• Journal of Power Electronics
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• v.4 no.4
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• pp.217-227
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• 2004

A robust controller that combines the merits of the feed-back, feed-forward and model-following control for induction motor drives utilizing field orientation control is designed in this paper. The proposed controller is a two-degrees-of­freedom (2DOF) integral plus proportional & rate feedback (I-PD) speed controller combined with a model-following (2DOF I-PD MFC) speed controller. A systematic mathematical procedure is derived to find the parameters of the 2DOF I-PD MFC speed controller according to certain specifications for the drive system. Initially, we start with the I-PD feed­back controller design, then we add the feed-forward controller. These two controllers combine to form the 2DOF I-PD speed controller. To realize high dynamic performance for disturbance rejection and set point tracking characterisitics, a MFC controller is designed and added to the 2DOF I-PD controller. This combination is called a 2DOF I-PD MFC speed controller. We then study the effect of the 2DOF I-PD MFC speed controller on the performance of the drive system under different operating conditions. A computer simulation is also run to demonstrate the effectiveness of the proposed controller. The results verify that the proposed 2DOF I-PD MFC controller is more accurate and more reliable in the presence of load disturbance and motor parameter variations than a 2DOF I-PD controller without a MFC. Also, the proposed controller grants rapid and accurate responses to the reference model, regardless of whether a load disturbance is imposed or the induction machine parameters vary.

• Journal of Power Electronics
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• v.9 no.1
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• pp.74-84
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• 2009

The design and implementation of a high performance PID (Proportional Integral & Differential) style controller with zero-phase error tracking property is considered in this article. Unlike a ball screw driven system, the controller in a direct drive system should provide a high level of tracking performance while avoiding the problems due to the absence of the gear system. The stiff mechanical element in a direct drive system allows high precise positioning capability, but relatively high tracking ability with minimal position error is required. In this work, a feasible position controller named 'Unified PID controller' is presented. It will be shown that the function of the closed position loop can be designed into unity gain system in continuous time domain to provide minimal position error. The focus of this work is in two areas. First, easy gain tunable PID position controller without speed control loop is designed in order to construct feasible high performance drive system. Second, a simple but powerful zero phase error tracking strategy using the pre-designed function of the main control loop is presented for minimal tracking error in all operating conditions. Experimental results with a s-curve based position pattern commonly used in industrial field demonstrate the feasibility and effective performance of the approach.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.126-133
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• 2000

This paper is a study on robust PID controller tuning technique using the frequency region model matching method.To design the robust PID controller satisfying disturbance attenuation and robust tracking property for a reference input first an {{{{ETA _$\infty$}}}} controller satisfying given performances is designed using an H$_{\infty}$ control method, And then the parameters(proportional gain integral gain and derivation gain) of the robust PID controller with the performances of the desinged H$_{\infty}$ controller are determined using the model matching method at frequency domain. in this paper this PID controller tuning technique is applied to PID speed controller design for BLDC motors. Consequently simulation results show that the proposed PID speed controller satisfies load torque disturbance attenuation and robust tracking property and this study has usefulness and applicability for the speed control system; design of BLDC motors.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.472-477
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• 2023

In this paper, we proposes the use of Model Predictive Control (MPC) techniques to enable quadcopter drones to effectively follow paths and maintain flight safety even under dynamic external environments and disturbances. Through simulations conducted in MATLAB/Simulink, the performance of two controllers, PID and MPC, is compared in flight scenarios with disturbances. The proposed design method shows that the MPC controller, when compared to the PID controller, exhibits a difference in the Mean Squared Error between the intended flight path and the actual path of the quadcopter drone. This difference is 0.2 in performance under no disturbance, and it increases to 0.8 under disturbance, demonstrating the improved path following accuracy of the MPC controller.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.1-8
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• 2008

A two-wheel balancing vehicle, which helps people moving freely and fast, and is applied from inverted pendulum system, has been widely researched and developed, and some products are came into a market in actuality. Until now, the two-wheel balancing vehicles developed have chosen the general PID control method. In this paper, we propose a new control method to improve a control capacity for a two-wheeled balancing vehicle for human transportation. The proposed method is the fuzzy PD+I control that is one of the improved PID control, and it contains a 2input-1output fuzzy system. This fuzzy system processes signals from proportional and derivative controller, and the fuzzy output signal generates the final output by summing up integral signal. The non-linearity of the fuzzy system makes an optimal output control signal by changing weight of the proportional signal and the derivative signal in process of time. We have simulated the fuzzy PD+I control system and experimented by implementing the two-wheel balancing mobile robot to verify the advantages of the proposed fuzzy PD+I control method in comparison with general PID control. As the results of simulation and experimentation, the proposed fuzzy PD+I control method has better control performance than general PID in this system and improves it.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.574-580
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• 2014

Storage tanks of Carbon dioxide ($CO_2$) carriers utilized for the purpose of carbon capture and storage (CCS) into subsea strata have to undergo a pre-cooling session before beginning to load cryogenic liquid cargos in order to prevent physical and thermal deterioration of tanks which may result from cryogenic $CO_2$ contacting tank walls directly. In this study we propose dynamic model to calculate the tank inflow of $CO_2$ gas injected for precooling process and its dynamic simulation results under proportional-integral control algorithm. We selected two cases in which each of them had one controlled variable (CV) as either the tank pressure or the tank temperature and discussed the results of that decision-making on the pre-cooling process. As a result we demonstrated that the controlling instability arising from nonlinearity and singularity of the mathematical model could be avoided by choosing tank pressure as CV instead of tank temperature.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.12
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• pp.782-790
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• 2011

Typical temperature control methods of a cooler for machine tools are hot-gas bypass and compressor variable speed control. The hot-gas bypass system has been widely used to control the cooler temperature in many general industrial fields. On the contrary, the compressor variable speed control is focused on special fields such as aerospace and high precision machine tools which need high precision control. The variable speed control system usually has two control variables such as target temperature and superheat. In other words, the variable speed control system is basically multi-input multi-output(MIMO) system. In spite of MIMO system, the proportional integral derivative(PID) feedback control methodology that based on single-input single-output (SISO) system is generally used for designing the variable speed control system. Therefore, it is inevitable to describe transfer functions for dynamic behaviors of every controlled variables and decide the PID gains with tremendous iteration process. Moreover, the designed PID gains do not provide optimum system performances. To solve these problems, high performance controller design method based on a state space model is suggested in this paper. An optimum controller is designed to minimize both control errors and energy inputs. This method was more simple to describe dynamic behaviors and easier to design the cooler controller which is MIMO system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.900-907
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• 2014

This paper proposes a MPC (Model Predictive Control) method for the torque and flux controls of induction motor. The proposed MPC method selects the optimized voltage vector for the matrix converter control using the predictive modeling equation of the induction motor and cost function. Hence, the reference voltage vector that minimizes the cost function of the torque and flux error within the control period is selected and applied to the actual system. As a result, it is possible to perform the torque and flux control of induction motor using only the MPC controller without a PI (Proportional-Integral) or hysteresis controller. Even though the proposed control algorithm is more complicated and has lots of computations compared with the conventional MPC, it can perform torque ripple reduction by synthesizing voltage vectors of various magnitude. This feature provides the reduction of amount of calculations and the improvement of the control performance through the adjustment of the number of the unit vectors n. The proposed control method is validated through the PSIM simulation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.318-324
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• 2014

Recent years have witnessed a growing demand for a wide variety of high-performance industrial robots. In this paper, for accurate gain tuning of a 6-axis articulated industrial robot with reduced noise, a program routine for a dynamic signal analyzer (DSA) using the frequency response method will be programmed using $LabVIEW^{(R)}$. Then, robot transfer functions can be obtained experimentally using the frequency response method with the DSA program. Data from the robot transfer functions are transformed into Bode plots, based on which an optimal gain tuning will be executed. Gain tuning can enhance the response quality of the output signal for a given input signal during real-time control of the robot. The effectiveness of our proposed technique will be verified by implementation with a (lab-manufactured) 6-axis articulated industrial robot (hereinafter called "RS2") and comparison with the zero position gain tuning, as well as other positions.