addresses employee and customer identity and the nature of managerial, employee and customer control within this ‘exclusive’ context. Of particular interest is how employees and customer’s ‘embody’ this control. Using Bourdieu’s (1986) conception of class and habitus, the concept of exclusivity goes beyond the management /service worker dyad by providing a means of investigating identity control by the organization over both customers and service workers. However, an organization’s exclusivity is not a closed normative pursuit of control, and shows this enterprise is part of a contested terrain, while revealing the ambiguity and ‘openness’ of control practices and pursuits. In order to uphold the ideal of exclusivity, management, service workers and customers must all engage in a precarious quest for establishing and maintaining a sense of control and/or identity. This paper demonstrates the continuing contradiction between bureaucratic practices of control and consumer culture, and highlights the need for research that investigates the context -dependent nature of control in service-related and consumer studies.

Improved joint control using a genetic algorithm for a humanoid robot

This paper describes experiments conducted in order to simultaneously tune 15 joints of a humanoid robot. Two Genetic Algorithm (GA) based tuning methods were developed and compared against a hand-tuned solution. The system was tuned in order to minimise tracking error while at the same time achieve smooth joint motion. Joint smoothness is crucial for the accurate calculation of online ZMP estimation, a prerequisite for a closedloop dynamically stable humanoid walking gait. Results in both simulation and on a real robot are presented, demonstrating the superior smoothness performance of the GA based methods.