• The Journal of Korea Robotics Society
• /
• v.9 no.1
• /
• pp.67-77
• /
• 2014

An electric motor is the one of the most important parts in robot systems, which mainly drives the wheel of mobile robots or the joint of manipulators. According to the requirement of motor performance, the controller type and parameters vary. For the wheel driving motors, a speed tracking controller is used, while a position tracking controller is required for the joint driving motors. Moreover, if the mechanical parameters are changed or a different motor is used, we might have to tune again the controller parameters. However, for the beginners who are not familiar about the controller design, it is hard to design pertinently. In this paper, we develop a nominal robust controller model for the velocity tracking of wheel driving motors and the position tracking of joint driving motors based on the disturbance observer (DOB) which can reject disturbances, modeling errors, and dynamic parameter variations, and propose the methodology for the determining the least control parameters. The proposed control system enables the beginners to easily construct a controller for the newly designed robot system. The purpose of this paper is not to develop a new controller theory, but to increase the user-friendliness. Finally, simulation and experimental verification have performed through the actual wheel and joint driving motors.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.181-183
• /
• 1996

Generally, While position type fuzzy controller has good performance in transient period, it has uniform steady state error of response. While velocity type fuzzy controller is capable of reducing steady state error of response, it is hard to develop the performance in transient period. In order to have both good performance in transient period and ability to reduce the steady state error of response, weighting fuzzy controller, which is composed of these two fuzzy controllers, is proposed. For the decision of weight to each fuzzy controller, Weighting fuzzy set is established according to the system state variables and applied to each fuzzy controller. The proposed weighted fuzzy controller has the merits of both position type fuzzy controller and velocity type fuzzy controller simultaneously.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.321-325
• /
• 1988

The objective of this study is to develop a microcomputer-based adaptive controller for an electro hydraulic velocity control system subjected to the variation of system parameters. The step response performance of the system with the adaptive controller is investigated for the variation of the external load torque, the moment of inertia and the reference inputs, and compared with that obtained by PID controller whose gains are constant. The experimental results show that this proposed model reference adaptive controller is robust to the variation of system parameters and yield much better control performance compared with the conventionel PID controller.

• 한국신재생에너지학회:학술대회논문집
• /
• 2008.10a
• /
• pp.353-356
• /
• 2008

HEV(Hybrid Electrical Vehicle) is considered as one of the next generation vehicles. To develop the HEV, there must be a reliable simulator, by which the capacities of the power resources are tested, and the parameters of the HEV are optimized before developing the real model of the HEVs. This process can save the money for designing the HEV system and improve the system without experiments. Matlab Simulink is familiar to mechanical engineers and the program can simultaneously provide a system model and a controller in one program. Nowadays, the Simdriveline toolbox which is used for analysis a power-train system is applied to build a dynamic model for a HEV system. In this study, we make a HEV simulator with the Simdriveline toolbox and develop a controller. There are two simple strategies, applied to the controller. One strategy includes a power split ratio and a shift map which are created by user. Other strategy calculated an appropriate amount of resource's torque along specific results, and this is useful when users can't develop a fitting controller. The methodologies for configuring the simulator and its control system are presented in this paper.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.147.2-147
• /
• 2001

In this paper we develop a new robust trajectory tracking control scheme without using joint velocity. The proposed controller doesn´t employ adaptation, Therefore, the construction of the controller becomed very simple. Moreover, by using numerical simulation, we make sure the effectiveness of the proposed controller in the presence of quantization errors.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.17 no.1
• /
• pp.101-111
• /
• 1993

Many processes such as machining, injection-moulding and metal-forming are usually operated by hydraulic servo-systems. The dynamic characteristics of these systems are complex and highly non-linear and are often subjected to the uncertain external disturbances associated with the processes. Consequently, the conventional approach to the controller design for these systems may not guarantee accurate tracking control performance. An effective neuro-fuzzy controller is proposed to realize an accurate hydraulic servo-system regardless of the uncertainties and the external disturbances. For this purpose, first, we develop a simplified fuzzy logic controller which have multidimensional and unsymmetric membership functions. Secondly, we develop a neural network which consists of the parameters of the fuzzy logic controller. It is show that the neural network has both learning capability and linguistic representation capability. The proposed controller was implemented on a hydraulic servo-system. Feedback error learning architecture is adopted which uses the feedback error directly without passing through the dynamics or inverse transfer function of the hydraulic servo-system to train the neuro-fuzzy controller. A series of simulations was performed for the position-tracking control of the system subjected to external disturbances. The results of simulations show that regardless of inherent non-linearities and disturbances, an accuracy tracking-control performance is obtained using the proposed neuro-fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.360-365
• /
• 2003

In this paper, we have developed a general purpose motion controller using an FPGA(Field Programmable Gate Array). The multi-PID controllers on a single chip are implemented as a system-on-chip for multi-axis motion control. We also develop a PC GUI for an efficient interface control. Comparing with the commercial motion controller LM 629 it has multi-independent PID controllers so that it has several advantages such as space effectiveness, low cost and lower power consumption. In order to test the performance of the proposed controller, robot finger is controlled. The robot finger has three fingers with 2 joints each. Finger movements show that position tracking was very effective. Another experiment of balancing an inverted pendulum on a cart has been conducted to show the generality of the proposed FPGA PID controller. The controller has well maintained the balance of the pendulum.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.26 no.10
• /
• pp.766-770
• /
• 2013

This paper tried to develop a BLDC electric motor securing the 800 W-level watertight structure for driving the outboard motor. For this purpose, this paper developed a high-efficient controller-integrating BLDC electric motor system for underwater propulsion and designed and developed a triple watertight structure. Besides, this study developed a outboard motor integrating motor, propeller and controller based on the production of a controller for BLDC motor which can the speed control by selecting low-voltage, high-current power element. The characteristics of developed outboard motor were 24 V input voltage, over 800 W motor output, and max. 3,000 rpm motor, and 84.9% motor efficiency, and the developed outboard motor could secure the watertight structure in 5 m in water depth.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.400-405
• /
• 1990

This paper deals with the design technique of the controller for the discrete system control using Extended Safe Petri Net which is deduced from Petri Net as its subclass with a specific constraint and which is introduced to develop the design and analysis for the discrete systems. First, we propose a construction matrix suitable for the discrete systems that represent the marking flows which are the dynamic behavior of the discrete systems. Next, we develop a method that can design the controller for the discrete system control by analyzing the proposed construction matrix into the incidence matrix of Extended Safe Petri Net. Finally, the validity of the proposed method is shown by using the incidence matrix and matrix equation of Extended Safe Petri Net model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.568-576
• /
• 1998

In this thesis discuss with a flexible robotic finger design and controller which is used for the micro flexible robotic finger. So, miniaturization, precision, controller for the control of grasping force and actuator were needed. And, even if we develop a new actuator and controller, in order to use on real system, we must considerate of a many side problem. In a force control of micro flexible finger for grasping an object, the fingertip's vibration was more important task of accuracy control. And, controller were adopt the PD/PI mixed type fuzzy controller. The controller were consist of two part, one is a PD type fuzzy controller for increase the rising time response, the other is a PI type fuzzy controller for decrease of steady-state error. Especially, in a PD type fuzzy controller, we used only seven rules. And, for a PI controller, we adopt a reset factor for the control of input values. so, we have overcome the exceed of controller's input range. For the estimate of ontroller's utility and usefulness, we have experiment and computer simulation of three cases. First, we consider of unit force grasping control for a task object, which is 0.03N. Second, bounding grasping force control which is add to a sinusoidal force on the unit force. At this cases the task force is (0.03+0.01 sin wt N). And consider of following of rectangular forces.