• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.499-505
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• 2011

In this paper, we proposed an adaptive fuzzy sliding mode control for nonlinear systems without parameter projection method. By modifying the controller structure, the parameters of the estimated input gain function are guaranteed not being identically zero and it is shown that the control scheme will not cause any implementation problem even if the estimated value of input gain function is zero at any moment during on-line operations. Except for the input gain function which an approximate estimate for its lower bound is needed, the proposed control scheme does not assume a priori the exact values of the bounding parameters. Based on Lyapunov synthesis methods, the overall control system guarantees that the tracking error asymptotically converges to zero and that all signals involved in controller are uniformly bounded. This can be illustrated by the simulation results for an inverted pendulum system.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.13-17
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• 2024

In this paper, union-based rule antecedent neuro-fuzzy controller, which can guarantee a parsimonious knowledge base with reduced number of rules, is proposed. The proposed neuro-fuzzy controller allows union operation of input fuzzy sets in the antecedents to cover bigger input domain compared with the complete structure rule which consists of AND combination of all input variables in its premise. To construct the proposed neuro-fuzzy controller, we consider the multiple-term unified logic processor (MULP) which consists of OR and AND fuzzy neurons. The fuzzy neurons exhibit learning abilities as they come with a collection of adjustable connection weights. In the development stage, the genetic algorithm (GA) constructs a Boolean skeleton of the proposed neuro-fuzzy controller, while the stochastic reinforcement learning refines the binary connections of the GA-optimized controller for further improvement of the performance index. An inverted pendulum system is considered to verify the effectiveness of the proposed method by simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.912-918
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• 2016

This paper presents various strategies for humanoid vehicle driving and egress tasks. For driving, a tele-operating system that controls a robot based on a human operator's commands is built. In addition, an autonomous assistant module is developed for the operator. Normal position control can result in severe damage to robots when they egress from vehicles. To prevent this problem, another approach that mixes various joint control techniques is adopted in this study. Additionally, a footplate is newly designed and attached to the vehicle floor for the ground landing phase of the egress task. The attached plate enables the robot to step down onto the ground in a safe manner. For stable locomotion, a balance controller is designed for the humanoid. For the design of the controller, the robot is modeled using an inverted pendulum that consists of a spring and a damper. Then, a state feedback controller (with pole placement and a state observer) is built based on the simplified model. Many approaches that are presented in this paper were successfully applied to a full-sized humanoid, DRC-HUBO+, in the DARPA Robotics Challenge Finals, which were held in the United States in 2015.

• Korean Journal of Applied Biomechanics
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• v.25 no.1
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• pp.29-37
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• 2015

Objective : The purpose of this study was to investigate the biomechanical properties of shock absorption strategy and postural stability during the drop landing for each types. Methods : The motions were captured with Vicon Motion Capture System, with the fourteen infra-red cameras (100Hz) and synchronized with GRF(ground reaction force) data(1000Hz). Ten male soccer players performed a drop landing with single-leg and bi-legs on the 30cm height box. Dependent variables were the CoM trajectory and the Joint Moment. Statistical computations were performed using the paired t-test and ANOVA with Turkey HSD as post-hoc. Results : The dominant leg was confirmed to show a significant difference between the left leg and right leg as the inverted pendulum model during Drop Landing(Phase 1 & Phase 2). One-leg drop landing type had the higher CoM displacement, the peak of joint moment with the shock absorption than Bi-leg landing type. As a lower extremity joint kinetics analysis, the knee joint showed a function of shock absorption in the anterior-posterior, and the hip joint showed a function of the stability and shock absorption in the medial-lateral directions. Conclusion : These findings indicate that the instant equilibrium of posture balance(phase 1) was assessed by the passive phase as Class 1 leverage on the effect of the stability of shock absorption(phase 2) assessed by the active phase on the effect of Class 2 leverage. Application : This study shows that the cause of musculo-skeletal injuries estimated to be focused on the passive phase of landing and this findings could help the prevention of lower damage from loads involving landing related to the game of sports.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.65-73
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• 1997

This paper proposes a new method of the structure pruning of dynamic recurrent neural networks (DRNN) using evolutionary computations. In general, evolutionary computations are population-based search methods, therefore it is very useful when several different properties of neural networks need to be optimized. In order to prune the structure of the DRNN in this paper, we used the evolutionary programming that searches the structure and weight of the DRNN and evolution strategies which train the weight of neuron and pruned the net structure. An addition or elimination of the hidden-layer's node of the DRNN is decided by mutation probability. Its strategy is as follows, the node which has mhnimum sum of input weights is eliminated and a node is added by predesignated probability function. In this case, the weight is connected to the other nodes according to the probability in all cases which can in- 11:ract to the other nodes. The proposed pruning scheme is exemplified on the stabilization and position control of the inverted-pendulum system and visual servoing of a robot manipulator and the effc: ctiveness of the proposed method is demonstrated by numerical simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.3-12
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• 1996

Sliding mode controller(SMC) is a simple but powerful nonlinear controller, because it guarantees the stability and the robustness. However, it leads to the high frequency chattering of the control input. Although the phenomenon can be avoided by introducing a thin boundary layer to the sliding surface, the method results in a steady state: error proportional to the boundary layer thickness. In this paper, we proposed a new sliding mode controller with self-tuning the thickness of a boundary layer. It uses a fuzzy rule base for tuning the thickness of a boundary layer. That is, the thickness is increased to some degree to reject a discontinuous control input at the initial state and then it is decreased as the states approaches to the steady states for improving the tracking performance. In order to assure the control performance, we perf'ormed the computer simulation using an inverted pendulum system as a controlled plant.