• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1402-1407
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• 2004

Moving a fragile object from an initial point to a goal location in minimum time without damage is pursued in this paper. In order to achieve the goal, first of all, the range of maximum acceleration and velocity are specified, which the manipulator can generate dynamically on the path that is planned a priori considering the geometrical constraints. Later, considering the impulsive force constraint of the object, the range of maximum acceleration and velocity are going to be obtained to keep the object safe while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of the acceleration and velocity. This time optimal trajectory planning can be applied for real applications and is suitable for not only a continuous path but also a discrete path.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1136-1139
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• 1996

For on-line trajectory planning such as teleoperation it is desirable to keep good manipulability of the robot manipulators since the motion command is not given in advance. To keep good manipulability means the capability of moving any arbitrary directions of task space. An optimization process with different manipulability measures are performed and compared for a redundant robot system moving in 2-dimensional task space, and gives results that the conventional manipulability ellipsoid based on the Jacobian matrix is not good choice as far as the optimal direction of motion is concerned.

• 전기의세계
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• v.21 no.1
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• pp.13-16
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• 1972

Dynamic Programming is regarded as a very powerful tool for solving nonlinear optimization problem subject to a number of constraints of state and control variables, but has definite disadvantages that it requires much more computing time and consumes much more memory spaces than other technigues. In order to eliminate the above-mentioned demerits, this paper suggests a news technique called Multiple Dynamic Programming. The underlying principles are based on the concept of multiple passes that, instead of forming fin lattices in time-state plane as adopted in the conventional Dynamic Programming, the Multiple Dynamic Programming constitutes, at the first pass, coarse lattices in the feasible domain of time-state plane and determines the optimal state trajectory by the usual method of Dynamic Programming, and at the second pass again constitutes finer lattices in the narrower domain surrounded by both the upperand lower edges next to the lattice edges through which the first pass optimal trajectory passes and determines the more accurate optimal trajectory of state, and then at the third pass repeats the same processes, and so on. The suggested technique insures remarkable curtailment in amounts of computer memory spaces and conputing time, and its applicability has been demonstrated by a case study on the hydro-thermal power coordination in Korean power system.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.560-565
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• 2014

In this study, the problem of trajectory optimization for underwater gliders considering depth constraints is discussed. Typically, underwater gliders are controlled to dive and climb in a saw-tooth pattern at constant gliding angles. This approach is effective and close to optimal for deep water applications. However, the optimal path deviates from the saw-tooth path in shallow water conditions. This study focuses on finding more efficient gliding paths that can minimize the traverse time in the horizontal plane when the water depth is limited. The trajectory optimization problem is formulated into a minimum time control problem with inequality path constraints and hydrodynamic drag effects. A numerical approach based on the pseudo-spectral method is adopted as a solution approach, and the simulation results are presented.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.5
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• pp.397-404
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• 1999

In this paper, several control methods for the discontinuous mode PWlvl-SRC are investigated with the l linearized small signal model. In order to analyze the stability and dyncunic characteristics of the controlled s system, the root locus as a function of the normaliz떠 output current(]\iOC) for a given normalized output v voltage(NOV) is employed. FurLhem10re, in this paper, the “Optimal trajectory control of PWM-SRC" is newly p propos(xl and its good dvnamic performances are evaluated with other four control laws.laws.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.1
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• pp.99-110
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• 1995

An industrial robot needs a simple and robust control algorithm obtaining high precision control performance in spite of disturbance and parameter's change. In this paper, for solving this problem, a new sliding mode control algorithm is proposed and applied to the trajectory control of a SCARA type robot. The proposed algorithm has diminished the chattering occurring in sliding mode by setting a dead band along the switching line on the phase plane. It shows that we can easily obtain a simple switching control input satisfying sliding mode in spite of regarding nonlinear terms of a manipulator and servo system as disturbance. A guideline for selection of dead-band width is determined by optimal value of cost function presenting magnitudes of chattering and error. By this algorithm, we can expect the high performance of the trajectory tracking of an industrial robot which needs a robust and simple algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.575-577
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• 1987

A new control method for DC motor position control with variable structure is presented. The proposed method uses the desired trajectory with optimal input satisfying the given performance requirement as the switching curve and is insensitive to parameter variation and disturbance. To show the validity of the proposed method, digital computer simulation is performed. And the result is compared with that of the optimal state feedback.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.831-836
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• 2007

This paper proposes an optimal galloping trajectory which costs low energy and guarantees the stability of the quadruped robot. In the realization of the fast galloping, the trajectory design is important. As a galloping trajectory, we propose an elliptic leg trajectory, which provides simplified locomotion to complex galloping motions of animals. However, the elliptic trajectory, as an imitation of animal galloping motion, does not guarantee stability and minimal energy consumption. We propose optimization based on the energy and stability using a genetic algorithm, which provides the robust and global solution to a multi-body, highly nonlinear dynamic system. To evaluate and verify the effectiveness of the proposed trajectory, computer simulations were carried out.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.75-82
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• 2006

In this paper, we propose an optimal trajectory for biped robots to move up-and-down stairs using a genetic algorithm and a computed-torque control for biped robots to be dynamically stable. First, a Real-Coded Genetic Algorithm (RCGA) which of operators are composed of reproduction, crossover and mutation is used to minimize the total energy. Constraints are divided into equalities and inequalities: Equality constraints consist of a position condition at the start and end of a step period and repeatability conditions related to each joint angle and angular velocity. Inequality constraints include collision avoidance conditions of a swing leg at the face and edge of a stair, knee joint conditions with respect to the avoidance of the kinematic singularity, and the zero moment point condition with respect to the stability into the going direction. In order to approximate a gait, each joint angle trajectory is defined as a 4-th order polynomial of which coefficients are chromosomes. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot that consists of seven links in the sagittal plane. The trajectory is more efficient than that generated by the modified GCIPM. And various trajectories generated by the proposed GA method are analyzed in a viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.405-413
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• 2006

A novel approach based on genetic algorithms (GA) is developed to find a global minimum-jerk trajectory of a space robotic manipulator in joint space. The jerk, the third derivative of position of desired joint trajectory, adversely affects the efficiency of the control algorithms and stabilization of whole space robot system and therefore should be minimized. On the other hand, the importance of minimizing the jerk is to reduce the vibrations of manipulator. In this formulation, a global genetic-approach determines the trajectory by minimizing the maximum jerk in joint space. The planning procedure is performed with respect to all constraints, such as joint angle constraints, joint velocity constraints, joint angular acceleration and torque constraints, and so on. We use an genetic algorithm to search the optimal joint inter-knot parameters in order to realize the minimum jerk. These joint inter-knot parameters mainly include joint angle and joint angular velocities. The simulation result shows that GA-based minimum-jerk trajectory planning method has satisfactory performance and real significance in engineering.