• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.7
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• pp.1411-1417
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• 2009

In this paper, we consider the design of $H_{\infty}$ control of linear discrete-time systems having no mathematical model. The basic approach is to use Q-learning which is a reinforcement learning method based on actor-critic structure. The model-free control design is to use not the mathematical model of the system but the informations on states and inputs. As a result, the derived iterative algorithm is expressed as linear matrix inequalities(LMI) of measured data from system states and inputs. It is shown that, for a sufficiently rich enough disturbance, this algorithm converges to the standard $H_{\infty}$ control solution obtained using the exact system model. A simple numerical example is given to show the usefulness of our result on practical application.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1708-1712
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• 2008

This paper describes a linear matrix inequality (LMI) approach to the design of robust low-order power system stabilizers (PSSs), which are used to damp out local-mode oscillations of synchronous generators. The performance of a PSS is expressed as the location of the closed-loop poles, and a single fixed-gain pole-placement controller is synthesized for a wide range of operating conditions. The synthesis results in simultaneous regional pole-placement stabilization. and is formulated as an LMI feasibility problem with a rank condition. A penalty method is applied to solve the rank-constrained LMI problem. Numerical experiments with a single-machine connected to an infinite bus system were performed to demonstrate the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.5
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• pp.226-228
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• 2006

This paper deals with a linear matrix inequality (LMI) approach to the design of a static output feedback controller that simultaneously stabilizes a finite collection of linear time-invariant plants. Simultaneous stabilization by static ouput feedback is represented in terms of LMIs with a rank condition. An iterative penalty method is proposed to solve the rank-constrained LMI problem. Numerical experiments show the effectiveness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1197-1200
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• 2010

The problem of designing a nonlinear sliding surface for an uncertain system is considered. The proposed sliding surface comprises a linear time invariant term and an additional time varying nonlinear term. It is assumed that a linear sliding surface parameter matrix guaranteeing the asymptotic stability of the sliding mode dynamics is given. The linear sliding surface parameter matrix is used for the linear term of the proposed sliding surface. The additional nonlinear term is designed so that a Lyapunov function decreases more rapidly. By including the additional nonlinear term to the linear sliding surface parameter matrix we obtain a nonlinear sliding surface such that the speed of responses is improved. We also give a switching feedback control law inducing a stable sliding motion in finite time. Finally, we give an LMI-based design algorithm, together with a design example.

• 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.17 no.7
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• pp.619-624
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• 2011

This paper presents a controller design method for a robust control problem with multiple constraints using genetic algorithms and LMI design method. A robust $H_{\infty}$ constraint with loop shaping and pole placement is used to address disturbance attenuation with error limits and desired transient specifications, in spite of the plant uncertainties and disturbances. In addition, a loop gain constraint is considered so as not to enlarge the loop gain unnecessarily. The robust $H_{\infty}$ constraint and pole placement constraint can be expressed in terms of two matrix inequalities and the loop gain constraint can be considered as an objective function so that genetic algorithms can be applied. Accordingly, a robust controller can be obtained by integrating genetic algorithms with LMI approach. The proposed controller design method is applied to a track-following system of an optical disk drive and is evaluated through simulation results.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.5
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• pp.18-25
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• 2002

In this paper, a novel computational approach for the stability analysis of the linguistic fuzzy system is proposed. The suggested analysis method is easily implemented by the recently spotlighted convex optimization techniques called Linear Matrix Inequalities (LMI). Compared with the previous works, the new method proposed herein is more relaxed and is applicable to not only the stabilization problem but also to the set-point regulation problem. Finally, the applicability of the suggested methodology is highlighted via computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.335-335
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• 2000

Applications such as unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs) and the time varying nature of their navigation, guidance and control systems motivate an integrated approach to trajectory general ion and trajectory tracking for autonomous vehicles. In this paper, an experimental testbed was designed for studying this integrated trajectory control approach. In this paper we apply the separating approach to an autonomous nonlinear vehicle system. A new linear matrix inequality based H$_{\infty}$ control technique for periodic time-varying systems is applied to the role of trajectory tracking. Trajectory general ion is accomplished by exploit ing the differential flatness property of the vehicle system; this at lows product ion of desired feasible nominal or reference trajectories from certain ″flat'system outputs. Simulation and experimental results are presented showing stable tracking of a periodic circular trajectory.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1744-1746
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• 2004

This paper focuses on the problem of asymptotic stabilization for time-delay systems. To this end, a memoryless state feedback controller is proposed. Then, based on the Lyapunov method, a delay-dependent stabilization criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. Certain free weighting matrices are used to express this relationship and linear matrix inequalities (LMIs)-based algorithm to design the controller stabilizing the system.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.233-236
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• 2015

In this paper, a nonlinear optimization problem is proposed to obtain a structured static output feedback controller for discrete time linear systems. The proposed optimization problem has LMI (Linear Matrix Inequality) constraints and a non-convex objective function. Using the conditional gradient method, we can obtain suboptimal solutions of the proposed optimization problem. Numerical examples show the effectives of the proposed approach.