• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.2066-2072
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• 2010

In this paper, a variable structure dynamic output feedback controller with an transformed sliding surface is designed for the improved robust control of a uncertain system under unmatched system uncertainty, matched input matrix uncertainty, and disturbance satisfying some conditions. This paper is extended from the results of the static output feedback VSS in [9]. To effectively remove the reaching phase problems, an initial condition of the dynamic output is determined. The previous some limitations on the dynamic output feedback variable structure controller is overcome in this systematic design. A stabilizing control is designed to generate the sliding mode on the predetermined sliding surface S=0 and as a results the closed loop exponential stability is obtained and proved together with the existence condition of the sliding mode on S=0 for all unmatched system matrix uncertainties. To show the usefulness of the algorithm, a design example and computer simulations are presented.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.4
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• pp.189-197
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• 2003

The problem of designing a parallel feedforward compensator (PFC) is considered for a class of non-square linear systems such that the closed-loop system is strictly passive. If a given square system has (vector) relative degree one and is weakly minimum phase, the system can be rendered passive by a state feedback. However, when the system states are not always measurable and the given output is considered, passivation (i.e. rendering passive) of a non-minimum phase system or a system with high relative degree cannot be achieved by any other methodologies except by using a PFC. To passivate a non-square system we first determine a squaring gain matrix and design a PFC such that the composite system has relative degree one and is minimum phase. Then the system is rendered strictly passvie by a static output feedback law. Necessary and sufficient conditions for the existence of the PFC and the squaring gain matrix are given by the static output feedback formulation, which enables to utilize linear matrix inequality (LMI). As an application of the scheme, an alternative way of replacing the role of velocity measurements is provided for the PD-control law of a convey-crane system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.685-689
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• 2005

In this paper, we consider a robust output feedback model predictive controller(MPC) design for Wiener model. Nonlinearities that couldn't be represented in static nonlinearity block of Wiener model are regarded as uncertainties in linear block. An dynamic output feedback controller design method is presented for Wiener MPC. According to MPC algorithm, the control law is computed based on linear matrix inequality(LMI)at each sampling time by solving convex optimization. Also, a new parameter dependent Lyapunov function is proposed to get a less conservative condition. The results are illustrated with numerical example.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.155-159
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• 2013

In this paper, a nonlinear matrix inequality problem and a nonlinear optimization problem are proposed for obtaining a structured static output feedback controller. The proposed nonlinear optimization problem has LMI (Linear Matrix Inequality) constraints and a nonlinear objective function. Using the conditional gradient method, the nonlinear optimization problem can be solved. A numerical example shows the effectiveness of the proposed approach.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.828-834
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• 2014

This paper presents a comparison among three types of approaches to an ARC (Active Roll Control) with an AARB(Active Anti-Roll Bar) for a vehicle system. Lateral acceleration and road profile are considered as disturbance. The ARC is designed with an LQ SOF (Linear Quadratic Static Output Feedback) control, $H_{\infty}$ control and SMC (Sliding Mode Control). These approaches are compared in terms of rollover prevention and ride comfort. For comparison, Bode plot analysis based on linear model and frequency response analysis based on CarSim simulation are performed.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.895-900
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• 2005

We derive a linear matrix inequality(LMI) condition guaranteeing that any invariant zeros of a triple (A, B, C) lie in the open left half plane of the complex plane, i.e. $C(sI-A)^{-1}B$ is minimum phase. The LMI condition is equivalent to a certain constrained Lyapunov matrix equation which can be found in many results relating to stability analysis or control design. We show that the LMI condition can be used to simplify various control engineering problems such as a dynamic output feedback control problem, a variable structure static output feedback control problem, and a nonlinear system observer design problem. Finally, we give some numerical examples.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1048-1052
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• 2007

This paper presents a rank-constrained linear matrix inequality(LMI) approach to simultaneous linear-quadratic(LQ) optimal control by static output feedback. Simultaneous LQ optimal control is formulated as an LMI optimization problem with a nonconvex rank condition. An iterative penalty method recently developed is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method, and the results are compared with those of previous work.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.620-625
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• 2008

The $H_{\infty}$ entropy in $H_{\infty}$ control theory is discussed based on investigating information transmission in continuous-time linear stochastic systems. It is proved that the stabilizing feedback does not change the time-average information transmission between system input and output, and the $H_{\infty}$ entropies of open- and closed-loop stable transfer functions are bounded by mutual information rate between input and output in the open-loop system. Furthermore, a new $H_2$ upper bound for $H_{\infty}$ entropy is introduced with a numerical example. Thus the $H_{\infty}$ entropy of a stable transfer function is sandwiched between $H_2$ norms of the original system and a static feedback system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.27.3-27
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• 2001

In this paper, a robust receding horizon controller for uncertain linear time-varying systems is presented in the dynamic output-feedback form. The existing output-feedback receding horizon controller in the literature is composed of a state observer and a static controller associated with the observer states (similar to LQC control), where the fundamental assumption is that the state observer will supply the exact states as time goes up. The performance of those controllers may be much degraded and even the closed-loop stability may not be guaranteed when the system suffers from disturbances and uncertainties or is time-varying. The proposed controller, which is not necessary to have the state-observer, overcomes such difficulties. Using matrix inequality conditions on the terminal weighting matrix, the closed-loop system stability is guaranteed. Numerical examples are ...