• 전기학회논문지
• /
• 제68권1호
• /
• pp.159-166
• /
• 2019

Due to the various engagement situations, it is very difficult to generate the optimal trajectory with several constraints. This paper investigates the sequential convex programming for the impact angle control with the additional constraint of altitude limit. Recently, the SOCP(Second-Order Cone Programming), which is one area of the convex optimization, is widely used to solve variable optimal problems because it is robust to initial values, and resolves problems quickly and reliably. The trajectory optimization problem is reconstructed as convex optimization problem using appropriate linearization and discretization. Finally, simulation results are compared with analytic result and nonlinear optimization result for verification.

• 제어로봇시스템학회논문지
• /
• 제5권1호
• /
• pp.11-15
• /
• 1999

In this paper, a robust pole placement controller for time invariant linear systems with polytopic uncertainties is presented. The proposed controller is a fixed order output feedback controller which stabilizes the uncertain systems and satisfies the constraints on the closed-loop pole location. The proposed controller can be obtained by minimizing a certain nonlinear object function subject to linear matrix inequality constraints. An algorithm for solving the nonlinear optimization problem is also proposed.

• Industrial Engineering and Management Systems
• /
• 제6권2호
• /
• pp.119-124
• /
• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 2023년도 춘계학술대회
• /
• pp.254-255
• /
• 2023

This paper discovers a robust managerial strategy for a stochastic inventory of perishable products, where the model experiences changing factors including inner parameters and an external disturbance with unknown form. An analytical solution for the optimization problem can be obtained by applying the Hamilton-Bellman-Jacobi equation, however the policy result cannot completely suppress the oscillation from the external disturbance. Therefore, an intelligent approach named Radial Basis Function Neural Networks is applied to estimate the unknown disturbance and provide a robust controller to manipulate the inventory level more effective. The final results show the outstanding performance of RBFNN controller, where both the estimation error and control error are guaranteed in the predefined limit.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.109-112
• /
• 1997

In this note, we investigate a noniterative design method of an observer-based robust H$\_$2/ controller in the presence of structured real parameter uncertainty by applying Riccati approach based on the guaranteed cost function. Motivated by the numerical difficulty of the problem, we try to develop a simple design method named as block-diagonal approach, which can be solved by the LMIs method. By assuming the block-diagonal structure of Riccati solution, the original problem can be derived into two sequentially decoupled optimization problems as LQG control problem. The proposed method seems to be numerically efficient in obtaining a feasible compensator.

• 제어로봇시스템학회논문지
• /
• 제15권3호
• /
• pp.255-257
• /
• 2009

The robust stabilization problem of a multivariable uncertain system with a polytopic model is considered. A PI-type $H_{\infty}$ controller with a low pass filter is used for robust stabilization and noise rejection. The problem is reduced to an LMI optimization problem. A sufficient condition for the existence of the PI controller is derived in terms of LMIs. The PI gain matrices are parameterized by using the solution matrices to the existence conditions. Finally, a numerical design example is given.

• ETRI Journal
• /
• 제36권3호
• /
• pp.506-509
• /
• 2014

This paper studies the energy efficiency power allocation for cognitive radio networks based on uplink orthogonal frequency-division multiplexing. The power allocation problem is intended to minimize the maximum energy efficiency measured by "Joule per bit" metric, under total power constraint and robust aggregate mutual interference power constraint. However, the above problem is non-convex. To make it solvable, an equivalent convex optimization problem is derived that can be solved by general fractional programming. Then, a robust energy efficiency power allocation scheme is presented. Simulation results corroborate the effectiveness of the proposed methods.

• International Journal of Computer Science & Network Security
• /
• 제22권8호
• /
• pp.45-54
• /
• 2022

In this study, a multi-objective robust job-shop scheduling (JSS) model was developed. The model considered multi-jobs and multi-machines. The model also considered uncertain processing times for all tasks. Each job was assigned a specific due date and a tardiness penalty to be paid if the job was not delivered on time. If any job was completed early, holding expenses would be assigned. In addition, the model added idling penalties to accommodate the idling of machines while waiting for jobs. The problem assigned was to determine the optimal start times for each task that would minimize the expected penalties. A numerical problem was solved to minimize both the makespan and the total penalties, and a comparison was made between the results. Analysis of the results produced a prescription for optimizing penalties that is important to be accounted for in conjunction with uncertainties in the job-shop scheduling problem (JSSP).

• 동력기계공학회지
• /
• 제4권3호
• /
• pp.72-80
• /
• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identification. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identification are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identity the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.560-564
• /
• 1996

A mixed H$^{2}$/$H^{\infty}$ controller design method for linear systems with time delay in all variables and parameter uncertainties in all system matrices is proposed. Robust $H^{\infty}$ performance and H$^{2}$ performance condition that accounts for model-matching of closed loop system and disturbance rejection is also derived. With expressing uncertain system with linear fractional transformation form, we transform the robust stability and performance problem to the H$^{2}$/$H^{\infty}$ optimization problem and design a mixed H$^{2}$/$H^{\infty}$ controller. Using the proposed method, mixed H$^{2}$/$H^{\infty}$ controller for underwater vehicle with time delay and parameter variations are designed. Simulations of a design example with hydrodynamic parameter variations and disturbance are presented to demonstrate the achievement of good robust performance.t performance.ance.