摘要:

The paper presents a systematic methodology for designing tracking control of robotic motion. The methodology is completely based on numerical methods and corresponding recurrence relations. It produces recursive control laws which force the system to exhibit the desired error dynamics. A few explicit, easily realizable control algorithms are given and compared with the computed-torque scheme. Closed-loop stability and bounds on system uncertainties are investigated in detail. Control algorithms that use only position measurements are also analysed. A benchmark problem is solved to illustrate the use of proposed algorithms.

ISSN:0020-7179    

DOI:10.1080/00207179608921656

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

New absolute stability results that unify and extend existing structured singular value bounds for mixed uncertainty are developed using frequency-domain arguments. These bounds generalize prior upper bounds for mixed-μ by permitting the treatment of non-diagonal real uncertain blocks, as well as accounting for internal matrix structure in the uncertainty. Several specializations to well known absolute stability criteria from the classical literature are given, which allow for a systematic comparison of these results in addressing the problem of robust stability for real parameter uncertainty.

ISSN:0020-7179    

DOI:10.1080/00207179608921657

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

In this paper, we will give necessary and sufficient conditions for the Hurwitz stability of MIMO interval systems. As a consequence of this result, we will give a precise bound on the H∞norm of unstructured perturbations that can be tolerated by MIMO interval systems connected in feedback with these perturbations. We will also consider the robust version of the Popov problem that considers interval MIMO systems subject to nonlinear time invariant sector bounded perturbations and, in turn, obtain a robust stability condition of the Popov problem with mixed perturbations.

ISSN:0020-7179    

DOI:10.1080/00207179608921658

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

The paper presents a regularized orthogonal least squares learning algorithm for radial basis function networks. The proposed algorithm combines the advantages of both the orthogonal forward regression and regularization methods to provide an efficient and powerful procedure for constructing parsimonious network models that generalize well. Examples of nonlinear modelling and prediction are used to demonstrate better generalization performance of this regularized orthogonal least squares algorithm over the unregularized one.

ISSN:0020-7179    

DOI:10.1080/00207179608921659

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

In this paper, the output control problem for linear uncertain systems is investigated under the specific framework of quadratic stabilizability. The approach generalizes previous works to systems where both the state and input matrices suffer from structural uncertainty of norm bounded as well as interval type. The stabilizability conditions are translated into parametrical problems. The output stabilizability problem both in the static and dynamic aspects is investigated with the help of quadratic stabilizability and its dual notion ‘the quadratic detectability’. The dynamic output stabilization problem can first be formally expressed as a static one. In this case, the proposed approach does not enable us to deal with the complete uncertainty case where all the dynamic, control and output matrices are uncertain. The output dynamic compensation in the classical framework of observer design is also addressed.

ISSN:0020-7179    

DOI:10.1080/00207179608921660

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

A redesign of model reference adaptive control using a non-quadratic Lyapunov function for deriving a new adaptive law leads to a tracking errore(t) belonging to theL1+αsignal space for plants with relative degree one, where α > 0 is a design parameter. A choice of 0 < α < 1 leads to the energy of |e(t;)|(1+α)/2smaller than that with the standard adaptive law for α = 1. Simulation results indicate that the new adaptive control scheme with0 < α < 1improves system tracking performance. Preliminary analysis shows that the new scheme with a projection modification is also robust with respect to external disturbances.

ISSN:0020-7179    

DOI:10.1080/00207179608921661

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

A new fast orthogonal estimation algorithm is derived for a wide class of nonlinear stochastic models including training radial basis function neural networks. The selection of significant regressors and the estimation of unknown parameters in the presence of nonlinear noise sources are considered, and simulated examples are included to demonstrate the efficiency of the new procedure.

ISSN:0020-7179    

DOI:10.1080/00207179608921662

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

The paper is concerned with the problem of testing the robust strict positive realness (SPRness) of a family of rational functions with both the numerator and the denominator dependent on the same set of parameters. We show that this problem can be solved by using a series of Routh tables. In other words, the robust SPRness of the whole family can be tested by performing only a finite number of elementary operations (arithmetic operations, logical operations and sign tests).

ISSN:0020-7179    

DOI:10.1080/00207179608921663

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

This paper studies a mixedH2/H∞control problem with internal stability by means of memoryless state feedback, for smooth nonlinear control systems. The problem consists of combining the performance requirements of quadratic optimal controllers with the robustness properties ofH∞controllers. It is shown that under appropriate assumptions, the problem is solvable if a pair of cross-coupled Hamilton-Jacobi-Isaacs equations allows smooth solutions. Our approach to the mixedH2/H∞nonlinear control problem is drawn from the concepts of non-zero sum differential game, LaSalle's Invariance Principle and completion of squares. Analogous results are also developed for discrete-time nonlinear systems, by using the Taylor expansion argument. Finally, all the results obtained in affine systems are generalized to non-affine nonlinear systems.

ISSN:0020-7179    

DOI:10.1080/00207179608921664

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor

摘要:

This paper considers a robust state estimation problem for a new class of uncertain systems. The new uncertainty class introduced in the paper involves structured uncertainties which are required to satisfy a certain averaged integral quadratic constraint. This uncertainty class combines aspects of norm-bounded and stochastic uncertainty descriptions. The solution to the robust state estimation problem is obtained by solving a parametrized Riccati differential equation of the game type.

ISSN:0020-7179    

DOI:10.1080/00207179608921665

出版商:Taylor & Francis Group    

年代:1996

数据来源: Taylor