• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1008-1013
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Velocity is controlled by using an optimal state controller LQR. A position control loop is added to form a PD controller. To minimize a position tracking error, neural network is introduced. The reference compensation technique as a neural network control structure is used, and a position tracking error of an autonomous helicopter is compensated by neural network installed in the remotely located ground station. Considering time delays between an autonomous helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network compensation performs better than that of the LQR itself.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.5
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• pp.37-42
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• 2004

This paper presents an optimal and robust tuning method of decentralized PI controller for the TITO second order systems to be formulated as LQR. The procedure is developed by establishing relationships between the closed-loop state equation including the decentralized PI tuning parameter and the . closed-loop state equation of LQR and by selecting the weighting factors Q and R of the cost function in order to satisfy the design specifications In frequency domain which the stability robustness and satisfied the performance guaranteed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.17-24
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• 2004

This paper proposes an optimal robust LQ-PID controller design method for the second order systems to satisfy the design specifications in time domain. The tuning parameters of LQ-PID controller are determinated by the relationships between the design parameters of the overshoot and the settling time which are design specifications in time domain, and the weighting factors Q and R in LQR. we can achieve the performance-robustness in time domain as well as the stability-robustness.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.1-8
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• 2004

This paper presents an optimal robust LQ-PID controller design method for the second order system with time-delay to meet design specifications. By LQR formulation of the second order system with time-delay, the tuning parameters of PID controller are related by weighting factors Q and R of cost function. The selection of weighting factors Q and R are chosen to satisfy such the design specifications as overshoot and settling time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1252-1257
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• 2004

This paper presents a decentralized LQ-PID controller for the TITO system which satisfies the performance of good command following, disturbance rejection, and sensor noise reduction that is design specifications in the frequency domain The procedure is developed by establishing the relationship between the closed-loop state equations including the decentralized PID tuning parameters and the closed-loop state equations of LQR and by selecting the weighting factors Q and R of the cost function in order to satisfy the design specifications in the frequency domain.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.2
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• pp.118-128
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• 2012

The goal of this paper is to design the target tracking controller for a quadrotor micro UAV using a vision sensor. First of all, the mathematical model of the quadrotor was estimated through the Prediction Error Method(PEM) using experimental input/output flight data, and then the estimated model was validated via the comparison with new experimental flight data. Next, the target tracking controller was designed using LQR(Linear Quadratic Regulator) method based on the estimated model. The relative distance between an object and the quadrotor was obtained by a vision sensor, and the altitude was obtained by a ultra sonic sensor. Finally, the performance of the designed target tracking controller was evaluated through flight tests.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.236-242
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• 2008

In this paper, we propose an optimized fuzzy controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for rotary inverted pendulum system. We adopt fuzzy controller to control the rotary inverted pendulum and the fuzzy rules of the fuzzy controller are designed based on the design methodology of Linear Quadratic Regulator (LQR) controller. Simple Genetic Algorithms (SGAs) is well known as optimization algorithms supporting search of a global character. There is a long list of successful usages of GAs reported in different application domains. It should be stressed, however, that GAs could still get trapped in a sub-optimal regions of the search space due to premature convergence. Accordingly the parallel genetic algorithm was developed to eliminate an effect of premature convergence. In particular, as one of diverse types of the PGA, HFCGA has emerged as an effective optimization mechanism for dealing with very large search space. We use HFCGA to optimize the parameter of the fuzzy controller. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy controller leads to superb performance in comparison with the conventional LQR controller as well as SGAs based fuzzy controller.

• Journal of the Korean Society of Propulsion Engineers
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• v.1 no.1
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• pp.24-32
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• 1997

A nonlinear dynamic simulation of a small gas turbine engine was performed by using DYNGEN program with various environmental conditions. It was observed that the effect of the bleed air flow rate changed to overall engine performance. The real time linear model which was a function of engine rotor speed was resulted to be close to nonlinear simulation results. For optimal LQR controller, it was considered only fuel flow rate or both fuel flow rate and bleed air rate as inputs. In the comparison of both results, the LQR controller with multi input had better performance than that with single input.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 1997.04a
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• pp.55-60
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• 1997

A nonlinear dynamic simulation was performed by using DYNGEN program with various environmental conditions. It was observed that the effect of the bleed air flow rate changed to overall engine performance. The real time linear model which was a function of rpm was resulted to be close to nonlinear simulation results. For optimal LQR controller, it was considered only fuel flow rate or both fuel flow rate and bleed air rate as inputs. In the comparison of both results, the LQR controller with multi input had better performance than that with single input.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.112-119
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• 2003

Generally, PID controller is not suitable to control multi variable system because it is very difficult to tune the PID gains. However, this paper shows that it is not hard to tune the PID gains if we can find a Jacobian matrix of the system. The Jacobian matrix expresses the ratio of output variations according to input variations. It is possible to adjust the input values in order to reduce the output error using the Jacobian. When the colt function is composed of error related terms, the gradient approach can tune the PID gains to minimize the function. In simulation, a hydrofoil catamaran with two inputs and two outputs is applied as a multi variable system. We can easily get the multi variable PID controller by the proposed teaming method. When the controller is compared with LQR controller, the performance is as good as that of LQR controller with a modeling equation.