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This paper presents a method for designing linear controllers to achieve robust tracking and disturbance rejection properties. Wide range of references and disturbances such as step and sinusoid forms are covered. The proposed control structure comprises a combination of state-feedback and output-feedback strategies. The output-feedback structure is selected based on the internal model principle and...
A gradient flow algorithm model developed for the on-line robust pole assignment is proposed for solving Sylvester equations. The algorithm shows to be capable of synthesizing linear feedback control systems via on-line computing feedback gain matrix and desired closed-loop poles. Meanwhile, the close-loop system matrix is least sensitive to perturbation or uncertainty, and uniformly asymptotically...
This paper studies the state feedback robust H∞ control with memory for uncertain linear switched systems with multiple delays. Based on Multi-Lyapunov-function method, a sufficient condition in the LMI formulation is proposed for H∞ bounded stabilization analysis. The switching law and the robust H∞ controller for each subsystem with memory are designed. An illustrative example shows the feasibility...
The design problem of robust pole assignment in second-order linear systems is investigated. Based on the degrees offered by the parametric solutions of a matrix equation, the parametric expressions of all the state feedback control laws are proposed. By utilizing the parametric expressions of the state feedback control laws, the error performance of measuring the system's robustness is parameterized...
This paper presents a new modeling and robust control approach for active noise blocking (ANB). The proposed modeling technique is based on a new non-minimal state-space realization (NSSR) of continuous-time multiple-input multiple-output (MIMO) linear time-invariant (LTI) systems. The NSSR model generates a non-minimal set of states for a given system, using measured inputs and outputs, without differentation...
This paper presents a gradient flow approach for computing the robust controller for linear systems using state-derivative feedback such that the sensitivity of the closed-loop system eigenvalues to perturbations in the system and gain matrix is minimized. The approach can be applied for any controllable system with some restrictions when assigning zero poles. The nonsingular and singular open-loop...
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