• Journal of Mechanical Science and Technology
• /
• v.18 no.3
• /
• pp.337-346
• /
• 2004

The control scheme using fuzzy modeling and Parallel Distributed Compensation (PDC) concept is proposed to provide asymptotic tracking of a reference signal for the flexible joint manipulators with uncertain parameters. From Lyapunov stability analysis and simulation results, the developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop multi-input/multi-output system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.9
• /
• pp.1368-1375
• /
• 1993

This paper deals with the decentralized robust adaptive controller design for large-scale interconnected systems. We consider an arbitrary interconnection of subsystems with unkown parameters and bounded disturbances. When the disturbance and uncertain interconnections are present, the stability of the controlled large scale system is ensured if there exists a positive definite M-matrix which is related to the bound of the interconnections. The possible bound of the interconnections is assumed to be known Pth order polynomials for the decentralized adaptive controller. A modified adaptive law is proposed guaranteeing the existence of a region of attraction from which all signals converge to a residual set Do, which contains the equilibrium.

• Transactions of The Korea Fluid Power Systems Society
• /
• v.4 no.2
• /
• pp.1-6
• /
• 2007

During the last few decades, excavation automation has been investigated to protect the operator from the hazardous working environment and to relieve the cost of the skilled operator. Therefore, a number of modelling and controller design methods of the hydraulic excavator are proposed in many literatures to realize the excavation automation. In this article, a geometric approach far the multi-body system modeling is adopted to develop the excavator mechanism model that contains 4 kinematic loops and 12 links. Considering a simple soil mechanism model with a number of uncertain soil parameters, an adaptive trajectory tracking control strategy based on the developed excavator model is proposed. The improved performance of the designed controller over the simple PID controller is validated via the simulation study.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.396-400
• /
• 1996

It is prerequisite to apply dynamics controller to control robot manipulator required to perform fast and Precise motion. In this Paper, we Propose an adaptive 3earning control method for the dynamic control of a robot manipulator. The proposed control scheme is made up of PD controller in the feedback loop and the adaptive learning controller in the feedforward loop. This control scheme has the ability to estimate uncertain dynamic parameters included intrinsically in the system and to achieve the desired performance without the nasty matrix operation. The proposed method is applied to a SCARA robot and experimentally verified.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.391-395
• /
• 1996

This paper presents a robust force tracking control of a small-sized SMA gripper with two fingers using shape memory alloy(SMA) actuators. The mathematical governing equation of the proposed system is derived by Hamilton's principle and Lagrangian equation and then, the control system model is integrated with the first-order actuator dynamics. Uncertain system parameters such as time constant of the actuators are also included in the control model. A robust two degree of freedom(TDF) controller using H$_{\infty}$ control theory, which has inherent robustness to model uncertainties and external disturbances, is adopted to achieve end-point force tracking control of the two-finger gripper. Force tracking control performances for desired trajectories represented by sinusoidal and step functions are evaluated by undertaking both simulation and experimental works.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.10
• /
• pp.135-140
• /
• 1997

The detection of cutting tool states in machining is important for the automation. The information of cutting tool states in metal cutting process is uncertain. Hence a industry needs the system which can detect the cutting tool states in real time and control the feed motion. Cutting signal features must be sifted before the classification. In this paper the Fisher's linear discriminant function was applied to the pattern recognition of the cutting tool states successfully. Cutting conditions and cutting force para- meters have shown to be sensitive to tool states, so these cutting conditions and cutting force paramenters can be used as features for tool state detection.

• Journal of Electrical Engineering and information Science
• /
• v.2 no.4
• /
• pp.59-65
• /
• 1997

In this paper, a general fuzzy syntactic method for recognition of flaw patterns and for the measurement of flaw characteristic parameters for a non-destructive inspections signal, called eddy-current, is presented. Solutions are given to the subtasks of primitive pattern selection, signal to symbol transformation, pattern grammar formulation, and event-synchronous flaw pattern extraction based on the grammars. Fuzzy attribute grammars are used as the model for the pattern grammar because of their descriptive power in the face of uncertain constraints caused by nose or distortion in the signal waveform, due to their ability to handle syntactic as well as semantic information. This approach has been implemented and the performance of eh resultant system has been evaluated using a library of law patterns obtained from steam generator tubes in nuclear power plants by an eddy current-based non-destructive inspection method.

• Management Science and Financial Engineering
• /
• v.18 no.2
• /
• pp.23-27
• /
• 2012

The problem of jointly determining a robust optimal bundle of price and order quantity for a retailer in a single-retailer, single supplier, single-product supply chain is considered. Demand is modeled as a decreasing power function of product price, and unit purchasing cost is modeled as a decreasing power function of order quantity and demand. Parameters defining the two power functions are uncertain but their possible values are characterized by ellipsoids. We extend a previous study in two ways; the purchasing cost function is generalized to take into account the economies of scale realized by higher product demand in addition to larger order quantity, and an exact transformation into an equivalent convex optimization program is developed instead of a geometric programming approximation scheme proposed in the previous study.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2008.10a
• /
• pp.85-110
• /
• 2008

Ground investigation data to be used as a basis for geotechnical analysis and foundation design are usually troubled with large uncertainty, due to natural variability and limited number of data. Statistical methods can be a rational tool for handling such uncertain ground data, in particular with a view to the selection of characteristic values for estimating ground design parameters used in design. The characteristic values of soil properties for use in geotechnical design have oftenly based on not only a subjective judgment but also engineer's past acumulated experience. This paper discussed some statistical methods which can handle such intrinsic ground uncertainty data with a case design in a rational manner.

• Industrial Engineering and Management Systems
• /
• v.15 no.4
• /
• pp.354-363
• /
• 2016

Due to uncertain environment, various parameters such as price, queuing length, warranty, and so on influence on inventory models. In this paper, an inventory-queuing-pricing problem with continuous review inventory control policy and batch arrival queuing approach, is presented. To best of our knowledge, (I) demand function is stochastic and price dependent; (II) due to the uncertainty in real-world situations, a fuzzy programming approach is applied. Therefore, the presented model with goal of maximizing total profit of system analyzes the price and order quantity decision variables. Since the proposed model belongs to NP-hard problems, Pareto-based approaches based on non-dominated ranking and sorting genetic algorithm are proposed and justified to solve the model. Several numerical illustrations are generated to demonstrate the model validity and algorithms performance. The results showed the applicability and robustness of the proposed soft-computing-based approaches to analyze the problem.