• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1139-1144
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• 1990

In this paper, we consider linear periodic discrete-time control systems under periodic compensation. Such a closed-loop system generally represents a periodic time-varying system. We examine the problem of finding a compensator such that the closed-loop system is realized as LTI model (if possible) with the closed-loop stability being satisfied. We present a necessary and sufficient condition for solving such problem and also give the characterization of realizable LTI models.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1255-1263
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• 2015

In the previous work, the authors studied the problem of robust discretization of linear time-invariant systems with polytopic uncertainties, where linear matrix inequality (LMI) conditions were developed to find an approximate discrete-time (DT) model of a continuous-time (CT) system with uncertainties in polytopic domain. The system matrices of obtained DT model preserved the polytopic structures of the original CT system. In this paper, we extend the previous approach to solve the problem of robust discretization of polytopic uncertain systems with aperiodic sampling. In contrast with the previous work, the sampling period is assumed to be unknown, time-varying, but contained within a known interval. The solution procedures are presented in terms of unidimensional optimizations subject to LMI constraints which are numerically tractable via LMI solvers. Finally, an example is given to show the validity of the proposed techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.752-757
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• 2000

This paper considers a decentralized control problem of dicrete LTI systems which have time delay between interconnections. This paper provides sufficient conditions for the decentralized controller to exist as a H$\infty$ disturbance attenuation ${\gamma}$ of a scaled system and shows that the controller can be designed by using the discrete standard $H_{\infty}$ control theory.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.878-883
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• 1990

There have been many approaches to solve the disturbance rejection problem in the control of LTI systems with state independent disturbances or possibly nonlinear state dependent disturbances. From the view point of each actuator, robot manipulators can be modeled as the second class of systems. With this model, M.Nakao et al. [1] introduced a decentralized control scheme based on interference estimation which is simple in its implementation and robust to the coupled dynamics and parameter variations. This paper systematically generalizes the control scheme to arbitrary finite dimensional LTI systems with disturbances. In doing so, we develop a disturbance observer theory for solving the disturbance rejection problem. We also present a discrete version of the theory with discussion of sampling and time-delay effects.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.583-586
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• 2013

We consider discrete-time LTI (Linear Time-Invariant) systems with constant input delays. The input delay is modeled by a first-order PdE (Partial difference Equation) and a backstepping transformation is employed to design a predictor feedback controller. The backstepping approach results in the construction of an explicit Lyapunov function, with which we prove the exponential stability of the closed-loop system formed by the predictor feedback. The numerical example demonstrates the design of the predictor feedback controller, and illustrates the validity of the exponential stability.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2427-2433
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• 2015

This paper presents an observer-based robust controller for constant reference tracking of linear time invariant systems with polytopic model uncertainties. To this end, this paper not only designs a robust integral controller gain but also suggests how to determine the robust observer gain and the observer model used in the observer. Since the observer model selection is not obvious due to the polytopic uncertainties, particular attention needs to be paid to that. This paper computes the robust controller and observer gains first. Then, the observer model is selected in a way that the whole closedloop is stable and LMIs are used in the middle of choosing the gains and observer model. Simulation examples show that the proposed observer-based feedback control successfully achieves robust reference tracking.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.489-494
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• 2013

This paper tackles the problem of designing a dynamic output-feedback control for linear discrete-time norm-bounded uncertain systems with input saturation. By employing a LPV (Linear Parameter Varying) instead of LTI (Linear Time-Invariant) control, the useful information on interpolation parameters appearing in the procedure of representing saturation nonlinearity as a convex polytope is additionally applied in the control design procedure. By solving the addressed problem that can be recast into a convex optimization problem characterized by LMIs (Linear Matrix Inequalities) with one prescribed scalar, the vertices of convex set containing an LPV output-feedback control gain and the associated maximal invariant set of initial states are simultaneously obtained.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.6-52
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• 2002

The method of identifying the plant models in this paper is the Observer Kalman filter identification (OKID) method. This method of system identification has several pertinent advantages. First, it assumes that the system in question is a discrete linear time-invariant (LTI) state-space system. Second, it requires only input and output data to formulate the model, no a priori knowledge of the system is needed. Third, the OKID method produces a psudo-Kalman state estimator, which is very useful for control applications. Last, the modal balanced realization of the system model means that tuncation errors will be small. Thus, even in the case of model order error the results of that error will...

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.995-1000
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• 2004

A digital adaptive flight control system is presented for a Japanese automatic landing flight experiment vehicle (ALFLEX). In previous adaptive control systems based on a linear-parameter-varying (LPV) form, the output behavior was excellent, while the behavior of the adjusted parameters was unsatisfactory. In the present study, to obtain a more appropriate parameter adjustment law, the relationship between the coefficient matrices in a continuous-time state equation and the coefficients of a pulse transfer function in a discrete system for conventional aircraft is investigated. As a result, it is revealed that the coefficients of the numerator can be treated as a linear function of dynamic pressure (linear-parameter-varying: LPV), while the coefficients of the denominator can be treated as constant (linear-time-invariant: LTI). From the above analysis, an improved parameter adjustment law is derived by reducing the number of the adjustment parameters. Simulation results also revealed both good output tracking and good parameter adjustment compared with the previous results.