In this work, a novel approach based on incremental state models is proposed for the modeling and control of multivariable delayed systems with colored noise. One of the key features of the new approach is that the proposed incremental state model compared with the non-incremental one, solves the problem of computing the target state in a natural way, since for a desired output, a zero incremental state can be taken as an objective. Moreover, the control action in an incremental form is equivalent to introduce an integral action, thereby cancelling the steady state errors, even in presence of disturbances. An optimal Linear Quadratic Regulator (LQR) control, based on the incremental model, is proposed and a Kalman filter is used to obtain the estimated state. Thus, another advantage of the proposed method is minimizing the output variance. Illustrative examples are chosen to evaluate the effectiveness of the proposed method.
In this work, a novel approach based on incremental state models is proposed for the modeling and control of multivariable delayed systems with colored noise. One of the key features of the new approach is that the proposed incremental state model compared with the non-incremental one, solves the problem of computing the target state in a natural way, since for a desired output, a zero incremental state can be taken as an objective. Moreover, the control action in an incremental form is equivalent to introduce an integral action, thereby cancelling the steady state errors, even in presence of disturbances. An optimal Linear Quadratic Regulator (LQR) control, based on the incremental model, is proposed and a Kalman filter is used to obtain the estimated state. Thus, another advantage of the proposed method is minimizing the output variance. Illustrative examples are chosen to evaluate the effectiveness of the proposed method. Read More
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