21 resultados para Multivariable Systems
Resumo:
A strongly connected decentralized control system may be made single channel controllable and observable with respect to any channel by decentralized feedbacks. It is noted here that the system example considered by Corfmat and Morse to illustrate this fact is already single channel controllable and observable, with respect to one of the channels. An alternate example which fits into the situation is presented in this item.
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A strongly connected decentralized control system may be made single channel controllable and observable with respect to any channel by decentralized feedbacks. It is noted here that the system example considered by Corfmat and Morse to illustrate this fact is already single channel controllable and observable, with respect to one of the channels. An alternate example which fits into the situation is presented in this item.
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In this paper, we consider the synthesis of decentralized dynamic compensators for large systems. The eliminant approach is used to obtain sufficient conditions for the existence of proper, stable, decentralized observer-controllers for stabilizing a large system. An illustrative example is given.
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Self-tuning is applied to the minimum variance control of non-linear multivariable systems which can be characterized by a ' multivariable Hammerstein model '. It is also shown that such systems are not amenable to self-tuning control if control costing is to be included in the performance criterion.
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The question of achieving decoupling and asymptotic disturbance rejection in time-invariant linear multivariable systems subject to unmeasurable arbitrary disturbances of a given class is discussed. A synthesis procedure which determines a feedback structure, incorporating an integral compensator, is presented.
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n this paper we study the genericity of simultaneous stabilizability, simultaneous strong stabilizability, and simultaneous pole assignability, in linear multivariable systems. The main results of the paper had been previously established by Ghosh and Byrnes using state-space methods. In contrast, the proofs in the present paper are based on input-output arguments, and are much simpler to follow, especially in the case of simultaneous and simultaneous strong stabilizability. Moreover, the input-output methods used here suggest computationally reliable algorithms for solving these two types of problems. In addition to the main results, we also prove some lemmas on generic greatest common divisors which are of independent interest.
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A new scheme for robust estimation of the partial state of linear time-invariant multivariable systems is presented, and it is shown how this may be used for the detection of sensor faults in such systems. We consider an observer to be robust if it generates a faithful estimate of the plant state in the face of modelling uncertainty or plant perturbations. Using the Stable Factorization approach we formulate the problem of optimal robust observer design by minimizing an appropriate norm on the estimation error. A logical candidate is the 2-norm, corresponding to an H�¿ optimization problem, for which solutions are readily available. In the special case of a stable plant, the optimal fault diagnosis scheme reduces to an internal model control architecture.
Resumo:
The paper deals with the basic problem of adjusting a matrix gain in a discrete-time linear multivariable system. The object is to obtain a global convergence criterion, i.e. conditions under which a specified error signal asymptotically approaches zero and other signals in the system remain bounded for arbitrary initial conditions and for any bounded input to the system. It is shown that for a class of up-dating algorithms for the adjustable gain matrix, global convergence is crucially dependent on a transfer matrix G(z) which has a simple block diagram interpretation. When w(z)G(z) is strictly discrete positive real for a scalar w(z) such that w-1(z) is strictly proper with poles and zeros within the unit circle, an augmented error scheme is suggested and is proved to result in global convergence. The solution avoids feeding back a quadratic term as recommended in other schemes for single-input single-output systems.
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The specific objective of this paper is to develop multivariable controllers that would achieve asymptotic regulation in the presence of parameter variations and disturbance inputs for a tubular reactor used in ammonia synthesis. A ninth order state space model with three control inputs and two disturbance inputs is generated from the nonlinear distributed model using linearization and lumping approximations. Using this model, an approach for control system design is developed keeping in view the imperfections of the model and the measurability of the state variables. Specifically, the design of feedforward and robust integral controllers using state and output feedback is considered. Also, the design of robust multiloop proportional integral controllers is presented. Finally the performance of these controllers is evaluated through simulation.
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In this paper, we present a decentralized dynamic load scheduling/balancing algorithm called ELISA (Estimated Load Information Scheduling Algorithm) for general purpose distributed computing systems. ELISA uses estimated state information based upon periodic exchange of exact state information between neighbouring nodes to perform load scheduling. The primary objective of the algorithm is to cut down on the communication and load transfer overheads by minimizing the frequency of status exchange and by restricting the load transfer and status exchange within the buddy set of a processor. It is shown that the resulting algorithm performs almost as well as a perfect information algorithm and is superior to other load balancing schemes based on the random sharing and Ni-Hwang algorithms. A sensitivity analysis to study the effect of various design parameters on the effectiveness of load balancing is also carried out. Finally, the algorithm's performance is tested on large dimensional hypercubes in the presence of time-varying load arrival process and is shown to perform well in comparison to other algorithms. This makes ELISA a viable and implementable load balancing algorithm for use in general purpose distributed computing systems.
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High temperature reaction calorimetry using molten lead berate as solvent has been used to study the thermochemistry of NdMnO3, YMnO3, La1-xSrxMnO3 (with 0 < x < 0.5), and Ln(0.5)Ca(0.5)MnO(3) (with Ln = La, Nd, Y), The enthalpies of formation of these multicomponent oxides from their binary constituents have been calculated from the measured enthalpy of drop solution, The energetic stability of the perovskite depends on the size of the A cation, The enthalpy of formation of YMnO3 (smallest A cation) is more endothermic than those of NdMnO3 and LaMnO3. The energetics of the perovskite also depends on the oxidation state of the B site's ions. In the La1-xSrxMnO3 system, the energetic stability of the structure increases with the Mn4+/Mn3+ ratio, The new values of the enthalpies of oxidations, with reliable standard entropies, were used to plot the phase stability diagram of the lanthanum-manganese-oxygen system in the temperature range 300-1100 K, The LaMnO3/MnO phase boundary evaluated in this study agrees with the one published by Atsumi et nl. calculated from thermogravimetric and conductivity measurements.
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Spin-density maps, deduced from polarized neutron diffraction experiments, for both the pair and chain compounds of the system Mn2+Cu2+ have been reported recently. These results have motivated us to investigate theoretically the spin populations in such alternant mixed-spin systems. In this paper, we report our studies on the one-dimensional ferrimagnetic systems (S-A,S-B)(N) where hi is the number of AB pairs. We have considered all cases in which the spin Sri takes on allowed values in the range I to 7/2 while the spin S-B is held fixed at 1/2. The theoretical studies have been carried out on the isotropic Heisenberg model, using the density matrix renormalization group method. The effect of the magnitude of the larger spin SA On the quantum fluctuations in both A and B sublattices has been studied as a function of the system size N. We have investigated systems with both periodic and open boundary conditions, the latter with a view to understanding end-of-chain effects. The spin populations have been followed as a function of temperature as well as an applied magnetic field. High-magnetic fields are found to lead to interesting re-entrant behavior. The ratio of spin populations P-A-P-B is not sensitive to temperature at low temperatures.
Resumo:
Giant magnetoresistance (GMR), which was until recently confined to magnetic layered and granular materials, as well as doped magnetic semiconductors, occurs in manganate perovskites of the general formula Ln(1-x)A(x)MnO(3) (Ln = rare earth; A = divalent ion). These manganates are ferromagnetic at or above a certain value of x (or Mn4+ content) and become metallic at temperatures below the curie temperature, T-c. GMR is generally a maximum close to T-c or the insulator-metal (I-M) transition temperature, T-im. The T-c and %MR are markedly affected by the size of the A site cation, [r(A)], thereby affording a useful electronic phase diagram when T-c or T-im is plotted against [r(A)]. We discuss GMR and related properties of manganates in polycrystalline, thin-film, and single-crystal forms and point out certain commonalities and correlations. We also examine some unusual features in the electron-transport properties of manganates, in particular charge-ordering effects. Charge ordering is crucially dependent on [r(A)] or the e(g) band width, and the charge-ordered insulating state transforms to a metallic ferromagnetic state on the application of a magnetic field.
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We have measured the thermopower (S) of hole-doped LaMnO3 systems in order to see its dependence on the Mn4+ content as well as to investigate other crucial factors that determine S. We have carried out hole doping (creation of Mn4+ by two distinct means, namely, by the substitution of La by divalent cations such as Ca and Sr and by self-doping without aliovalent substitution). The thermopower is sensitive not only to the hole concentration but also to the process employed for hole doping, which we explain as arising from the differences in the nature of the hole-doped states. We also point out a general trend in the dependence of S on hole concentration at high temperatures (T> T-c), similar to that found in the normal-state thermopower of the cuprates.
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Part I (Manjunath et al., 1994, Chem. Engng Sci. 49, 1451-1463) of this paper showed that the random particle numbers and size distributions in precipitation processes in very small drops obtained by stochastic simulation techniques deviate substantially from the predictions of conventional population balance. The foregoing problem is considered in this paper in terms of a mean field approximation obtained by applying a first-order closure to an unclosed set of mean field equations presented in Part I. The mean field approximation consists of two mutually coupled partial differential equations featuring (i) the probability distribution for residual supersaturation and (ii) the mean number density of particles for each size and supersaturation from which all average properties and fluctuations can be calculated. The mean field equations have been solved by finite difference methods for (i) crystallization and (ii) precipitation of a metal hydroxide both occurring in a single drop of specified initial supersaturation. The results for the average number of particles, average residual supersaturation, the average size distribution, and fluctuations about the average values have been compared with those obtained by stochastic simulation techniques and by population balance. This comparison shows that the mean field predictions are substantially superior to those of population balance as judged by the close proximity of results from the former to those from stochastic simulations. The agreement is excellent for broad initial supersaturations at short times but deteriorates progressively at larger times. For steep initial supersaturation distributions, predictions of the mean field theory are not satisfactory thus calling for higher-order approximations. The merit of the mean field approximation over stochastic simulation lies in its potential to reduce expensive computation times involved in simulation. More effective computational techniques could not only enhance this advantage of the mean field approximation but also make it possible to use higher-order approximations eliminating the constraints under which the stochastic dynamics of the process can be predicted accurately.