Jung-Shik Kong

Optimized Walking Will Recognizing System of the Walking Aid with the Fuzzy Algorithm

This paper describes optimal operation method using recognition of walker`s will for a robotic walker. Recently, walking aid system has been required according to the increase of elder and handicapped person. However, most of walking aid system don`t have actuator for its movement. Unfortunately, standard frames have weakness for the movement to upward/download direction of slope. So, active type walking aids are interested, but it is not easy to control. In this paper, we adapt user`s will system that can recognize walking direction and speed. First, FSR(Force Sensing Register) is applied to measure user`s will to walk. And then, fuzzy algorithm is used for determining optimal wheel velocity and direction of the walking aid. From the result, walking aid can move smoothly and safely following the user`s will. The walking aid can help user to walk more optimally. Here, all the processes are verified experimentally in the real world.

Backlash compensation for a humanoid robot using disturbance observer

This paper describes the control of a geared DC motor having a backlash for implementation of a humanoid robot using disturbance observer. Critical problem of the humanoid robot is caused by the nonlinearity such as a backlash. To meet this problem, a control method using disturbance observer has been proposed. The disturbance observer is designed to estimate the effects of nonlinearities in the system, to make the nonlinear system behave linearly, and to cancel them efficiently. To design the low-pass filter in the disturbance observer, cut-off frequency of the output should be found. The goal of this paper is the implementation of the proposed system, compensating the backlash effect. To accomplish the goal, PD control and disturbance observer are employed to the system with no load and full load. As a result, system stability can be guaranteed by compensating the effect of backlash. In addition, real experiment shows the proposed control methodology will satisfy the stable working of a humanoid type in the future.

Messages scheduling for a humanoid robot in the CAN

This paper deals with the messages scheduling of a CAN (Controller Area Network), based on the distributed control scheme to integrate actuators and sensors in a humanoid robot. In order to supply the distributed processing for a humanoid robot, each control unit should have the efficient control method, fast calculation and valid data exchange. The preliminary study has concluded that the performance of CAN is better and easier to implement than other network such as FIP (Factory Instrumentation Protocol), VAN (Vehicle Area Network), etc. Since a humanoid robot has to treat the significant control signals from many actuators and sensors, the communication time limitation could be critical according to the transmission speed and data length of CAN specification. In this paper, the CAN message scheduling in a humanoid robot was suggested under the presence of Jitter in the message group, the existence of high load of messages over the network and the presence of transmission errors. In addition, the response time under the worst case is compared with the limitation by using the simulation algorithm. As a result, the suggested messages scheduling can guarantee our CAN limitation, and utilize to generate the walking patterns for the humanoid.

Vibration Reduction Algorithm at the Walking-will Recognition Sensor on Uneven Terrain

This paper presents the vibration reduction algorithm at the walking-will recognition sensors on the uneven terrain. Recently, concern about walking assistant aids is increasing according to the increase in population of elder and handicapped person. However, most of walking aids don`t have any actuators for its movement. So, general walking aids have weakness for its movement to upward/download direction of slope. To overcome the weakness of the general walking aids, many researches for active type walking aids are being progressed. Especially, vibration analysis and impulse reduction are one of the important elements of the active-type walking aid during moving on the outdoor area because the ground has many kinds of obstacles such as speed dumps, puddles and so on. So, we analyze the influence from vibration by uneven terrain. And then, we propose the impulse reduction algorithm to overcome the vibration. All the processes are verified experimentally in an active-type walking aid.

A Study on the Joint Controller for a Humanoid Robot based on Genetic Algorithm

This paper presents a joint controller for a humanoid robot based on genetic algorithm. h humanoid robot has basically instability during walking because it isn`t fixed on the ground. Moreover nonlinearities of the joints increase its instability. If one of them isn`t satisfied, the robot may fall down at the ground during walking. To attack one of those problems, joint controller is proposed. It can perform tracking control preciously and reduce the effect of nonlinearities by gear, limitation of the input voltage, coulomb friction and so on. This controller is based on fuzzy-sliding mode controller (FSMC) and compensator and control gains are searched by a proposed genetic algorithm. It can reduce the effect by nonlinearities. Also, to improve the tracking performance, the proposed controller has motion controller. From the given controller, a humanoid robot can moved more preciously. Here, all the processes are investigated through simulations and it is verified experimentally in a real joint system for a humanoid robot.

Nonlinear motor control using dual feedback controller

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems of the structural instability basically, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control are based on fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system that is employed by only single algorithm because the system includes multiple nonlinearities. In this paper, a switching PID is considered for a control of saturation, and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between simulation and experiment. After that, the switching PID gains are determined using genetic algorithm for removing limit cycle by saturation. The control algorithm is applied by dual feedback concept based on disturbance observer. All the processes are investigated through simulations and are verified experimentally in a real humanoid system.

Design of a switching PID controller using advanced genetic algorithm for a nonlinear system

This paper deals with a switching PID controller using a genetic algorithm in a multi-nonlinear system. In controlling the nonlinear element of the system, there are some problems such as the limit cycle. In this study, a switching PID controller was proposed to solve problems caused by nonlinearities of system. The PID is a well-known robust controller. But, in a motor system case, it may have a limit cycle when proportional gains exceed limit. However, in other case, if the PID gain is relatively small, its torque characteristics can be too weak. In this case, the suggested switching PID controller was found to be a good approach for solving these problems despite there being difficulties in determining its boundary and gains at each boundary. In this paper, an improved genetic algorithm was used for identifying a motor system and to determining each gain for the controller. In particular, new type of crossover and mutation using a sigmoid function is applied to improve the searching ability based on the proposed improved genetic algorithm. All the processes are investigated through simulations and are verified experimentally in a real motor system.

A Study on the Control Algorithm for Active Walking Aids by Using Torque Estimation

This paper presents the control algorithm of active walking aids estimating external torque of the wheels from user`s will. Nowadays, interest of the walking aids is increased according to the increase in population of elder and handicapped person. Although many walking aids are developed, most of walking aids don`t have any actuators for its movement. However, general walking aids have weakness for its movement to upward/download direction of slope. To overcome the weakness of the general walking aids, many researches for active type walking aids are being progressed. Unfortunately it is difficult to precision control of walking will during its movement, because it is not easy to recognize user`s walking will. Many kinds of methods are proposed to recognize of user`s walking will. In this paper, we propose control algorithm of walking aids by using torque estimation from wheels. First, we measure wheel velocity and voltage at the walking aids. From these data, external forces are extracted. And then walking will that is included by walking velocity and direction is estimated. Finally, walking aids are controlled by these data. Here, all the processes are verified by simulation.

Implementation of the Controller for a Stable Walking of a Humanoid Robot Using Improved Genetic Algorithm

This paper deals with the controller for a stable walking of a humanoid robot using genetic algorithm. A humanoid robot has instability during walking because it isn`t fixed on the ground, and its nonlinearities of the joints increase its instability. If controller isn`t robust, the robot may fall down at the ground during walking because of its nonlinearities. To solve this problem, robust controller is required to reduce the effect of nonlinearities and to gain the good tracking performance. In this paper, motion controller that is based on fuzzy-sliding mode controller is proposed. This controller can remove the effect of the saturation by limitation of the input voltage. It also includes compensator for reducing the effect of the nonlinearity by backlash and PI controller improving the tracking performance. In here, genetic algorithm is used for searching the optimal gains of the controller. From the given controller, a humanoid robot can moved more preciously. All the processes are investigated through simulations and are verified experimentally in a real joint system for a humanoid robot.

Improved genetic algorithm-based FSMC design for multi-nonlinear system

A new motion controller for the multi-nonlinear system is proposed by using a fuzzy sliding mode controller (FSMC) based on improved genetic algorithm (GA). In controlling the nonlinear element of the system, there are some critical problems such as the limit cycle. As the system has nonlinearities, a robust controller is one of the optimal solutions. The FSMC is a kind of the robust methods to control nonlinearities effectively in a system. Prior to applying a FSMC, genetic algorithm is used for identifying system without manual tuning and obtaining optimal fuzzy set of FSMC. The suggested GA is an improved type to find optimal solution. It uses new type of crossover and mutation with a sigmoid function that is applied to improve the searching ability. Also, an additional compensator and motion controller are suggested in order to improve position tracking. All the processes are investigated through simulations and experimentally verified in a real motor system.