Insensitive Pole Assignment Design

In this study, we propose a class of dynamic compensators based on linear function observers which achieve arbitrary pole assignment of the closed loop. The construction procedure directly utilizes Wang's algorithm (1992, 1996) for the static output feedback pole assignment problem, and the same technique can be applied to dual observers also. As a result, assuming the structure of either observer, the sufficient condition of the compensator's order is naturally derived. The condition is more transparent than the one proposed by Rosenthal and Wang (1996), and it is shown that both give the same minimal order under some mild assumptions.

(1976). Addendum to the paper ‘ On the pole assignment in linear systems with fixed order compensators ’. International Journal of Control: Vol. 23, No. 6, pp. 887-888.

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 .

This article investigates region stabilization issue of switched neural networks (SNNs) with multiple modes (MMs) and multiple equilibria (ME) via a pole assignment method. In such an SNN, every neuron is observed with more than one mode and unstable equilibrium point. First, SNNs with MMs and ME are modeled in terms of switched systems with unstable subsystems and ME. Second, a necessary and sufficient condition and a sufficient condition are, respectively, proposed for arbitrary switching paths pole assignment and arbitrary periodic/quasi-periodic switching paths (PSPs/QSPs) asymptotically region stabilizing pole assignment of switched linear time-invariant (LTI) systems with ME. It is shown that to stabilize a switched LTI system, some/all poles of all/some linear subsystems can be assigned to suitable locations of the right-half side of the complex plane. Third, based on the obtained pole assignment results, an asymptotical-region-stabilizing-control law observed as distributed state feedback controllers of MMs, asymptotical-region-stabilizing PSPs/QSPs, and a corresponding algorithm are all designed for asymptotical region stabilization of switched linear/nonlinear neural networks with MMs and ME. Finally, a numeral example is given to illustrate the effectiveness and practicality of the new results.

The theory of pole assignment in linear time invariant systems with incomplete state measurements is generalized to include the case in which a controllable observable plant of order n is augmented by a compensator of fixed dimensionality p (0≤p<n). The maximum sot of eigenvalues that can be preassigned arbitrarily is specified. The results previously available are shown to be particular cases of the theory proposed in the present paper, and Davison's (1970) algorithm is extended so as to apply to fixed order compensators design.

A sufficient rank condition for arbitrary pole assignability by static output feedback of m-input, p-output linear systems of McMillan degree n<mp is given. This condition is easy to check and is satisfied by the generic system. An effective computational method to compute the feedback laws assigning any self-conjugate set of closed-loop poles is also given.

The pole assignment problems of linear systems by decentralized static output feed-back are considered in this paper. A compactification of decentralized static feedback space, product Grassmannians, is introduced in this paper. Its degree under Plücker–Segre embedding is computed. Sufficient conditions for arbitrary and almost arbitrary pole assignability are given. It is also proved that the generic $m \times p$ system of McMillan degree n has arbitrary pole assignability by r-channel decentralized static output with $m_i $ inputs and $p_i $ outputs on the ith channel if $\sum_{i = 1}^r {m_i p_i } \geq n$ when the degree of the product Grassmannians is odd, or if a $\sum_{i = 1}^r {m_i p_i } > n$ and the local channels have either the same numbers of inputs or the same numbers of outputs when the degree of the product Grassmannians is even.

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.

In this paper a new design procedure is proposed that combines linear quadratic optimal control (LQ) with pole assignment. In LQ-problems the quadratic weights are usually found by trial and error to get good time behavior. In contrast the proposed method modifies a given state weighting matrix such that all closed-loop poles are located in a specified region of the complex s-plane. It is shown that this can be done with the smallest possible increase of the quadratic performance index under consideration. The procedure is extended to the design of robust control systems where the plant is described by a family of linear systems according to different operational conditions. The control of a F4E aircraft demonstrates the achievements of the new procedure.

This paper presents a continuous time solution to the problem of the design of a relatively optimal control, precisely, a dynamic control which is optimal with respect to a given initial condition and it is stabilizing for any other initial state. This technique provides a drastic reduction of the complexity of the controller and successfully applies to systems in which (constrained) optimality is necessary for some "nominal operation" only. The technique is combined with a pole assignment procedure. It is shown that once the closed-loop poles have been fixed and an optimal trajectory originating from the nominal initial state compatible with these poles is computed, a stabilizing compensator which drives the system along this trajectory can be derived in closed form. There is no restriction about the optimality criterion and the constraints. The optimization is carried out over a finite-dimensional parameterization of the trajectories. However, although the complexity of the compensator is not affected by the choice of cost and constraints, (the compensator dimension is fixed as a design data) it is not in general easy to optimize in the proposed space since, in general, the constraints are infinite dimensional so approximations are necessary. In the case of quadratic optimization with simultaneous pole assignment, an efficient solution based on convex quadratic programming is proposed

A new result of the problem of pole assignment by output feedback is presented. A simple condition is given under which min (n, m + r − 1) closed-loop poles can be assigned arbitrarily by a gain output feedback, where n, mand r are the dimensions of the state, output and input vectors, respectively. Under the same condition, a new lower bound for the number of poles assignable by a fixed-order dynamic compensator is given which improves considerably on the results of Breach and Pearson (1970) and Ahmari and Vacroux (1973). A design algorithm and illustrative examples are also given.

This paper presents a self-tuning controller that minimises a cost function incorporating system input, output and set-point variations, and adapts it in such a way that the closed-loop poles are located on prespecified locations. The link that exists between the classical control strategy of pole assignment and the suboptimal strategy of the self-tuning controller is demonstrated and made use of to produce a generalised controller which possesses the major advantages of both. The controller combines the robustness of pole assignment with the ease of reference following provided by suboptimal self tuning.

A technique is discussed for the selection of the closed loop poles in the output (or state) feedback problem. Each closed loop pole is placed on a circular arc whose radius corresponds to that pole's open loop natural frequency. It is shown that the damping value is the only parameter which can be changed so that the eigenvalues remain on the defined circle. The required gain matrix for pole placement can then be formulated as an unconstrained optimization problem. The Powell method and a heuristic search technique, called a genetic algorithm, are used in the optimization. A 6-DOF continuous time structural model with low damping and two closely spaced modes is used to obtain the required pole placement gain matrix. It is shown that the genetic algorithm gave overall better results than Powell's method in terms of minimizing the norm of the state and output pole placement gain. In addition, an eigenparameter sensitivity calculation was successful only in further reducing the norm in the state feedback case. Furthermore, it is shown that only velocity feedback terms need be considered. This has the advantage of a 50-percent reduction in the design space. (Author)

A new pole-placement algorithm for multi-input controllable systems is presented. The algorithm can be used to obtain real-valued feedback gains for arbitrarily specified real and complex, distinct or multiple eigenvalues. The multi-input controllable time-invariant system is converted to a single-input system. Pole assignment is achieved by making use of certain properties of the equation TF - AT = D , where A is the open-loop system matrix and F represents a matrix having the desired closed-loop eigenvalues.

Some points of the paper by N.K. Nichols (see ibid., vol.AC-31, p.643-5, 1986), concerning the robust pole assignment of linear multiinput systems, are clarified. It is stressed that the minimization of the condition number of the closed-loop eigenvector matrix does not necessarily lead to robustness of the pole assignment. It is shown why the computational method, which Nichols claims is robust, is in fact numerically unstable with respect to the determination of the gain matrix. In replying, Nichols presents arguments to support the choice of the conditioning of the closed-loop poles as a measure of robustness and to show that the methods of J Kautsky, N. K. Nichols and P. VanDooren (1985) are stable in the sense that they produce accurate solutions to well-conditioned problems.