• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.496-501
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• 2016

This paper presents a design method of non-parallel distributed compensation (non-PDC) static output feedback controller for continuous- and discrete-time T-S fuzzy systems. The existence condition of static output feedback control law is represented in terms of linear matrix inequalities (LMIs). The proposed sufficient stabilizing condition does not need any transformation matrices and equality constraints and is less conservative than the previous result of [21].

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.826-830
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• 2004

Fault tolerant control method for 6-pole homopolar magnetic bearings are presented. If some of the coils or power amplifiers suddenly fail, the remaining coil currents change via a novel distribution matrix such that the same magnetic forces are maintained before and after failure. Lagrange multiplier optimization with equality constraints is utilized to calculate the optimal distribution matrix that maximizes the load capacity of the failed bearing. Some numerical examples of distribution matrices are provided to illustrate this control method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1332-1339
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• 1989

The problem of finding an admissible object trajectory for a cooperating two-robot system is investigated. The method is based on reformulating the problem as a nonlinear optimization problem with equality constraints in terms of the joint variables. The optimization problem is then solved numerically on a computer. The solution automatically gives the corresponding joint variable trajectories as well, thus eliminating the need for solving the inverse kinematic problem. The performance indices are chose in joint and cartesian spaces and computer simulations are performed.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.5
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• pp.801-810
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• 2004

The Primal-Dual Interior-Point (PDIP) method is currently one of the fastest emerging topics in optimization. This method has become an effective solution algorithm for large scale nonlinear optimization problems. such as the electric Optimal Power Flow (OPF) and natural gas and electricity OPF. This study describes major theoretical developments of the PDIP method as well as practical issues related to implementation of the method. A simple quadratic problem with linear equality and inequality constraints

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.29-32
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• 2001

This paper presents matrix inequality conditions for H$_2$optimal control of linear time-invariant descriptor systems in continuous and discrete time cases, respectively. First, the necessary and sufficient condition for H$_2$control and H$_2$controller design method are expressed in terms of LMls(linear matrix inequalities) with no equality constraints in continuous time case. Next, the sufficient condition for H$_2$control and H$_2$controller design method are proposed by matrix inequality approach in discrete time case. A numerical example is given in each case.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.614-620
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• 2009

The force distribution in multi-legged robots is a constrained, optimization problem. The solution to the problem is the set points of the leg contact forces for a particular system task. In this paper, an efficient and general formulation of the force distribution problem is developed using linear programming. The considered walking robot is a quadruped robot with a locked-joint failure, i.e., a joint of the failed leg is locked at a known place. For overcoming the drawback of marginal stability in fault-tolerant gaits, we define safety margin on friction constraints as the objective function to be maximized. Dynamic features of locked-joint failure are represented by equality and inequality constraints of linear programming. Unlike the former study, our result can be applied to various forms of walking such as crab and turning gaits. Simulation results show the validity of the proposed scheme.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.697-699
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• 2000

In this paper, an extension of model predictive controller for nonlinear process using Takagi-Sugeno(TS) fuzzy model is proposed Since the consequent parts of TS fuzzy model comprise linear equations of input and output variables. it is locally linear, and the Generalized Predictive Control(GPC) technique which has been developed to control Linear Time Invariant(LTI) plants, can be extended as a parallel distributed controller. Also fuzzy soft constraints are introduced to handle both equality and inequality constraints in a unified form. So the traditional constrained GPC can be transferred to a standard fuzzy optimization problem. The proposed method conciliates the advantages of the fuzzy modeling with the advantages of the constrained predictive control, and the degree of freedom is increased in specifying the desired process behavior.

• Journal of the Korean Mathematical Society
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• v.37 no.4
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• pp.625-643
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• 2000

In this paper we formulate an optimal control problem governed by time-delay Volterra integral equations; the problem includes control constraints as well as terminal equality and inequality constraints on the terminal state variables. First, using a special type of state and control variations, we represent a relatively simple and self-contained method for deriving new necessary conditions in the form of Pontryagin minimum principle. We show that these results immediately yield classical Pontryagin necessary conditions for control processes governed by ordinary differential equations (with or without delay). Next, imposing suitable convexity conditions on the functions involved, we derive Mangasarian-type and Arrow-type sufficient optimality conditions.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.49 no.2
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• pp.153-160
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• 2013

Control allocation is an important part of a system. It implements the function that map the desired command forces from the controller into the commands of the different actuators. In this paper, the authors present an approach for solving constrained control allocation problem in vessel system by using multi-parametric quadratic programming (mp-QP) algorithm. The goal of mp-QP algorithm applied in this study is to compute a solution to minimize a quadratic performance index subject to linear equality and inequality constraints. The solution can be pre-computed off-line in the explicit form of a piecewise linear (PWL) function of the generalized forces and constrains. The efficiency of mp-QP approach is evaluated through a dynamic positioning simulation for a vessel by using four tugboats with constraints about limited pushing forces and found to work well.

• 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.