• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
• /
• pp.579-584
• /
• 1998

In this work, we present a method to deal with the interval valued decision making systems. First, we propose a new type of equality measure based on the Ordered Weighted Averaging (OWA) operator. The proposed equality measure has a structure to render the extreme values of the measure by choosing a suitable weighting vector of the OWA operator. From this property, we derive a bidirectional fuzzy inference network which can be applied for the decisionmaking systems requiring the inverval valued decisions.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
• /
• pp.146-151
• /
• 1994

An empirical comparison of static fuzzy relational models which are identified with different fuzzy implication operators and inferred by different composition operators is made in case that all the information is represented by the fuzzy discretization. Four performance measures (integral of mean squared error, maximal error, fuzzy equality index and mean lack of sharpness) are adopted to evaluate and compare the quality of the fuzzy relational models both at the numerical level and logical level. As the results, the fuzzy implication operators useful in various fuzzy modeling problems are discussed and it is empirically shown that the selection of data pairs is another important factor for identifying the fuzzy model with high quality.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
• /
• pp.1226-1229
• /
• 1993

This paper proposes a new on-line fuzzy model identification(ONFID) algorithm in which the fuzzy model evaluation stage is incorporated. The fuzzy model evaluation is performed by the fuzzy equality index which is known to be a useful tool to evaluate the performance of the identified fuzzy model. Then the fuzzy model is updated according to the result of the evaluation. Proposed ONFID algorithm can sensibly identify to the system changes. To show the usefulness of the proposed algorithm, it is applied to the fuzzy model identification problem of the gas furnace and the output prediction problem of the flexible joint manipulator which is a nonlinear system.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
• /
• pp.697-699
• /
• 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.

• 한국지능시스템학회논문지
• /
• 제20권3호
• /
• pp.356-361
• /
• 2010

M. Demirci[Vague groups, J. math. Anal. Appl. vol.230, pp. 142-156, 1999] studied the vague group operation on a crisp set as a fuzzy function and estabished the vague group structure on a crisp set. In this paper we consider bi-groups which are studied by A.A.A. Agboola and L.S. Akinola. And we also will define vague bi-groups and fuzzy bi-functions and we investigate some basic operations on the vague bi-group and fuzzy bi-functions.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
• /
• pp.818-821
• /
• 1993

In the last years fuzzy control has grown up to an important methodology of control engineering. In spite of the successful realizations of the underlying concepts in industrial products there has only been little effort regarding a semantical foundation of the prevailing heuristics that are used in fuzzy control. For this reason we want to outline promising approaches to an interpretation and better mathematical justification of fuzzy control, where the fundamental ideas of using equality relations to specify fuzzy environments for crisp data are presented. It turns out that Mamdani's classical max-min-inference is a consequence of our model.

• 한국수학교육학회지시리즈B:순수및응용수학
• /
• 제22권3호
• /
• pp.285-298
• /
• 2015

In [41], Th.M. Rassias proved that the norm defined over a real vector space V is induced by an inner product if and only if for a fixed positive integer l holds for all x₁, ⋯ , x_2l ∈ V . For the above equality, we can define the following functional equation Using the fixed point method, we prove the Hyers-Ulam stability of the functional equation (0.1) in fuzzy Banach spaces.

• International Journal of Control, Automation, and Systems
• /
• 제2권1호
• /
• pp.15-22
• /
• 2004

Some recent advances in stability and optimality for the nonlinear receding horizon control (NRHC) or the nonlinear model predictive control (NMPC) are assessed. The NRHCs with terminal conditions are surveyed in terms of a terminal state equality constraint, a terminal cost, and a terminal constraint set. Other NRHCs without terminal conditions are surveyed in terms of a control Lyapunov function (CLF) and cost monotonicity. Additional approaches such as output feedback, fuzzy, and neural network are introduced. This paper excludes the results for linear receding horizon controls and concentrates only on the analytical results of NRHCs, not including applications of NRHCs. Stability and optimality are focused on rather than robustness.

• 한국군사과학기술학회지
• /
• 제13권6호
• /
• pp.951-957
• /
• 2010

An optimal path generation method considering the safety of UGV(Unmanned Ground Vehicle) is proposed and demonstrated through examples. Among various functions of UGV, real-time obstacle avoidance is a key issue to realize realistic scenario in FCS(Future Combat Systems). A two-dimensional narrow corridor environment is considered as a test field. For each step of UGV movement, two objectives are considered: One is to minimize the distance to the target and the other to maximize the distance to the nearest point of an obstacle. A weighted objective function is used in the optimization problem. Equality and inequality constraints are taken to secure the UGV's dynamics and safety. The weighting factors are controlled by a fuzzy controller which is constructed by a fuzzy rule set and membership functions. Simulations are performed for two cases. First the weighting factors are considered as constant values to understand the characteristics of the corresponding solutions and then as variables that are adjusted by the fuzzy controller. The results are satisfactory for realistic situations considered. The proposed optimal path generation with the fuzzy control is expected to be well applicable to real environment.

• Smart Structures and Systems
• /
• 제29권4호
• /
• pp.617-624
• /
• 2022

A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.