In the paper problems with dynamic decoupling of the left-invertible multi-input multi-output dynamic (MIMO) linear time invariant (LTI) plants are considered. It is presented an universal and efficient algorithm for synthesis of control system for proper, square, right and left invertible plants which can be both unstable and/or non-minimumphase.
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For parallel inverters system, controlling the output voltage in normal operation constantly is named the voltage control mode (VCM), and controlling the output current constantly in abnormal operation conditions (such as short circuit) is named the current control mode (CCM). The combined three-phase inverter topology is presented, the equivalent inverter topology with a LCL filter is obtained and mathematical models are built in VCM and CCM. A hybrid control strategy is proposed. The PID control and the repetitive control are used in VCM to obtain the fast dynamic responses and low harmonic distortions. On the other hand, the state feedback control is used in CCM. Pole assignment has been employed in designing parameter of the PID controller and state feedback, and the repetitive control design process is given. Experimental results validate the proposed control using two 400KVA parallel inverters.
PL
Dla równoległego systemu przekształtników zazwyczaj stosuje się system kontroli napięcia VCM i system kontroli prądu CCM (w warunkach specjalnych - np. zwarcia). Zaprezentowano topologie przekształtnika trójfazowego. Odpowiednia topologia przekształtnika z filtrem LCL została przedstawiona. Zaproponowano hybrydową strategię sterowania. System PID sterowania użyty w VCM zapewnia szybką odpowiedź dynamiczną i małe zniekształcenia. W układzie CCM użyto stałego sprzężenia zwrotnego. Sprawdzono położenie biegunów. Wyniki eksperymentu z dwoma 400kVA równoległymi przekształtnikami potwierdziły założenia.
The Generalized Predictive Controller (GPC) [1], [2] belongs to the general class of predictive controllers. The authors have proposed an alternative (although equivalent) formulation for the GPC in state space [7]. This formulation is based on a robust observer [5], and the poles selection is closely related to the controller robustness. An important feature of predictive controllers consists of their ability to take explicitly into account hard constraints in their formulation. However, their design must be accompanied by a guarantee of feasibility. There are some papers which deal with (his problem [4], [9], [8], [3], although all of them suppose that the state of the process can be measured on-line. However, in some cases, the design of the GPC proposed by the authors cannot measure online the process states since they are artificial states, that is to say, not related to physical magnitudes. The authors in paper [6] extend the results of [3] to the GPC in the case where all the states are online measurable. So the state estimation will be presented employing the same ideas of this previous work [6]. When the states have to be observed with the robust observer proposed, the authors show that there appears in the analysis a linear but time varying system perturbed with the error in the initial estimation of states. This initial error belongs to a known and bounded set. The main result states that if it is possible to find a collection of non-empty sets K_j that converge to the maximal robust control invariant set when j increases, the feasibility of GPC control law is guaranteed for all the sampling instants. Finally, this result is verified in a numerical example with a 2 states process.
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Pole assignment by feedback control of the second order coupled singular distributed parameter systems is discussed via functional analysis and operator theory in Hilbert space. The solutions of the problem and the constructive expression of the solutions are given by the generalized inverse one of bounded linear operator. This research is theoretically important for studying the stabilization and asymptotical stability of tlie second order coupled singular distributed parameter systems.
The aim of this paper is to investigate the relation between controllability and pole-assignment for positive linear discrete-time systems by analogy with nonconstrained systems on the basis of existing in the literature controllability criteria and controllability canonical form. Conditions on the system matrices and closed-loop eigenvalues are presented, which guarantee that there exists a positive feedback matrix with appropriate structure such that the closed-loop system is positive and should have a prescribed set of eigenvalues. The method and procedure for pole-assignment of controllable positive systems are proposed. A numerical example illustrating the procedure is provided.
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Some elementary optimization techniques, together with some not so well-known robustness measures and condition numbers, will be utilized in pole assignment. In particular, "Method 0" by Kautsky et al. (1985) for optimal selection of vectors is shown to be convergent to a local minimum, with respect to the condition number 1/2 ||X||_F^2 - ln |det X|. This contrasts with the misconception by Kautsky et al. that the method diverges, or the recent discovery by Yang and Tits (1995) that the method converges to stationary points.
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