• 전기학회논문지
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• 제60권1호
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• pp.32-35
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• 2011

The economic value of a wind farm project is influenced by various risk factors such as wind power output and electricity market price. In particular, there is uncertainty in the economic evaluation of a wind farm project due to uncertain wind power outputs, which are fluctuated by weather factors such as wind speed, and volatile electricity market prices. This paper presents a systematic method to assess the economic value and payback period of a wind farm project using Least Square Monte-Carlo (LSMC) simulation. Numerical example is presented to validate the effectiveness of the proposed economic assessment method for a wind farm project.

• 대한전기학회논문지
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• 제35권9호
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• pp.380-387
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• 1986

We have developed a dual control algorithm by means of innovations approach and established the stability of dual by introducing the pole-placement method suggested by Berger on the non-dual control. The dual controller realizing this algorithm decreases control loss sharply when compared with that of a non-dual controller, and shows the characteristics of suppressing the output deviation in transient state effectively. The total control energy and the accumulated square misdistance of this dual controller are shown to be 1-10% and 0.1-10% of those of CE control, respectively. Consequently this controller solves the non-minimum phase problem encountered when discretizing the system equation, and can be used to overcome the uncertainty of system effectively by adjusting the learning rate of the controller.

• Smart Structures and Systems
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• 제15권3호
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• Advances in robotics research
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• 제2권1호
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• pp.99-112
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• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.445-450
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• 1998

In this paper, a robust nonlinear prediction-type controller (RNPC) is developed for the continuous time nonlinear system whose control objective is composed of system output and its desired value. The basic control law of RNPC is derived such that the future response of the system is first predicted by appropriate functional expansions and the control law minimizing the difference between the predicted and desired responses is then calculated. RNPC which involves two controls, i.e., the auxiliary and robust controls into the basic control, shows the stable closed loop dynamics of nonlinear system of any relative degree and provides the robustness to the nonlinear system with parameter/modeling uncertainty. Simulation tests for the position control of a two-link rigid body manipulator confirm the performance improvement and the robustness of RNPC.

• 대한전기학회논문지
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• 제40권2호
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• pp.207-216
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• 1991

In the case that the robot manipulator should respond to the variance and uncertainty of the environment in performing preforming precision tasks, it is indispensable that the robot utilizes the various sensors for intrlligence. In this paper, the robot force control method is implemented with a force/torque sensor, two personal computers, and a PUMA 560 manipulator for performing the various application tadks. The hybrid position/force control method is used to control the force and position axis separately. An interface board is designed to read the force/torque sensor output into the computer. Since the two computers should exchange the information quickly, a common memory board is designed. Before the algorithms of application tasks are developed, the basic force commands must be supplied. Thus, the MOVE-UNTIL command is used at the discrete time instant and, the MOVE-COMPLY is used at the continuous time instant for receiving the force feedback information. Using the two basic force commands, three application algorithms are developed and implemented for edge-following, insertion, and grinding tasks.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권9호
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• pp.520-525
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• 2000

This paper deals with the design of H$\infty$ control for uncertain linear systems with the regional eigenvalue assignment constraint. The considered region is a disk in the left half plane and the two types of time-varying uncertainties are considered. We presents a state feedback control that minimize the L2 gain from the disturbance to the measured output as well as it guarantees that all eigenvalues of closed loop are inside a disk. The state feedback control is obtained by checking the feasibility of linear matrix inequalities (LMI's) which are numerically tractable. Finally we give an example to show the applicability and usefulness of our results.

• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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• pp.987-995
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• 1999

A new robust controller design methodology for single-input single-output systems is proposed, where the proposed controller consists of a conventional or optimal servo controller at the outer loop as well as the robust internal-loop compensator(RIC) to eliminate the model uncertainty and external disturbance. It is shown that RIC with finite gain can make actual systems be nominal models within a prespecified error bound. And, it is also shown that RIC-based system is robustly stable regardless of input saturation. Several numerical examples are illustrated to show validities of the proposed robust controller.

• Advances in aircraft and spacecraft science
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• 제6권5호
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• pp.371-389
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• 2019

The implementation of a robust $H_{\infty}$ Control, which is numerically efficient for uncertain nonlinear dynamics, on longitudinal and lateral autopilots is realised for a quarter scale Piper J3-Cub model accepted as an unmanned aerial vehicle (UAV) under the condition of sensor noise and disturbance effects. The stability and control coefficients of the UAV are evaluated through XFLR5 software, which utilises a vortex lattice method at a predefined flight condition. After that, the longitudinal trim point is computed, and the linearization process is performed at this trim point. The "${\mu}$-Synthesis"-based robust $H_{\infty}$ control algorithm for roll, pitch and yaw displacement autopilots are developed for both longitudinal and lateral linearised nonlinear dynamics. Controller performances, closed-loop frequency responses, nominal and perturbed system responses are obtained under the conditions of disturbance and sensor noise. The simulation results indicate that the proposed control scheme achieves robust performance and guarantees stability under exogenous disturbance and measurement noise effects and model uncertainty.

• 제어로봇시스템학회논문지
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• 제7권11호
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• pp.896-903
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• 2001

This study investigates the use of mixed $H_2/H_{$\infty}$ and $\mu$-synthesis to construct a robust controller for the benchmark problem. The model treated in the problem is a coupled three-inertial system that reflects the dynamics of mechanical vibrations. This kind of problem requires to be satisfied the robust performance (both in the time and frequency-domain specifications). We, first, adopt the mixed $H_2/H_{$\infty}$ theory to design a feedback controller K(s). Next, $\mu$-synthesis method is applied to the overall system to make use of structured parametric uncertainty. This process permits higher levels of controller authority and reduces the conservativeness of the controller. Finally, the feedforward controller is also used to improve the transient response of the output. We confirm that all design specifications except a complementary sensitivity condition can be achieved.