• Structural Engineering and Mechanics
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• v.34 no.5
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• pp.581-595
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• 2010

This paper presents topology optimization of geometrically and materially nonlinear structures using a bi-directional evolutionary optimization (BESO) method. To maximum the stiffness of nonlinear structures under prescribed design load, the complementary work is selected as the objective function of the optimization. An optimal design can be obtained by gradually removing inefficient material and adding efficient ones. The proposed method can be applied to a series of geometrically and/or materially nonlinear structures. The results show considerable differences in topologies and stiffness of the optimal designs for linear and nonlinear structures. It is found that the optimal designs for nonlinear structures are much stiffer than those for linear structures when large design loads (which result in significantly nonlinear deformations) are applied.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.160-170
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• 2008

Temperature control of an enclosed thermal system which has many applications including Rapid Thermal Processing (RTP) of semiconductor wafers showed an input-constraint violation for nonlinear controllers due to inherent strong coupling between the elements [1]. In this paper, a constrained nonlinear optimal control design is developed, which accommodates input constraints using the linear algebraic equivalence of the nonlinear controllers, for the temperature control of an enclosed thermal process. First, it will be shown that design of nonlinear controllers is equivalent to solving a set of linear algebraic equations-the linear algebraic equivalence of nonlinear controllers (LAENC). Then an input-constrained nonlinear optimal controller is designed based on that LAENC using the constrained linear least squares method. Through numerical simulations, it is demonstrated that the proposed controller achieves the equivalent performances to the classical nonlinear controllers with less total energy consumption. Moreover, it generates the practical control solution, in other words, control solutions do not violate the input-constraints.

• Journal of IKEEE
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• v.11 no.1 s.20
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• pp.1-14
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• 2007

In this paper, a design of an integral augmented nonlinear optimal variable structure system(INOVSS) is presented for the prescribed output control of uncertain MIMO systems under persistent disturbances. This algorithm basically concerns removing the problems of the reaching phase and combining with the nonlinear optimal control theory. By means of an integral nonlinear sliding surface, the reaching phase is completely removed. The ideal sliding dynamics of the integral nonlinear sliding surface is obtained in the form of the nonlinear state equation and is designed by using the nonlinear optimal control theory, which means the design of the integral nonlinear sliding surface and equivalent control input. The homogeneous $2{\upsilon}(\kappa)$ form is defined in order to easily select the $2{\upsilon}$ or even $(\kappa)-form$ higher order nonlinear terms in the suggested sliding surface. The corresponding nonlinear control input is designed in order to generate the sliding mode on the predetermined transformed new surface by means of diagonalization method. As a result, the whole sliding output from a given initial state to origin is completely guaranteed against persistent disturbances. The prediction/predetermination of output is enable. Moreover, the better performance by the nonlinear sliding surface than that of the linear sliding surface can be obtained. Through an illustrative example, the usefulness of the algorithm is shown.

• 전기의세계
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• v.26 no.2
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• pp.84-88
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• 1977

In this paper we apply the maximum principle to design of time optimal nonlinear sampled-data control systems. We introduce the general design procedures and the mathematical formalas for time optimal processes and trajectories. Then we show the application of the technique to determine the optimal control signal, control sequence, switching time and sampling period to the given 4th order process.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.533-536
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• 2014

In this paper, a near optimal decentralized observer-controller design method is proposed for ramp metering systems based on SDRE (State Dependent Riccati Equation) approach. The optimal nonlinear observer gain is parameterized in terms of the solution matrix of an SDRE. This paper gives a simple algorithm to compute the near optimal observer gain. The optimal control design problem is also considered. Finally, numerical simulation results are given to illuminate the effectiveness and practicality of the proposed design method.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1086-1089
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• 2012

We propose a near optimal controller design method for ramp metering based on SDRE (State Dependent Riccati Equation) approach. We parameterize the optimal nonlinear controller in terms of the solution matrices of an SDRE. We also give a simple algorithm to obtain the controller gain. Finally we give numerical results to show the effectiveness of the proposed near optimal traffic controller design method.

• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1151-1161
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• 2014

Despite the fact that the optimal design for nonlinear model depends on the unknown quantity of parameter to estimate basically, its popularity is growing in bio and engineering statistics area since all those models in the area are virtually nonlinear. In this paper we have dealt with the case when the researcher has multiple objectives in experimentation, decision among the competing models, protection against the departure from the assumed model, and the con icting interests among design criteria. To tackle these issues we attempted several new approaches which are taking advantage of the easiness of constrained optimal design. Several nonlinear models were tested.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.3
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• pp.25-30
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• 2005

Nonlinear optimal control problems lead to Hamilton-Tacobi equations which are not analytically solvable for most practical problems. This difficulty has led to the development of suboptimal nonlinear design techniques such as controller design based on feedback linearization(FL). In this paper, we present some simple examples where the optimal answer can be found for the optimal controller, FL controller and linear controller and determine its relative performance. As a result, we get the condition of a nonlinear system for the FL controller to an optimal design.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.4
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• pp.1-8
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• 1998

In order to solve the conflict problem between the ride comfort and the road holding, the optimal design of shock absorber that minimizes the r.m.s. of sprung mass vertical acceleration and pitch rate with the understeer characteristics constraints in the high speed stability is proposed. The design of experiments and the nonlinear optimization algorithm are used together to obtain the optimal design of shock absorber. The second order regression models of the input variables(front and rear damping coefficients) and the output variables (ride comfort index and road holding one) are obtained by the central composite design in the design of experiments. Then the optimal design of shock absorber can be systematically adjusted with applying the nonlinear optimization algorithm to the obtained second order regression model. The frequency response analysis of sprung mass acceleration and pitch rate shows the effectiveness of the proposed optimal design of shock absorber in the sprung mass resonance range with the understeer characteristics constraints.

• Structural Engineering and Mechanics
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• v.17 no.5
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• pp.707-725
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• 2004

An optimal design method with nonlinear elastic analysis is presented. The proposed nonlinear elastic method overcomes the drawback of the conventional LRFD method that accounts for nonlinear effect by using the moment amplification factors of $B_1$ and $B_2$. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are employed to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are strength, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.