Cytosine DNA methylation is a heritable epigenetic mark present in many eukaryotic organisms. Although DNA methylation likely has a conserved role in gene silencing, the levels and patterns of DNA methylation appear to vary drastically among different organisms. Here we used shotgun genomic bisulfite sequencing (BS-Seq) to compare DNA methylation in eight diverse plant and animal genomes. We found that patterns of methylation are very similar in flowering plants with methylated cytosines detected in all sequence contexts, whereas CG methylation predominates in animals. Vertebrates have methylation throughout the genome except for CpG islands. Gene body methylation is conserved with clear preference for exons in most organisms. Furthermore, genes appear to be the major target of methylation in Ciona and honey bee. Among the eight organisms, the green alga Chlamydomonas has the most unusual pattern of methylation, having non-CG methylation enriched in exons of genes rather than in repeats and transposons. In addition, the Dnmt1 cofactor Uhrf1 has a conserved function in maintaining CG methylation in both transposons and gene bodies in the mouse, Arabidopsis, and zebrafish genomes.

For discrete-time scalar systems, we propose an approach for designing feedback controllers of fixed order to minimize an upper bound on the peak magnitude of the tracking error to a given command input. The work makes use of linear programming to design over a class of closed-loop systems recently proposed for the rejection of non-zero initial conditions and bounded disturbances. We incorporate performance robustness in the form of a guaranteed upper bound on the peak magnitude of the tracking error under plant coprime factor uncertainty.

In this paper, we examine time-domain limitation-of-performance problems in feedback control system design. The main result is a theorem which gives a dual formulation to the problem of determining absolute limits on the time-domain shaping of the response to a fixed input. The duals that arise are particularly illuminating. They have a simple interpretation as optimizing the impulse response of a transfer function whose poles are readily constructed from the data. Much insight is obtainable from the dual, for example, in helping to classify classes of plants with the same quantitative behavior. New results on classical performance measures, such as overshoot and undershoot, are presented. We also examine minimization of the difference between the maximum and minimum values of the error response, a quantity we term fluctuation.

Two important practical criteria for most real control systems are that the controller has an integrator and that the closed-loop system has robust stability. In this paper we identify and characterize a grouping or classification of linear scalar discrete-time plants comprising three classes according to the best possible stability robustness margins against coprime factor uncertainty that can be obtained with integral controllers.

In this paper we present two new results on Bode-type integrals. Firstly, we obtain, for a given scalar or multivariable continuous-time plant, the infimum of the Bode sensitivity integral which can be obtained with any stabilizing controller. The result involves the unstable plant poles and, perhaps surprisingly, a subset of the plant nonminimum phase zeros. Secondly, we obtain an apparently new expression for the Bode integral for the complementary sensitivity for a stable discrete-time scalar system.

In this paper we investigate the exact solution, minimizing the l(infinity) norm of the regulated output for a fixed input in SISO discrete-time feedback control systems. This is achieved by allowing non-zero steady state value and parametrizing the output to have a rational transfer function with chosen poles on the stability boundary. Alongside these l(infinity)-optimal solutions, we obtain solutions in l(1) with the same order transfer functions and arbitrarily close l(infinity) norms.

We incorporate an arbitrary number of "candidate" positive distinct poles into the scalar l/sub 1/ optimization framework in order to obtain low-order rational suboptimal solutions to constrained l/sub 1/ optimization problems. Our approach uses a single linear program to minimize an upper bound on the l/sub 1/ norm and gives a solution which uses only the best out of the prespecified poles. Rational suboptimal solutions to a scalar two-block problem are obtained similarly.

For discrete-time scalar systems, we propose an approach for designing feedback controllers of fixed order to minimize an upper bound on the peak magnitude of the tracking error to a given command input. The work makes use of linear programming to design over a class of closed-loop systems proposed for the rejection of non-zero initial conditions and bounded disturbances. Performance robustness in the form of a guaranteed upper bound on the peak magnitude of the tracking error under plant uncertainty is incorporated into the formulation

We obtain rational suboptimal continuous-time solutions to some optimal control problems specified via time domain performance criteria. These include /spl Lscr//sub 1/ and /spl Lscr//sub /spl infin// norms and peak overshoot. The approach uses linear semi-infinite programming to compute weights for a given finite set of rational basis functions and makes the best possible use of the basis. The closed-loop transfer functions obtained satisfy appropriate interpolation constraints for internal stability and the formulation allows additional linear constraints to be incorporated.

Shows how value sets and the zero exclusion principle can be used to obtain results on the robust stability and design of controllers against a special infinite-dimensional l/sub 1/ norm bounded parametric uncertainty in both numerator and denominator of scalar discrete-time plants. This parametric uncertainty has properties of both parametric and unstructured uncertainty and allows standard H/sup /spl infin// design tools to be used without conservatism.

We present results on the incorporation of two poles into the solution of II optimisation problems where the solution order is constrained to be less than that for the true optimum. For given order of solution, using two poles can allow a smaller l(1) norm to be obtained than can be obtained with a truncated polynomial solution, or a solution with just one real pole. Linear programs achieving pole placement for two distinct poles are presented, along with some applications of duality theory to obtain pole locations for a simple problem involving a complex pair of poles.

AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.

AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.

This work contains results on properties of integrating feedback controllers which give maximal stability robustness against real coefficient uncertainty in the numerator and denominator coefficients of transfer functions of classes of linear discretetime scalar plants. The integrator imposes simply computed upper bounds on the size of the smallest destabilising plant numerator and denominator uncertainties. The ability for these bounds to be achieved for a given nominal plant depends on the existence of solutions of particular sign properties to interpolation problems. The first main result of this paper is to use these sign constraints to infer properties of the roots of corresponding controller polynomials. In particular it is shown how the robustness bound on denominator uncertainty cannot be achieved by a controller with any strictly unstable poles. The second main result concerns cancellation of nominal minimum phase plant zeros and its effect on robustness.

We consider the problem of determining whether a polynomial of a given order and having only nonnegative coefficients can be found to interpolate a given set of positive data. This problem arises in the design of maximally robust integrating feedback controllers for linear discrete-time plants and is also relevant to the design of nonovershooting control systems. We present an algorithm for determining whether such a polynomial exists for given interpolation data.

In this paper we investigate a dual formulation for the problem of designing linear time-invariant controllers which minimize the maximum value, and/or maximize the minimum value, of signals in the standard one-parameter feedback configuration. The reference input, which is permitted to be unstable, is fixed, and there are no disturbances. Some results concerning the influence of unstable plant poles and zeros, and unstable zeros of the reference input, on achievable overshoot and undershoot reduction are obtained.

This paper contains results on the design of integral feedback controllers for discrete-time SISO plants, with maximal stability robustness against real time-invariant coefficient uncertainty in the plant numerator. The main result is the characterisation of nominal plants into two classes, according to whether or not maximal robustness is limited by the need to avoid a cancellation between the perturbed plant numerator and the integrator pole. Optimal stability margins and remarks about robust design are given for both kinds of plant.

In this paper, we incorporate the placement of one real closed-loop pole into a compensator design framework based upon the Youla parameterization, duality theory, and linear programming. This framework has been used to design discrete-time compensators to solve the l/sub 1/ controller design problem as well as other related time-domain optimization problems. Previous work on these problems has focused on deadbeat systems. It is known that these can require high-order controllers. Part of the motivation for this work is to improve the tradeoff between controller order and performance over that, using deadbeat control.

This paper uses convex analysis for the pole assignment design of discrete-time SISO systems incorporating robust stability against norm bounded parametric perturbations in the plant transfer function. The method involves designing an overparameterized pole assignment controller for the nominal plant with the overparameterization chosen to reduce the size of changes in the closed-loop characteristic equation which result from plant perturbations. Sufficiency bounds on the l(p) norm of the perturbation guaranteeing stability are obtained.

In this paper minimum norm duality results are applied to the problem of finding the largest l/sub p/ ball containing the coefficients of only stable polynomials and centred at a nominal stable point in coefficient space for both discrete-time and continuous-time systems. The results of this work are then applied to the computation of the largest stable hypercube (l/sub /spl infin// ball) in coefficient space.<>