• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.6
• /
• pp.927-934
• /
• 2017

This paper is concerned with applicability of two-degree-of-freedom controllers to the recently suggested i-PID controllers, in which unknown parts of the plant are taken into account without any modeling procedure. First, i-PID controller with two-degree-of-freedom is applied to a specific model, called Anisochronic model, to confirm the usefulness of this method. Second, using the original examples of i-PID controllers, it is confirmed that performance/robustness of system are to be improved due to two-degree-of-freedom, especially when the input changes suddenly. It is seen that as the desired robustness increases the optimal value of two-degree-of-freedom parameter ${\alpha}_A$ would be negative. It is checked and verified that if this value was limited to 1 or less as is generally known, performance would be degraded.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2000.11a
• /
• pp.159-167
• /
• 2000

During the operation of crane system in the container yard, it is necessary to control the crane trolley position so that the swing of the hanging container is minimized. Recently an automatic control system with high speed and rapid transportation is required. Therefore, we designed a controller to control the crane system with disturbances and weight change. In this paper, we present the neural network two degree of freedom PID controller to control the swing motion and trolley position. Then we executed the computer simulation to verify the performance of the proposed controller and compared the performance of the neural network PID controller with our proposed controller in terms of the rope swing and the precision of position control. Computer simulation results show that the proposed controller has better performances than neural network PID with disturbances.

• Journal of the Institute of Convergence Signal Processing
• /
• v.8 no.2
• /
• pp.124-129
• /
• 2007

Recently, the application of the linear machine for industrial field is remarkably increased, especially for the gantry machine, machine tool system and CNC. However a linear meter remains the vibrational characteristic itself therefore, In these application fields, high position control performance is essentially required in both the steady and the transient states. In this paper, the design method for a position control is proposed by using the two-degree-of freedom PID controller. This method has great features for the linear machine drives such as no over-shoot phenomena and single gain tuning strategy. By comparison with conventional PID controller, the improvement of performance of a linear motor control system using two degrees of freedom controller are discussed. Through the simulation results, the usefulness of the proposed algorithm is proved. With the simulation results, it was made clear that the introduction of two degrees of freedom controller designed by the proposed method not only improves the over shoot and starting characteristic of response but also removes the undesirable characteristic variation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1327-1332
• /
• 2003

In this paper, an ATC(Automated Transfer Crane) control system is required rapid transportation to get highest productivity with low cost. Therefore, the container paths should be built in terms of the least time and least sway when container is transferred from the initial coordinate to the finial coordinate. So we applied the best-first search method for forming the container path, and calculated the anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the neural network two degree of freedom PID (TDOFPID) controller to control the precise navigation. For simulation, we constructed the container profiles so that we analyzed the state of formed path and the performance of TDOFPID controller to the formatted path. Then we compared the performance of ES-tuned PID controller with our proposed controller in terms of trolley position, anti-sway, path change, disturbance, and the load of containers. The computer simulation results show that the proposed controller has better the other on the various conditions.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.9
• /
• pp.1202-1209
• /
• 2018

This paper is concerned with the problem of setting controller's parameters when applying the intelligent PID (i-PID), which has recently been proposed and had many successful results, to the two-degree-of-freedom (2DoF) PID controller structure. Generally, the parameter settings of conventional PID controllers are known to be quite difficult and be dependent on the characteristics of the plants. In addition, it is less known how the two 2DoF parameters are set up for the improvement of transient characteristics. Here, we are going to present one of the criteria for parameter setting in the case of using a 2DoF i-PID, by evaluating the error signals to the set-point and disturbance. That is, we first, obtain parameters of i-PID by optimizing the disturbance responses, and then determine two parameters of 2DoF component through optimizing set-point response. The standard values of all parameters are calculated for the 7 types of test batches and rounded up as a table.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.142-142
• /
• 2000

During the operation of crane system in container yard, it is necessary to control the crane trolley position so that the swing of the hanging container is minimized. Recently an automatic control system with high speed and rapid transportation is required. Therefore, we designed a controller to control the crane system with disturbances. In this paper, Ive present the neural network two degree of freedom PID controller to control the swing motion and trolley position. Then we executed the computer simulation to verify the performance of the proposed controller and compared the performance of the neural network PID controller with our proposed controller in terms of the rope swing and the precision of position control . Computer simulation results show that the proposed controller has better performances than neural network PID with disturbances.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.12a
• /
• pp.193-196
• /
• 2000

ln this paper, we consider to apply of 2-DOF (Degree of Freedom) PID controller at D.C servo motor system. Many control system use I-PD, PIB control system. but the position control system have difficulty in controling variable load and changing parameter We propose neural network 2-DOF PID control system having feature for removal disturbrances and tracking function in the target value point.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.256-261
• /
• 2004

This paper presents a simple two-degree of freedom PID tuning table based on the CDM design method. The structure of the control system will be composed of plant, P or PI or PID controller and a pre-filter. The finalized formula can be used based on the experimental test of the plant in the same manner as the Ziegler-Nichols' second method. That is; users just need to find the critical gain and critical period experimentally and the parameters of the P, PI or PID controller with the pre-filter can be obtained by substituting the values of critical gain and critical period in the tuning table. The simulation results of the control systems utilizing the proposed controllers compared with those using the Ziegler-Nichols' second method will also be demonstrated.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.1907-1908
• /
• 2006

Recently, an automatic crane control system is required with high speed and rapid transportation. Therefore, when container is transferred from the initial coordinate to the finial coordinate, the container paths should be built in terms of the least time and without sway. Therefore, we calculated the anti-collision path for avoiding collision in its movement to the finial coordinate in this paper. And we constructed the neural network predictive two degree of freedom PID controller to control the precise navigation. The proposed predictive control system is composed of the neural network predictor, two degree of freedom PID controller, neural network self-tuner which yields parameters of two degree of freedom PID. We analyzed crane system through simulation, and proved excellency of control performance over the conventional controllers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.05a
• /
• pp.395-398
• /
• 2001

In this paper, we consider to apply of 2-DOF (Degree of Freedom) PID controller at D.C servo motor system. Many control system use I-PD, PID control system but the position control system have difficulty in controling variable load and changing parameter. We propose neural network 2-DOF PID control system haying feature for removal disturbances and tracking function in the target value point. Experiment result for 2-DOF PID controller with neural network are illustrated.