• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.295-300
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• 2008

In this paper, a new looper controller is proposed to minimize the tension variation of a strip in the hot strip finishing mill. The proposed control technology is based on a receding horizon control (RHC) to satisfy the constraints on the control input/state variables. The finite terminal weighting matrix is used instead of the terminal equality constraint. The closed loop stability of the RHC for the looper system is analyzed to guarantee the monotonicity of the optimal cost. Furthermore, the RHC is combined with a 4SID(Subspace-based State Space System Identification) model identifier to improve the robustness for the parameter variation and the disturbance of an actuator. As a result, it is shown through a computer simulation that the proposed control scheme satisfies the given constraints on the control inputs and states: roll speed, looper current, unit tension, and looper angle. The control scheme also diminishes the tension variation for the parameter variation and the disturbance as well.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.429-434
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• 2013

This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.377-382
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• 2005

This paper presents a new method for the attitude control of planar space robots. In order to control highly constrained non-linear system such as a 3D space robot, the analytical formulation for the system with complex dynamics and effective control methodology based on the formulation, are not always obtainable. In the proposed method, correspondingly, a non-analytical but effective self-organizing modeling method for controlling a highly constrained system is proposed based on a polynomial data mining algorithm. In order to control the attitude of a planar space robot, it is well known to require inputs characterized by a special pattern in time series with a non-deterministic length. In order to correspond to this type of control paradigm, we adopt the Model Predictive Control (MPC) scheme where the length of the non-deterministic horizon is determined based on implementation cost and control performance. The optimal solution to finding the size of the input pattern is found by a solving two-stage programming problem.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1212-1217
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• 2008

This paper studies the feasibility of using the nonlinear model predictive control as a formation flight control algorithm for unmanned aerial vehicles. The optimal control inputs for formation flight are calculated through the cost function which incorporates the relative positions of the individual vehicles to maintain a desired formation and also the inequality constraints on inputs and states using the Karush-Kuhn-Tucker conditions. In the nonlinear model predictive control setting, the optimal control inputs are implemented in a receding horizon manner, which is suitable for dealing with dynamic constraints. Numerical simulations are executed for the validation of the proposed scheme.

• Korean Journal of Environmental Agriculture
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• v.29 no.1
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• pp.27-32
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• 2010

This study was conducted to reclassify Anryong series based on the second edition of Soil Taxonomy and to discuss the formation of Anryong series distributed on the mountain foot slope. Morphological properties of typifying pedon of Anryong series were investigated and physico-chemical properties were analyzed according to Soil survey laboratory methods manual. The typifying pedon of Anryong series has brown (7.5YR 4/4) loam Ap horizon (0-22 cm), strong brown (7.5YR 4/6) cobbly clay loam BAt horizon (22-35 cm), strong brown (7.5YR 4/6) cobbly clay loam Bt1 horizon (35-55 cm), reddish brown (5YR 5/4) cobbly clay loam Bt2 horizon (55-82 cm), and brown (7.5YR 5/4) cobbly clay loam Bt3 horizon (82-120 cm). The typifying pedon has an argillic horizon from a depth of 22 to 120 cm and a base saturation (sum of cations) of less than 35% at 125 cm below the upper boundary of the argillic horizon. It can be classified as Ultisol, not as Alfisol. It has udic soil moisture regime, and can be classified as Udult. Also that meets the requirements of Typic Hapludults. It has 18-35% clay at the particle-size control section, and have mesic soil temperature regime. Therefore Anryong series can be classified as fine loamy, mesic family of Typic Hapludults, not as fine loamy, mesic family of Ultic Hapludalfs. Anryong series occur on mountain foot slope positions in colluvial materials derived from acid and intermediate crystalline rocks. They are developed as Ultisols with clay mineral weathering, translocation of clays to accumulate in an argillic horizon, and leaching of base-forming cations from the profile for relatively long periods under humid and temperate climates in Korea.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1258-1263
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• 2011

This study was conducted to reclassify Asan series based on the second edition of Soil Taxonomy and to discuss the formation of Asan series distributed on the rolling to hilly areas. Morphological properties of typifying pedon of Asan series were investigated and physico-chemical properties were analyzed according to Soil survey laboratory methods manual. The typifying pedon of Asan series has dark yellowish brown (10YR 4/4) gravelly loam Ap horizon (0-18 cm), strong brown (7.5YR 5/6) gravelly clay loam BA horizon (18-30 cm), red (2.5YR 4/6) gravelly clay loam Bt1 horizon (30-52 cm), red (2.5YR 4/8) gravelly clay loam Bt2 horizon (52-98 cm), and red (2.5YR 4/8) gravelly clay loam C horizon (98-160 cm). The typifying pedon has an argillic horizon from a depth of 30 to 98 cm and a base saturation (sum of cations) of less than 35% at 125 cm below the upper boundary of the argillic horizon. It can be classified as Ultisol, not as Inceptisol. It has udic soil moisture regime, and can be classified as Udult. Also that meets the requirements of Typic Hapludults. It has 18-35% clay at the particle-size control section, and has mesic soil temperature regime. Therefore Asan series can be classified as fine loamy, mesic family of Typic Hapludults, not as fine loamy, mesic family of Typic Dystrudepts. Asan series occur on rolling to hilly areas in residual materials derived from granite gneiss, schist, and gneiss rocks. They are developed as Ultisols with clay mineral weathering, translocation of clays to accumulate in an argillic horizon, and leaching of base-forming cations from the profile for relatively long periods under humid and temperate climates in Korea.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.327-330
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• 1996

It is well known that the controller output limits have a signifiant effect on the closed loop system performance. Considering the input constraints in GPCF, an effective selection method of the control weighting(.gamma.) is proposed to reduce the amplitude and the rate of control signals so that control signals lie within the limits. It is based on the relation between control weighting(.gamma.) and optimal solution of the unconstrained GPCF. The GPCFIC algorithm chooses an .gamma. at each sampling time so that all unconstrained GPCF output over the control horizon satisfy the rate and the amplitude constraints. In order to evaluate the performance of the GPCFIC, the computer simulations have been done for level control of PWR steam generator in low power operation and shown satisfactory results.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.407-422
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• 2004

A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.20-23
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• 1996

This paper deals with the flexible manipulator with rotational and translational degrees of freedom, which has an arm of time-varying length with the prismatic joint. The tracking control problem of the flexible manipulator is considered. First we design the controller of the 2-type robust servo system based on the finite horizon optimal control theory for the trajectory planned as a discontinuous velocity. Next, to reduce the tracking error, we use the method of the dynamic programming and of modifying the reference trajectory in time coordinate. The simulation results show that the dynamic modeling is adequate and that the asymptotic stabilization of the flexible manipulator is preserved in spite of nonlinear terms. The PTP control error has been reduced to zero completely, and the trajectory tracking errors are reduced sufficiently by the proposed control method.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1147-1154
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• 2001

In this paper, a new iterative learning control scheme for discrete time nonlinear systems is proposed based on an objective function consisting of the output error and input energy. The relationships between the proposed ILC and the optimal control are described. A new input update law is proposed and its convergence is proved under certain conditions. In this proposed update law, the inputs in the whole control horizon are updated at once considered as one large vector. Some illustrative examples are given to show the effectiveness of the proposed method.