• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1871-1880
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• 2011

In this paper, a controller for two wheeled inverted pendulum robot, i.e., Segway type robot that is a convenient and easily handled vehicle is designed to have more stable balancing and faster velocity control compared to the conventional method. First, a widely used PID control structure is applied to the two wheeled inverted pendulum robot and proper PID control gains for some specified weights of users are obtained to get accurate balancing and velocity control by use of experimental trial-and-error method. Next, neural network is employed to generate appropriate PID control gains for arbitrarily selected weight. Here the PID gains based on the trial-and-error method are used as training data. Simulation study has been carried out to find that the performance of the designed controller using the neural network is more excellent than the conventional PID controller in terms of faster balancing and velocity control.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.290-294
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• 2014

PID(Proportional, Integral, Derivative) controller is the most popular process controllers in nuclear power plants. The optimized parameter setting of the process controller contributes to the stable operation and the efficiency of the operating nuclear power plants. PID parameter setting is tuned when new process control systems are installed or current process control systems are changed. When the nuclear plant is shut down, a lot of PID tuning methods such as the Trial and Error method, Ultimate Oscillation method operation, Ziegler-Nichols method, frequency method are used to tune the PID values. But inadequate PID parameter setting can be the cause of the unstable process of the operating nuclear power plant. Therefore the results of PID parameter setting should be simulated, optimized and finally verified. This paper introduces the simulation method of PID tuning to optimize the PID parameter setting and confirms them of the actual PID controller in the operating nuclear power plants. The simulation method provides the accurate process modeling and optimized PID parameter setting of the multi-loop control process in particular.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.310-313
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• 2002

In industrial actual control system, PID controller has been used with its high delicate control system in position control system. PID controller has simple structure and superior ability in several characteristics. When the response of system is changed by delay time, variable load , disturbances and external environment, control gain of PID controller must be readjusted on the system dynamic characteristics. Therefore, a control ability of PID controller is degraded when the control gain is inappropriately determined. When the response characteristic of system is changed under a condition, control gain of PID controller must be changed adaptively to be a waited response of system. In this paper an PIDA controller is constructed by Two-Layers Neural Network applying back-propagation(BP) algorithm. Form the result of compute. simulation in the proposed controller, its usefulness is verified.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.48-55
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• 2008

In this paper, we propose a hybrid fuzzy controller for high performance. Hybrid fuzzy controller are combined Fuzzy and PID controller. In tuning the controller, the parameters of PID and the factors fuzzy controllers were obtained from the model identification and by using genetic algorithms, respectively. Simulation examples demonstrated a better performance of the proposed controller than conventional ones.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.69-77
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• 1999

This paper describes the design of fuzzy digital PID controller using simplified indirect inference method. First, the fuzzy digital PID controller is derived from the conventional continuous time linear digital PID controller. Then the fuzzification, control-rule base, and defuzzification using SIM in the design of the fuzzy digital controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional digital PID controller, which has the same linear structure, but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIM is applied, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control performance of the one proposed by D. Misir et al.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.138-142
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• 2004

This paper proposes the design of the model following control system using the PID control structure. PID control system became model following control by inserting new pre-compensator in order to improve control performance in discrete-time region. Gain of the PID controller needs to be readjusted when response of system changes due to disturbance or load fluctuation. Performance of control system improves by joining neural network to PID control system because performance of control system depends largely on each PID gain in PID control system. And the games of the PID controller in the proposed control system are automatically adjusted by back-propagation algorithm of the neural network. Angular position of DC servo motor is selected as a plant in order to verify control performance in model following control. After it is applied to the position control system, it's performance is verified through computer experiment.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.1
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• pp.55-64
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• 2002

Due to the friction characteristics of cylinders and the rail of a passenger car, in the system actuated with hydraulic systems, there exist dead zones, which can not be controlled by a PID controller. In this paper, the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-crossing speed region. To overcome the drawbacks of a PID controlled hydraulic system, a zooming fuzzy logic controller is designed and finally an improved hybrid controller is Proposed. The proposed controller is composed of the PID controller and the zooming fuzzy controller. The effectiveness of the proposed control scheme is shown by simulation and experimental results, In which the proposed hybrid control method yields good control performance not only in the zero-crossing speed region but also In the overall control region including steady-state region.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.190-195
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• 2016

In this paper, Propose to prevent compressor surge and improve the transient response of the fuel flow control system of turbojet engine. Turbojet engine controller is designed by applying Fuzzy-PID control algorithm. To prevent any surge or a flame out event during the engine acceleration or deceleration, the Fuzzy-PID controller effectively controls the fuel flow input of the control system. Fuzzy-PID results are used as the fuel flow control inputs to prevent compressor surge and flame-out for turbo-jet engine and the controller is designed to converge to the desired speed quickly and safely. Using LabVIEW to perform computer simulations verified the performance of the proposed controller. Response characteristics pursuant to the gain were analyzed by simulation.

• Journal of Drive and Control
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• v.9 no.4
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• pp.58-61
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• 2012

The customers who used the hydroulic system desire the product that has more detailed specification quickly during the industrial technology is developed. Every researcher try to reduce the developed period and to satisfy the customers' desire. Lot's of simulation software and hardware already was used to be satisfied those purpose. But these kind of equipment need a lot of cost to set up and technical knowledge to drive that system. This paper concerns about analog PID controller that can be assembled with a few resistor, condenser and optional amplifier and doesn't need technical knowledge to drive. At the first, the plant was modeled mathematically to design the analog PID controller's circuit. After that, PID controller's parameter was selected by customers' desire. Finally, the analog PID controller's circuit was assembled from the control law. The circuit's availability was confirmed by step response test in the controlled system.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.61-67
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• 2018

This paper presents a method to apply disturbance observer to PID controller for robustness enhancement of UAVs. The system uncertainties and disturbances bring adverse effects on performance and stability of UAVs. In this paper, we estimate the acceleration disturbances using nonlinear disturbance observer, then compensate disturbances with composite controller. By employing nonlinear disturbance observer and composite controller, we have better performance and robustness than conventional PID controller. The asymptotical stability of nonlinear disturbance observer is presented through theoretical analysis. The estimation performance of nonlinear disturbance observer is evaluated by numerical simulation. And performance of disturbance observer based PID controller is evaluated by comparing the performance with conventional PID controller.