Damping ratio of polynomials with perturbed coefficients

Let a family of polynomials be P(s)=t ₀Sⁿ+t₁s ^n-1 . . .+t_n where O<α _j⩽t_j⩽β. Recently, C.B. Soh and C.S. Berger have shown that a necessary and sufficient condition for this equation to have a damping ratio of φ is that the 2ⁿ⁺¹ polynomials in it which have t_k=α_k or t_k=β_k have a damping ratio of φ. The authors derive a more powerful result requiring only eight polynomials to be Hurwitz for the equation to have a damping ratio of φ using Kharitonov's theorem for complex polynomials     

Direct state-space solution to the discrete-timeH∞ one-block problem

A general state-space representation is used to allow a complete formulation of the H_∞ optimization problem without any invertibility condition on the system matrix, unlike existing solutions. A straightforward approach is used to solve the one-block H_∞ optimization problem. The parameterization of all solutions to the discrete-time H_∞ suboptimal one-block problem is first given in transfer function form in terms of a set of functions in H _∞ that satisfy a norm bound. The parameterization of all solutions is also given as a linear fractional representation     

Robust stability and performance via fixed-order dynamiccompensation: the discrete-time case

A discrete-time feedback-control-design problem involving parametric uncertainty is considered. A quadratic bound suggested by recent work on discrete-time state-space H_∞ theory is utilized in conjunction with the guaranteed cost approach to guarantee robust stability with a robust performance bound. The principal result involves sufficient conditions for characterizing robust full- and reduced-order controllers with a worst case H ₁ performance bound     

Efficient algorithms for system diagnosis with both processor andcomparator faults

For the comparison-based self-diagnosis of multiprocessor systems, an extended model that considers both processor and comparator faults is presented. It is shown that in this model the system diagnosability is t⩽Zδ/2Z, where δ is the minimum vertex degree of the system graph. However, if the number of faulty comparators is assumed not to exceed the number of faulty processors, the diagnosability of the model reaches t⩽δ. An optimal O(|E|) algorithm, where E is the set of comparators, is given for identifying all faulty processors and comparators, provided that the total number of faulty components does not exceed the system diagnosability, and an O(|E|)² algorithm for the case t⩽δ is also presented. These efficient algorithms determine the faulty processors by calculating each processor's weight, which is mainly defined by the number of adjacent relative tests stating `agreement'. After sorting the processors according to their weights, the algorithms determine all faulty components by separating the sorted processor list     

Linear and nonlinear algorithms for identification in H∞ with error bounds

A linear algorithm and a nonlinear algorithm for the problem of system identification in H_∞ posed by Helmicki et al. (1990) for discrete-time systems are presented. The authors derive some error bounds for the linear algorithm which indicate that it is not robustly convergent. However, the worst-case identification error is shown to grow as log(n), where n is the model order. A robustly convergent nonlinear algorithm is derived, and bounds on the worst-case identification error (in the H_∞ norm) are obtained     

Mixed H2/H∞ control:a convex optimization approach

The problem of finding an internally stabilizing controller that minimizes a mixed H₂/H_∞ performance measure subject to an inequality constraint on the H_∞ norm of another closed-loop transfer function is considered. This problem can be interpreted and motivated as a problem of optimal nominal performance subject to a robust stability constraint. Both the state-feedback and output-feedback problems are considered. It is shown that in the state-feedback case one can come arbitrarily close to the optimal (even over full information controllers) mixed H₂/H_∞ performance measure using constant gain state feedback. Moreover, the state-feedback problem can be converted into a convex optimization problem over a bounded subset of (n×n and n ×q, where n and q are, respectively, the state and input dimensions) real matrices. Using the central H_∞ estimator, it is shown that the output feedback problem can be reduced to a state-feedback problem. In this case, the dimension of the resulting controller does not exceed the dimension of the generalized plant     

H∞ analysis and synthesis ofdiscrete-time systems with time-varying uncertainty

The problems of H_∞ analysis and synthesis of discrete-time systems with block-diagonal real time-varying uncertainty are considered. It is shown that these problems can be converted into scaled H_∞ analysis and synthesis problems. The problems of quadratic stability analysis and quadratic stabilization of these types of systems are dealt with as a special case. The results on synthesis are established for general linear dynamic output feedback control     

Decoupling of square singular systems via proportional statefeedback

Necessary and sufficient conditions for the decoupling of a solvable square singular system Ex˙(t)=Ax(t)+Bu(t ) with output y(t)=Dx(t), through an admissible control law of the form u(t)=Kx(t)+Hr(t) where H is a square nonsingular matrix. It has been shown that for a given singular system that satisfies these conditions, a propagational state feedback exists for which the system's transfer function is a diagonal, nonsingular, and proper rational matrix. The proofs of the main results are constructive and provide a procedure for computing an appropriate proportional state feedback     

Discrete-time filtering for linear systems with non-Gaussianinitial conditions: asymptotic behavior of the difference between theMMSE and LMSE estimates

The authors consider the one-step prediction problem for discrete-time linear systems in correlated plant and observation Gaussian white noises, with nonGaussian initial conditions. They investigate the large time asymptotics of ϵ_t, the expected squared difference between the MMSE and LMSE (or Kalman) estimates of the state of time t given past observations. They characterize the limit of their error sequence {ϵ_t, t=0,1,. . .} and obtain some related rates of convergence; a complete analysis is provided for the scalar case. The discussion is based on explicit representations for the MMSE and LMSE estimates, recently obtained by the authors, which display the dependence of these quantities on the initial distribution     

Robust H∞ control for linear systems withnorm-bounded time-varying uncertainty

Robust H_∞ control design for linear systems with uncertainty in both the state and input matrices is treated. A state feedback control design which stabilizes the plant and guarantees an H_∞-norm bound constraint on disturbance attenuation for all admissible uncertainties is presented. The robust H_∞ control problem is solved via the notion of quadratic stabilization with an H_∞ -norm bound. Necessary and sufficient conditions for quadratic stabilization with an H_∞-norm bound are derived. The results can be regarded as extensions of existing results on H_∞ control and robust stabilization of uncertain linear systems     

Strict aperiodic property of polynomials with perturbedcoefficients

Let a family of polynomials be P(s)=t ₀sⁿ+t₁s ⁿ±¹ + . . . + t_n where 0<a_j⩽t_j⩽b _j. V.L. Kharitonov (1978) derived a necessary and sufficient condition for the above equation to have only zeros in the open left-half plane. The present authors derive some similar results for the equation to be strictly aperiodic (distinct real roots)     

Decomposition of 2-D linear systems into 1-D systems in thefrequency domain

A method is presented for the decomposition of the frequency domain of 2-D linear systems into two equivalent 1-D systems having dynamics in different directions and connected by a feedback system. It is shown that under some assumptions the decomposition problem can be reduced to finding a realizable solution to the matrix polynomial equation X(z₁)P(z₂ )+Q(z₁)Y(z₂ )=D(z₁, z₂). A procedure for finding a realizable solution X(z₁ ), Y(z₂) to the equation is given     

Damping margins of polynomials with perturbed coefficients

Considers the polynomial P(s)=t₀ Sⁿ+t₁ S^n-1 +···+t_n where 0<a _j⩽t_j⩽b_j. Recently, V.L. Kharitonov (1978) derived a necessary and sufficient condition for this polynomial to have only zeros in the open left-half plane. Two lemmas are derived to investigate the existence of theorems similar to the theorem of Kharitonov. Using these lemmas, the theorem of Kharitonov is generalized for P(s) to have only zeros within a sector in the complex plane. The aperiodic case is also considered     

L2-gain analysis of nonlinear systems andnonlinear state-feedback H∞ control

Previously obtained results on L2-gain analysis of smooth nonlinear systems are unified and extended using an approach based on Hamilton-Jacobi equations and inequalities, and their relation to invariant manifolds of an associated Hamiltonian vector field. On the basis of these results a nonlinear analog is obtained of the simplest part of a state-space approach to linear H_∞ control, namely the state feedback H_∞ optimal control problem. Furthermore, the relation with H_∞ control of the linearized system is dealt with     

H∞ optimal control as a weightedWiener-Hopf problem

It is shown that H_∞ optimization is equivalent to weighted H₂ optimization in the sense that the solution of the latter problem also solves the former. The weighting rational matrix that achieves this equivalence is explicitly computed in terms of a state-space realization. The authors do not suggest transforming H_∞ optimization problems to H₂ optimization problems as a computational approach. Rather, their results reveal an interesting connection between H_∞ and H₂ optimization problems which is expected to offer additional insight. For example, H₂ optimal controllers are known to have an optimal observer-full state feedback structure. The result obtained shows that the minimum entropy solution of H_∞ optimal control problems can be obtained as an H₂ optimal solution. Therefore, it can be expected that the corresponding H_∞ optimal controller has an optimal observer-full state feedback structure     

Necessary and sufficient conditions for mixedH2 and H∞ optimal control

It is shown that D.S. Bernstein and W.M. Hadad's (ibid., vol.34, no.3, p.293, 1989) necessary condition for full-order mixed H ₂ and H_∞ optimal control is also sufficient, and that J.C. Doyle et al.'s (Proc. Amer. Control Conf., p.2065, 1989) sufficient condition for full-order mixed H₂ and H_∞ optimal control is also necessary. They are duals of one another     

Optimal distributed t-resilient election in completenetworks

The problem of distributed leader election in an asynchronous complete network, in the presence of faults that occurred prior to the execution of the election algorithm, is discussed. Failures of this type are encountered, for example, during a recovery from a crash in the network. For a network with n processors, k of which start the algorithm that uses at most O(n log k +n+kt) messages is presented and shown to be optimal. An optimal algorithm for the case where the identities of the neighbors are known is also presented. It is noted that the order of the message complexity of a t-resilient algorithm is not always higher than that of a nonresilient one. The t-resilient algorithm is a systematic modification of an existing algorithm for a fault-free network     

Minimum H∞-norm regulation of lineardiscrete-time systems and its relation to linear quadratic discretegames

A solution is derived to the H_∞-optimization problem that arises in multivariable discrete-time regulation when the controller has full access to the state vector. The solution method is based on the close relations that exist between linear quadratic differential game theory and H_∞-optimization. The existing theory of discrete-time quadratic games is readily applied in order to derive the solution to a finite-time horizon version of the H_∞ -optimization problem. The solution of the infinite-time horizon H_∞-optimization problem is obtained by formally taking the limit of the number of stages to infinity     

The application of scheduled H∞controllers to a VSTOL aircraft

The authors apply H_∞-designed controllers to a generic VSTOL (vertical and short takeoff and landing) aircraft model GVAM. The design study motivates the use of H _∞ techniques, and addresses some of the implementation issues which arise for multivariable and H_∞-designed controllers. An approach for gain scheduling H_∞ controllers on the basis of the normalized comprime factor robust stabilization problem formulation used for the H_∞ design is developed. It utilizes the observer structure unique to this particular robustness optimization. A weighting selection procedure, has been developed for the associated loop-shaping technique used to specify performance. Multivariable controllers pose additional problems in the event of actuator saturations, and a desaturation scheme which accounts for this is applied to the GVAM. A comprehensive control law was developed and evaluated using the Royal Aerospace Establishment piloted simulation facility     

On recursive, O(N) partitioning of a digitizedcurve into digital straight segments

A simple online algorithm for partitioning of a digital curve into digital straight-line segments of maximal length is given. The algorithm requires O(N) time and O(1) space and is therefore optimal. Efficient representations of the digital segments are obtained as byproducts. The algorithm also solves a number-theoretical problem concerning nonhomogeneous spectra of numbers