• Structural Engineering and Mechanics
• /
• v.81 no.3
• /
• pp.267-280
• /
• 2022

Multiscale structure has attracted significant interest due to its high stiffness/strength to weight ratios and multifunctional performance. However, most of the existing concurrent topology optimization works are carried out under deterministic load conditions. Hence, this paper proposes a robust concurrent topology optimization method based on the bidirectional evolutionary structural optimization (BESO) method for the design of structures composed of periodic microstructures subjected to uncertain dynamic loads. The robust objective function is defined as the weighted sum of the mean and standard deviation of the module of dynamic structural compliance with constraints are imposed to both macro- and microscale structure volume fractions. The polynomial chaos expansion (PCE) method is used to quantify and propagate load uncertainty to evaluate the objective function. The effective properties of microstructure is evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The proposed method is a non-intrusive method, and it can be conveniently extended to many topology optimization problems with other distributions. Several numerical examples are used to validate the effectiveness of the proposed robust concurrent topology optimization method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.9
• /
• pp.757-763
• /
• 2002

A newly designed haptic interface enables an operator to control a remote robot precisely. It transmits position information to the remote robot and feeds back the interaction force from it. A control algorithm of haptic interface has been studied to improve the robustness and stability to uncertain dynamic environments with a proposed contact dynamic model that incorporates human hand dynamics. A simplified hybrid parallel robot dynamic model fur a 6 DOF haptic device was proposed to from a real time control system, which does not include nonlinear components. LQC/LTR scheme was adopted in this paper for the compensation of un-modeled dynamics. The recovery of the farce from the remote robot at the haptic interface was demonstrated through the experiments.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.792-796
• /
• 1992

Readings from robotic sensors are somewhat uncertain. This uncertainty problem makes it difficult to employ the sensor feedback controlled robots widely in real industrial sites, In this paper, redundant sensor fusion techniques are discussed to effectively overcome the sensor uncertainty, A weighted averaging technique is proposed under static and dynamic sensing environments. Proposed technique is tested by the experiments of stereoscopic 3d position measurements.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.127-130
• /
• 1990

The fuzzy logic controller which can be applied to various industrial processes is quite often dependent on the heuristics of the experienced operator. The operator's knowledge is often uncertain. Therefore an incorrect control rule on the basis of the operator's information is a cause of bad performance of the system. This paper proposes a new self-learning fuzzy control method by the fuzzy system identification using the data pairs of input and output and arbitrary initial relation matrix. The position control of a DC servo motor model is simulated to verify the effectiveness of the proposed algorithm.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2308-2310
• /
• 2000

In adaptive fuzzy control, fuzzy systems are used to approximate the unknown plant nonlinearities. Until now, most of the papers in the field of controller design for nonlinear system using fuzzy systems considers the affine system with fixed grid-rule structure. This paper considers general nonlinear systems and dynamic fuzzy rule structure. Adaptive laws for fuzzy parameters and fuzzy rule structrue are established so that the whole system is stable in the sense of Lyapunov.

• 제어로봇시스템학회:학술대회논문집
• /
• 1999.10a
• /
• pp.133-136
• /
• 1999

Many researches on the identification of a system have been carried out using a least square method, an adaptive filter, and so on. However, it is difficult to apply these methods in a nonlinear system. In the case of a nonlinear system, it is known that the signal compression method is able to estimate uncertain parameters of linear element in a nonlinear system because it is able to separate linear element and nonlinear element in a nonlinear system. However, the signal compression method cannot be applied to a motion simulator because actuators of the simulator is single-rod cylinders which includes expansion and compression dynamic properties. Therefore, this paper proposes a modified signal compression method which is able to estimate uncertain parameters of the motion simulator dynamics. The dynamic properties of this system are identified by separating expansion and compression properties when applying the signal compression method. And then, the identified parameters are applied to design a sliding mode controller for the simulator. The performance of the designed sliding mode controller is evaluated experimentally.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.4
• /
• pp.311-314
• /
• 2001

Recently, research on Intelligent Information Process has actively been under way JD various areas and gradually extended to be adaptive to uncertain and complex dynamic environments. This paper presents a Multiple Valued Logic Automata(MVL-Automata) Model, utilizing properties of difference in a Multiple Valued Logic function. That is, MVL-Automata is able to be autonomously adapted to dynamic changing since an input stling is mapped to the value of a Multiple Valued Logic function and the property of difference in a Multiple Valued Logic function is applied to state transition. Therefore, Multiple Valued Logic Automata can be widely applied to the modeling dynamically of changing environments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.3
• /
• pp.297-305
• /
• 1999

Autonomous mobile robots are required to achieve multiple goals while responding quickly to the dynamic environments. An appropriate robot control architecture, which clearly and systematically defines the relationship among the inputs, the processing functions and the outputs, thus needs to be embedded in the robot controller. This paper proposes a kind of hybrid control architecture which combines the key features of the two well-known robot control architectures; hierarchical and behavioral- based. The overall control architecture consists of three layers, i.e. the highest planner, the middle plan executor, and the lowest monitor and behavior-based controller. In the planned situation, only one behavior module is chosen by the logical coordinator in the plan executor according to the way point bin. In the exceptional situation, the central controller in the plan executor issues an additional control command to reach the planned way point. Several simulations and experiments with autonomous mobile robot show that the proposed architecture enables the robot controller to achieve the multiple sequential goals even in dynamic and uncertain environments.

• Industrial Engineering and Management Systems
• /
• v.6 no.2
• /
• pp.106-118
• /
• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.594-597
• /
• 2005

In this paper, I-PDA controller based on Coefficient Diagram Method incorporating feedforward controller is applied by robotic manipulators. Robotic manipulator models contain uncertain elements, which are not known exactly. Therefore, the dynamics of robotic manipulators are generally classified as uncertain dynamic system. The controller considered for the robotic manipulators need to move payloads of different masses from one point to another with good balance of the stability and response, consequently we propose I-PDA controller based on Coefficient Diagram Method incorporating FFC. The effectiveness of the controller for different system type of robotic manipulators is demonstrated by the simulation results.