• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.171-175
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• 1992

In this paper, we derive the optimal input-constrained control law which minimizes predictive control objective function subject to input constraints. In order to obtain the closed form of control law, three suboptimal methods are proposed and evaluated by simulation.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.566-569
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• 2009

In this paper, we propose a less conservative a linear matrix inequality (LMI) condition for the constrained robust model predictive control of systems with input constraints and polytopic uncertainty. Systems with input constraints are represented as perturbed systems with sector bounded conditions. For the infinite horizon control, closed-loop stability conditions are obtained by using a parameter dependent Lyapunov function. The effectiveness of the proposed method is shown by an example.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1655-1658
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• 1991

This paper considers the design and analysis of one-step ahead optimal and adaptive controllers, under the restriction that a known constraint on the input amplitude is imposed. It is assumed that the discrete-time single-input, single-output system to be controlled is linear, except for inequality constraints on the input. The objective function to be minimized is an one-step quadratic function, where polynomial weights on the input and output are included. Both the known parameter and unknown parameter (indirect adaptive controller) cases are examined.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.119-122
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• 2003

The aim of this paper is to propose a nonlinear controller for a single cart-type inverted pendulum using energy-based control scheme. Using a nonlinear model relating the angular position and velocity to the control input and a nonlinear controller is designed to regulate the angular position and velocity in the presence of input constraints. It is proved that the angular position and velocity converge to zero.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.835-841
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• 2014

In this paper we propose a swing-up strategy for a single inverted pendulum. The proposed method has a feature whereby can handle the input and output constraint of a pendulum in a systematic way. For the swing-up of a pendulum, we adopt a 2-DOF control structure that combines the feedforward and feedback control. In order to generate the swing-up feedforward trajectories that satisfy the input and output constraint, we formulate the problem of generating feedforward trajectories as a nonlinear optimal control problem subject to constraints. We illustrate that the proposed method is more flexible than the existing method and provides great freedom in choosing the actuator of the inverted pendulum. Through an experiment, we show that the proposed method can swing a pendulum upward effectively while satisfying all the imposed constraints.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1901-1904
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• 2003

MPC or model predictive control is representative of control methods which are able to handle physical constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global aymptotic stability can be obtained; until recently, use of infinite horizons was thought to be inevitable in this case. A globally stabilizing finite-horizon MPC has lately been suggested for neutrally stable continuous-time systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. The idea originates from the so-called small gain control, where the global stability is proven using a non-quadratic Lyapunov function. The newly developed finite-horizon MPC employs the same form of Lyapunov function as the terminal cost, thereby leading to global asymptotic stability. A discrete-time version of this finite-horizon MPC is presented here. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.112-119
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• 2001

A variety of input shaper has been proposed to reduce the residual vibration of flexible structures. Multi-hump input shaper is known to be robust for parameter variations. However, existing approach should solve the more complicated nonlinear simultaneous equations to improve the robustness of the input shaper with the additional constraints. In this paper, by proposing a graphical approach which uses convolution of shaper, the multi-hump convolution input shaper could be designed even if the constraints are added for further robustness. With a mass-damper-spring model, the better performance is obtained using the proposed new multi-hump convolution input shaper.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.178-183
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• 2003

This work is a modified version of an earlier work that was based on ellipsoidal type feasible sets. Unlike the earlier work, polyhedral types of invariant and feasible sets are adopted to deal with input constraints. The use of polyhedral sets enables the formulation of on-line algorithm in terms of QP (Quadratic Programming), which can be solved more efficiently than semi-def algorithms. A simple numerical example shows that the proposed method yields larger stabilizable sets with greater bounds on disturbances than is the case in the earlier approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.1032-1040
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• 2012

This paper proposes controller of leader robot considering following robot with input constraints based on leader-following approach. In the previous formation control researches, it was assumed that leader and follower is same object. If leader robot drives as maximum speed that the initial position errors still remain even if following robot have same velocity as a leader. In the situation that velocity of following robot is lower than its leader robot, following robot cannot follow leader robot. Furthermore, the following robot will not be able to made formation with leader robot and keep proximity communication or sensing range. Therefore, multiple mobile robot system using leader-following method should be guaranteed range to get information each other. In this paper, Leader robot is driving to goal position using linear controller and following robot is following trajectory to be made from leader robot. We assume that following robot has input constraints to realize different performance between leader robot and following robot. We design controller of leader robot for desired goal position including the errors between formation and following robot. Thus, we propose leader robot controller considering input constraints of following robot. Finally, we were able to confirm the validity of the proposed method based on simulation results.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.397-402
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• 2005

The guaranteed cost control problem for a class of linear systems with norm-bounded time-varying parameter uncertainties and input constraints is considered. A sufficient condition for the existence of guaranteed cost state feedback controllers is derived via the linear matrix inequality (LMI) approach, and a design procedure to guaranteed cost controllers is given. Furthermore, a convex optimization problem is formulated to determine the optimal guaranteed cost controller. An example is given to illustrate the effectiveness of the proposed results.