Multi-input Multi-output Plants Research Articles

Stabilization of a Set of Interpolated Plants: A Factorization Approach

Stabilization of a multi-input multi-output plant with variable operating conditions is considered. The plant is described as a linear interpolation of proper stable coprime factorizations of the transfer functions of two representative models which are defined at two representative operating points. This paper considers a certain set of interpolated models in which we expect the real plant is included. Stabilization of all interpolated models in the set by an interpolated controller and a fixed controller is considered. The problems are reduced to certain H∞ control problems. Stabilizability conditions are presented in terms of LMIs (linear matrix inequalities) in the state space.

Anti-Windup Design for MIMO Plants Having General Infinite and Unstable Zero Structure

In this paper an anti-windup scheme for multi-input, multi-output (MIMO) plants is presented. While the proposed anti-windup scheme has general applicability, attention in this paper is focused on issues concerned with the infinite and unstable (or non-minimum phase) plant zeros, as represented in the factorization of rational transfer function matrices provided by the generalized interactor matrix. This factorization can be used directly to obtain controllers providing triangular decoupling of the closed-loop system. It is argued that design for triangular decoupling of non-minimum phase plants is one way of designing linear controllers whose performance degrades gracefully in the presence of input saturations. In particular, by forgoing the requirement that the closed-loop system be diagonally decoupled, it is possible to obtain controllers capable of limiting peak control amplitudes without necessarily compromising controller bandwidth.

多入出力系に対するASPR化並列フィードフォワード補償器設計法

多入出力系に対するASPR化並列フィードフォワード補償器設計法

Feedback representation of precompensators: application to decoupling linear multi-input multi-output plants

In this paper we examine the problem of internally stabilizing, and simultaneously diagonally decoupling, a linear multivariable system by two-parameter compensation. Based on our earlier results (Boussaid and Guerin 1996) we prove that any given plant (P) of full row rank can be decoupled with stability by the considered configuration. Computation of the decoupling compensators follows by easy constructions. The decoupling problem with a minimum number of unstable zeros in the decoupled system is also formulated and solved in the ‘generic‘ case.

Multi-channel output gain margin improvement using generalized sampled-data hold functions

This paper considers the multichannel gain margin problem for linear time-invariant continuous-time multi-input multi-output plants controlled by memoryless generalized sampled-data hold functions (GSHF). It is proved that arbitrarily large output gain margins can be achieved by suitable selection of the sampling time and the hold function. We use state space methods and give a constructive design procedure. The controller we use is memoryless in the sense that the discrete-time closed-loop system has the same McMillan degree as the open-loop continuous-time plant. >

MIMOl 1-optimization with a scalar control

In Ref. 1, the author showed that some scalar mixed sensitivity minimization problems have rationall1-optimal solutions and computed these solutions. Here, a similar approach is applied to a multi-input multi-output (MIMO) plant. The general flavor of the solution is the same as in Ref. 1, but there is one distinct new feature. We prove that some of the outputs may be ignored, in the sense that they have no influence on the optimal solution and that all the operators corresponding to the remaining outputs have the same optimal norm. This fact suggests alternative methods for solving the problem and it is employed in the construction of an exact rationall1-optimal solution of a particular problem.

A unified theory for the CGT approach to adaptive control

The command generator tracker (CGT) approach to model reference adaptive control of linear time invariant multi-input multi-output plants which are not almost strictly positive real (ASPR) is considered. Three new algorithms are proposed which are characterized by the insertion of supplementary dynamics in (i) feedback with the plant; (ii) in parallel with the plant; and (iii) in cascade with the plant, respectively. The three different implementations are shown to be special cases of a metasystem representation for the adaptive system. The new algorithms extend earlier results by introducing adaptive gains for the supplementary dynamics in addition to adaptive gains for the controller. A stability proof is presented which shows that the error between the plant and model outputs is bounded in the presence of bounded input and output disturbances. If the model input is constant for t ≥ t 1, and no disturbances exist, then conditions are obtained for the choice of the design parameters in the parallel supplementary dynamics case which guarantee that the output error is asymptotically vanishing.

Design of G-interactor and its application to direct multivariable adaptive control

In the design of multi-input multi-output (MIMO) adaptive control systems an interactor plays an important role. The derivation of the interactor requires system parameter values unless the interactor is in diagonal form. This is a considerable restriction when the interactor is applied to the adaptive control system design. In MIMO adaptive control many parameters must be estimated to achieve good tracking. Over-parametrization causes many problems, e.g. bad tracking performance and long calculation time of control input. A design of interactor, called a G-interactor, for unknown MIMO plants is given. It is applied to MIMO adaptive control systems. The G-interactor requires minimum information on the plant, such as the relative degree of each element of the plant transfer matrix. For this design a canonical form, called the G-canonical form, of a matrix A is investigated. The canonical form is also used to eliminate redundant parameters of MIMO adaptive control systems. Numerical examples show the effect...

むだ時間を含む多変数離散値系に対するモデル規範形適応制御系の一設計

In spite of the large number of design methods for model reference adaptive control system (MRACS) have been proposed by the researchers of stability theorem, only a few studies of MRACS for multi-input multi-output (MIMO) plant with time-delay have been published to date.In this paper, a design method for discrete MRACS is proposed based on Lyapunov's direct method. The controlled plant is a MIMO linear plant with time-delays. It is shown that the proposed adaptive algorithms gurantee the convergency of plant's output to reference model's response by introducing an auxiliary input vector. For the adaptive algorithms proposed here, only available input-output date of the plant are used and no information on unknown plant parameter is required. Finally, the validity of the proposed adaptive algorithms is demonstrated by numerical examples.

Design of Deadbeat Controllers and Reduced-Order Observers for Linear Multivariable Discrete-Time Plants

In this paper, a method based upon the use of the Brunovsky canonical form [1] is presented for the design of control systems incorporating deadbeat reduced-order discrete-time observers for a class of linear multivariable discrete-time plants with in-accessible state vectors. The design method is illustrated by the synthesis of a regulator for a multi-input multi-output third-order plant.