The problem of disturbance rejection by constant measurement output feedback is studied. Necessary and sufficient conditions are given for the problem to have a solution. A simple procedure is described for the computation of the feedback that solves the problem. This consists in solving two linear equations over the ring of proper rational matrices.
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This paper deals with two important practical problems in motion control of robot manipulators: the measurement of joint velocities, which often results in noisy signals, and the uncertainty of parameters of the dynamic model. Adaptive output feedback controllers have been proposed in the literature in order to deal with these problems. In this paper, we prove for the first time that Uniform Global Asymptotic Stability (UGAS) can be obtained from an adaptive output feedback tracking controller, if the reference trajectory is selected in such a way that the regression matrix is persistently exciting. The new scheme has been experimentally implemented with the aim of confirming the theoretical results.
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We consider stabilizing a discrete-time LTI (linear time-invariant) system via state feedback where both the quantized state and control input signals are involved. The system under consideration is stabilizable and stabilizing state feedback has been designed without considering quantization, but the system's stability is not guaranteed due to the quantization effect. For this reason, we propose a hybrid quantized state feedback strategy asymptotically stabilizing the system, where the values of the quantizer parameters are updated at discrete time instants. We also extend the result to the case of static output feedback.
The paper considers a set of linear discrete-time systems with uncertain parameters. A method of synthesis of robust control which simultaneously stabilizes all the systems from this set is proposed. This method consists of two steps. First, a set of stochastic comparison systems with multiplicative noises is constructed such that if the stochastic system from this set is mean square stable then the corresponding system with uncertain parameters from the original set is robustly stable. Second, the simultaneous stabilization problem for the comparison system is solved. To find a gain matrix of the simultaneously stabilizing controller in the case of state feedback an LMI based algorithm is given and in the case of static output feedback a new method and convergent iteration algorithm are obtained.
An algorithmic method is presented for the computation of a reduced set of quadratic Plucker relations describing completely the Grassmann variety of the corresponding projective space. In particular, it is proven that a set of three terms homogeneous equations can be extracted from the whole set of quadratic Plucker relations. This set contains a specific number of equations, which exactly-constitute a reduced set of quadratic Plucker relations. This is achieved by using a simple criterion based on a correspondence between the coordinates of a decomposable vector and lexicographical orderings. In addition, the algorithm suggested is error-free from numerical computations. The above theory is used for the development of a unifying approach for pole assignment by state and output feedback, for asymptotic observer design and for zero assignment by squaring down for linear time-invariant regular type control systems.
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