• ETRI Journal
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• v.42 no.5
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• pp.700-711
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• 2020

Because of the rapid increase of mobile traffic, flexible broadband supportive unmanned aerial vehicle (UAV)-based 6G mobile networks using free space optical (FSO) links have been recently proposed. Considering the advancements made in UAVs, big data processing, and artificial intelligence precision control technologies, the formation of an additional wireless network based on UAV aerial platforms to assist the existing fixed base stations of the mobile radio access network is considered a highly viable option in the near future. In this paper, a combined time bound optimization scheme is proposed that can adaptively satisfy the control and communication time constraints as well as the processing time constraints in FSO-based 6G UAV aerial networks. The proposed scheme controls the relation between the number of data flows, input data rate, number of worker nodes considering the time bounds, and the errors that occur during communication and data processing. The simulation results show that the proposed scheme is very effective in satisfying the time constraints for UAV control and radio access network services, even when errors in communication and data processing may occur.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.174-182
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• 1999

This paper describes a research work of developing a computer-aided design of product with bending constraints and piercing for progressive working. an approach to the CAD system is based on the knowledge-based rules. Knowledge for the CAD system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written AutoLISP on the AutoCAD with a personal computer and is composed of four main modules, which are input and shape treatment, flat pattern layout, production feasibility check, and strip-layout module. Based on knowledge-based rules, the system is designed by considering several factors, such as radius and angle of bend, material and thickness of product, complexities of blank geometry and punch profile, bending sequence, availability of press. Strip layout drawing generated by piercing with punch profiles divide into automatically for external area is shown into graphic forms, including bending sequences for the product with piercing and bending constraints. Results obtained using the modules enable the designer and manufacturer of piercing and bending dies to be more efficient in this field.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.208-220
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• 2006

Energy of wheeled mobile robot is usually supplied by batteries. In order to extend operation time of mobile robots, it is necessary to minimize the energy consumption. The energy is dissipated mostly in the motors, which strongly depends on the velocity profile. This paper investigates various 3-step (acceleration - cruise - deceleration) speed control methods to minimize a new energy object function which considers the practical energy consumption dissipated in motors related to motor control input, velocity profile, and motor dynamics. We performed an analysis on the energy consumption various velocity profile patterns generated by standard control input such as step input, ramp input, parabolic input, and exponential input. Based on these standard control inputs, we analyzed the six 3-step velocity profile patterns: E-C-E, P-C-P, R-C-R, S-C-S, R-C-S, and S-C-R (S means a step control input, R means a ramp control input, P means a parabolic control input, and E means an exponential control input, C means a constant cruise velocity), and suggested an efficient iterative search algorithm with binary search which can find the numerical solution quickly. We performed various computer simulations to show the performance of the energy-optimal 3-step speed control in comparison with a conventional 3-step speed control with a reasonable constant acceleration as a benchmark. Simulation results show that the E-C-E is the most energy efficient 3-step velocity profile pattern, which enables wheeled mobile robot to extend working time up to 50%.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.12
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• pp.998-1003
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• 2002

As nonholonomic dynamic systems have constraints imposed on motions that are not integrable, i.e., the constraints cannot be written as time derivatives of some functions of generalized coordinates, advanced techniques are needed for their control. In this paper, a sliding mode tracking control for nonholonomic dynamic systems is proposed. By introducing a general scheme of coordinate transformation, the state of nonholonomic systems is mapped into a bounded space and a robust controller for dynamic models of nonholonomic systems with input disturbances is designed using sliding mode control scheme. Simulation results of tacking control for a nonholonomic mobile robot with two actuated wheels are provided to show the effectiveness of the proposed controller.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.285-288
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• 1996

Generally MPS, standardized by IBM, is the input type of large scale linear programming problems, and there may be unnecessary variables or constraints. These can be discarded by preprocessing. As the size of a problem is reduced by preprocessing, the running time is reduced. And more, the infeasibility of a problem may be detected before using solution methods. When the preprocessing implemented by this paper is used in NETLIB problems, it removes unnecessary variables and constraints by 21%, 15%, respectively. The use of preprocessing gives in the average 21% reduction in running time by applying the interior point method. Preprocessing can detect 10 out of 30 infeasible NETLIB problems.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.697-699
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• 2000

In this paper, an extension of model predictive controller for nonlinear process using Takagi-Sugeno(TS) fuzzy model is proposed Since the consequent parts of TS fuzzy model comprise linear equations of input and output variables. it is locally linear, and the Generalized Predictive Control(GPC) technique which has been developed to control Linear Time Invariant(LTI) plants, can be extended as a parallel distributed controller. Also fuzzy soft constraints are introduced to handle both equality and inequality constraints in a unified form. So the traditional constrained GPC can be transferred to a standard fuzzy optimization problem. The proposed method conciliates the advantages of the fuzzy modeling with the advantages of the constrained predictive control, and the degree of freedom is increased in specifying the desired process behavior.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.145-150
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• 1999

A real-time control system, composed of the controlled processor and the controller computer(s), may have a variety of task types, some of which have tight timing-constraints in generating the correct control input. The maximum period of those task failures tolerable by the system is called the hard deadline, which depends on not only fault characteristics but also task characteristics. In the paper, we extend a method deriving the hard deadline in LTI system executing single task. An algorithm to combine the deadlines of all the elementary tasks in the same operation-mode is proposed to derive the hard deadline of the entire system. For the end, we modify the state equation for the task to capture the effects of task failures (delays in producing correct values) and inter-correlation. We also classify the type of executing the tasks according to operation modes associated with relative importance of correlated levels among tasks, into series, parallel, and cascade modes. Some examples are presented to demonstrate the effectiveness of the proposed methods.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.732-735
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• 1999

A GA-based optimization technique is adopted in the paper to obtain optimal future control inputs for predictive control systems. For reliable future predictions of a process, we identify the underlying process with an NNARX model structure and investigate to reduce the volume of neural network based on the Lipschitz index and a criterion. Since most industrial processes are subject to their constraints, we deal with the input-output constraints by modifying some genetic operators and/or using a penalty strategy in the GAPC. Some computer simulations are given to show the effectiveness of the GAPC method compared with the adaptive GPC algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.515-515
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• 2000

The performance of dynamic path following of a wheeled mobile robot with nonholonomic constraints has some drawbacks such as the influence of the initial state. The drawbacks can be overcome by the temporary path generator and modified output. But with the previous input-output linearization method using them, it is difficult to tune the gains, and if there are some modeling errors, the low gain can make the system unstable. And if a high gain is used to overcome the model uncertainties, the control inputs are apt to be large so the system can be unstable. In this paper. an H$_{\infty}$ controller is designed to guarantee robustness to model parameter uncertainties and to consider the magnitude of control inputs. And the solution to Hamilton Jacobi (HJ) inequality, which is essential to H$_{\infty}$ control design, is obtained by nonlinear matrix inequality (NLMI).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4387-4404
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• 2015

The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.