Pole assignment techniques for multivariable systems using unity rank output feedback

It is shown that the problem of pole assignment by gain output feedback in linear time-invariant multivariable systems may be reduced to an algebraic optimisation problem, using the concept of virtual model following. The method requires no transformation of the open-loop system to a canonical form. A number of related problems involving combinations of pole placement with a secondary design objective are also discussed.

The problem of pole assignment in linear, multivariable systems using an unconstrained-rank feedback matrix is considered. The effect of output feedback of unspecified rank on the characteristic polynomial of a multivariable system is first studied. The results are then used to derive a recursive algorithm for pole assignment without any restrictions on the rank of the output feedback matrix used. The method is based on the pseudoinverse concept for obtaining least-squares solutions of sets of linear equations, and is computationally efficient.

This short paper deals with the problem of pole assignment with incomplete state observation. It is shown that if the system is controllable and observable, and if n \leq r + m - 1 , an almost arbitrary set of distinct closed-loop poles is assignable by gain output feedback, where n, r , and m are the numbers of state variables, inputs and outputs, respectively. This result improves considerably the ones obtained so far about this problem. Different from the conventional approach using the characteristic equation, an approach based on the properties of the eigenspaces of the closed-loop dynamics is used in this short paper, which gives a new light on the various problems in the linear system theory. It is also shown, as a direct consequence of this result, that the minimum order of the dynamic compensator required for almost arbitrary pole assignment of overall closed-loop system is not greater than n - m - r + 1 .

In this paper, the eigenstructure assignment of linear multivariable control systems is studied from a geometric point of view. For the class of systems in which the number of outputs plus the number of inputs exceeds the number of states, genericity properties relative to this problem are derived. It is shown, without any assumption on the genericity of the system, that the pole assignment can be carried out by choosing some closed-loop eigenvectors almost freely. The crucial point is that all the expected degrees of freedom in pole assignment are so described without redundancy, which fully justifies the practical interest of such techniques. Despite the technicality required for the derivation of intermediate results, the main result, which is an eigenstructure assignment algorithm, is very easy to implement because it is only based on the computation of certain sums and intersections of characteristic subspaces. Furthermore, it is shown how the basic tools developed here can be used to tackle the problem of finding a necessary and sufficient condition for exact pole assignment.

This paper highlights the importance of the co-efficient matrix of the numerator transfer function matrix in pole placement and stabilization assessment of multivariable control systems. The problem of pole assignment with non-unity-rank output feedback, obtained as the sum of unity rank output feedback in two stages, is discussed. The design equations of Seraji [5] formulated in terms of the appropriately partitioned co-efficient matrix of the system numerator transfer function matrix. The pole placement and stabilization assessment procedures are illustrated with numerical examples.

Pole assignment for linear systems by periodic output feedback

A computational approach is proposed to solve the minimum norm and/or robust pole assignment problem for linear periodic discrete-time systems. The proposed approach uses a periodic Sylvester equation based parametrization of the periodic pole assignment problem and exploits the non-uniqueness of the problem by imposing conditions on the norm of the resulting periodic state feedback and/or on the condition numbers of the periodic eigenvector matrices of the closed-loop system. The solution method relies on using gradient search methods on suitably defined cost functions. Explicit expression of the gradients of cost functions are derived and the efficient evaluation of the cost functions and gradients is discussed. Numerical examples illustrate the effectiveness of the proposed approach.

ABSTRACTThe paper considers the pole assignment and the stabilisation problem under the practically essential constraint, that the designed controllers have to be causal, because only in that case they will be realisable in real time. It is shown that in case of a strictly proper process, when the set of solutions of the pole assignment or stabilisation problem is not empty, then it always contains a non-empty subset of non-causal controllers. Moreover, according to the set of causal controllers, we have one of the three situations: (1) the set is empty, (2) the set has actually one element and (3) there exists a subset of causal solutions. The paper provides complete solutions for both problems in the form of instructions for building the corresponding sets of causal controllers. Drawing on examples of a double integrator with delay, the procedures are illustrated.

Robust partial pole assignment problem for high order control systems

The pole assignment problem for distributed parameter systems governed by analytic semigroups is discussed. Introducing unbounded feedback operators, we can solve the problem under a weaker restriction on the separation of the open-loop and the closed-loop poles. These types of feedback systems inherit the spectrum determined growth assumption of the open-loop systems. We first present a characteristic equation whose roots are the poles of the closed-loop system. Next we give a feedback element which realizes the desired pole assignment of the closed-loop system. We show an interesting result that an infinite number of the open-loop poles can be uniformly moved by means of a suitable linear feedback. We apply the results -to a heat system and a flexible structure for the cases of distributed controls and boundary controls.

We consider the problem of robust pole assignment for a linear time invariant plant with state feedback subject to time delay in the control input. For systems with a known time delay, we offer a parametric formula for the feedback gain matrix that will assign a desired set of closed-loop eigenvalues to the time-delay system. Secondly we consider systems subject to small input time delays and introduce an unconstrained optimisation algorithm for the computation of a state feedback matrix to deliver the desired pole placement in a manner that minimises the sensitivity of the eigenvalues to input time delays. The performance of the algorithm is compared against an alternative robust pole placement method from the recent literature and found to give significantly reduced time delay sensitivity.

In this paper, a theory of polynomial and rational matrix interpolation is introduced and applied to problems in systems and control. The polynomial matrix interpolation theory is first outlined and then applied to solving matrix equations; it is also used in pole assignment and other control problems. Rational matrix interpolation is also discussed and it is used to solve rational matrix equations including the model matching problem.

This paper considers pole assignment and robust pole assignment problems for discrete-time linear periodic systems by using linear periodic state feedback. The monodromy matrix of the closed-loop system is represented in a special form. By combining this special form with our recent result on solutions to a class of generalized Sylvester matrix equations, a complete parametric approach for pole assignment via periodic state feedback is proposed. The free parameters existing in the solutions to pole assignment are further used to achieve robustness performances. The robust pole assignment problem is converted into a nonconvex optimization problem. Numerical examples illustrate the effectiveness of the proposed approaches.

Enclosure methods are described for the solution of linear and nonlinear systems of equations. These methods produce high precision solutions with the help of interval mathematics and the implemented optimal scalar product, e.g. in Pascalsc. Some problems of control theory are reformulated, so that they can be solved with the help of the enclosure methods. Especially, the problem of pole assignment is discussed in detail.KeywordsSingular VectorControllability MatrixLinear Equation SystemPole AssignmentInterval VectorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Sensitivity analysis of the feedback synthesis problem (FSP) for linear multivariable systems is presented. Both local linear and nonlocal nonlinear perturbation bounds are derived using the Schur form of the closed-loop state matrix. Condition numbers for the general FSP and the pole assignment problem in particular are given. Restrictions are imposed only on the degrees of the invariant polynomials of the closed-loop matrix but not on its spectrum.