• 전기의세계
• /
• 제22권1호
• /
• pp.28-34
• /
• 1973

This paper treats with the sub-optimal control problem of noninear systems by approximation method. This method involves the approximation by linearization which provides the sub-optimal solution of non-linear control problems. The result of this work shows that, in the problem in which the controlled plant is characterized by an ordinary differential equation of first order, the solution obtained by this method coincides with the exact solution of problem. In of case of the second or higher order systems, it is proved analytically that this method of linearization produces the sub-optimal solution of the given problem. It is also shown that the sub-optimality of solution by the method can be evaluated by introducing the upper and lower bounded performance indices. Discussion is made on the procedure with some illustrative examples whose performance indices are given in the quadratic forms.

• 제어로봇시스템학회논문지
• /
• 제5권4호
• /
• pp.403-410
• /
• 1999

In this study, a parallel algorithm has been developed that can quickly solve the optiaml control problem of large-scale dynamic systems. The algorithm adopts the sequential quadratic programming methods and achieves domain decomposition-type parallelism in computing sensitivities for search direction computation. A silicon wafer thermal process problem has been solved using the algorithm, and a parallel efficiency of 45% has been achieved with 16 processors. Practical methods have also been investigated in this study as a way to further speed up the computation time.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.272-275
• /
• 1997

When a manipulator makes contact with an object having position uncertainty, performance measures vary considerably with the control law. To achieve the optimal solution for this problem, an unique objective function that weights time and impact force is suggested and is solved with the help of variational calculus. The resulting optimal velocity profile is then modified to define a sliding mode for the impact and force control. The sliding mode control technique is used to achieve the desired performance. Sets of experiments are performed, which show superior performance compared to any existing controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.1169-1172
• /
• 1996

A time-optimal control law for quick, strongly nonlinear systems has been developed and demonstrated. This procedure involves the utilization of neural networks as state feedback controllers that learn the time-optimal control actions by means of an iterative minimization of both the final time and the final state error for the known and unknown systems with constrained inputs and/or states. The nature of neural networks as a parallel processor would circumvent the problem of "curse of dimensionality". The control law has been demonstrated for a velocity input type motor identified by a genetic algorithm called GENOCOP.

• 대한전기학회논문지
• /
• 제31권7호
• /
• pp.18-24
• /
• 1982

We derived an optimal control of the Stochastic Bilinear Systems. For that we, firstly, formulated stochastic bilinear system and estimated its state when the system state is not directly observable. Optimal control problem of this system is reviewed on the line of three optimization techniques. An optimal control is derived using Hamilton-Jacobi-Bellman equation via dynamic programming method. It consists of combination of linear and quadratic form in the state. This negative feedback control, also, makes the system stable as far as value function is chosen to be a Lyapunov function. Several other properties of this control are discussed.

• ETRI Journal
• /
• 제36권2호
• /
• pp.280-285
• /
• 2014

In this paper, the optimal power control problem in a cooperative relay network is investigated and a new power control scheme is proposed based on a non-cooperative differential game. Optimal power allocated to each node for a relay is formulated using the Nash equilibrium in this paper, considering both the throughput and energy efficiency together. It is proved that the non-cooperative differential game algorithm is applicable and the optimal power level can be achieved.

• 대한전기학회논문지
• /
• 제34권5호
• /
• pp.173-178
• /
• 1985

The control of a linear system with random coefficients is discussed here. The cost function is of a quadratic form and the random coefficients are assumed to be completely observable by the controller. Stochastic Process involved in the problem by the controller. Stochastic Process involved in the problem formulation is presented to be the unique strong solution to the corresponding stochastic differential equations. Condition for the optimal control is represented through the existence of solution to a Cauchy problem for the given nonlinear partial differential equation. The optimal control is shown to be a linear function of the states and a nonlinear function of random parameters.

• Smart Structures and Systems
• /
• 제19권1호
• /
• pp.21-31
• /
• 2017

To control the stochastic vibration of a vibration-sensitive instrument supported on a beam, the beam is designed as a sandwich structure with magneto-rheological visco-elastomer (MRVE) core. The MRVE has dynamic properties such as stiffness and damping adjustable by applied magnetic fields. To achieve better vibration control effectiveness, the optimal bounded parametric control for the MRVE sandwich beam with supported mass under stochastic and deterministic support motion excitations is proposed, and the stochastic and shock vibration suppression capability of the optimally controlled beam with multi-mode coupling is studied. The dynamic behavior of MRVE core is described by the visco-elastic Kelvin-Voigt model with a controllable parameter dependent on applied magnetic fields, and the parameter is considered as an active bounded control. The partial differential equations for horizontal and vertical coupling motions of the sandwich beam are obtained and converted into the multi-mode coupling vibration equations with the bounded nonlinear parametric control according to the Galerkin method. The vibration equations and corresponding performance index construct the optimal bounded parametric control problem. Then the dynamical programming equation for the control problem is derived based on the dynamical programming principle. The optimal bounded parametric control law is obtained by solving the programming equation with the bounded control constraint. The controlled vibration responses of the MRVE sandwich beam under stochastic and shock excitations are obtained by substituting the optimal bounded control into the vibration equations and solving them. The further remarkable vibration suppression capability of the optimal bounded control compared with the passive control and the influence of the control parameters on the stochastic vibration suppression effectiveness are illustrated with numerical results. The proposed optimal bounded parametric control strategy is applicable to smart visco-elastic composite structures under deterministic and stochastic excitations for improving vibration control effectiveness.

• International Journal of Control, Automation, and Systems
• /
• 제6권6호
• /
• pp.845-858
• /
• 2008

In this paper, we consider a terminal, linear control system with delay, subject to unknown but bounded disturbances. For this system, we consider the problem of constructing a worst-case optimal feedback control policy, which can be corrected at fixed, intermediate time instants. The policy should guarantee that for all admissible uncertainties the system states are in prescribed neighborhoods of predefined system states, at all fixed, intermediate time instants, and in the neighborhood of a given state at a terminal time instant, and the value of the cost function is the best guaranteed value. Simple explicit rules(which can be easily implemented on-line) for constructing the optimal control policy in the original control problem are derived.

• Smart Structures and Systems
• /
• 제10권1호
• /
• pp.15-31
• /
• 2012

This study proposes an active control method to suppress beam-rotating machinery system vibrations. The present control method is a combination of the fuzzy input estimation method (FIEM) and linear quadratic Gaussian problem (LQG) algorithms. The FIEM can estimate the unknown input and optimal states by measuring the dynamic displacement, the optimal estimated states into the feedback control; thereby obtaining the optimal control force for a random linear system. Active vibration control of a beam-rotating machinery system is performed to verify the feasibility and effectiveness of the proposed algorithm. The simulation results demonstrate that the proposed method can suppress vibrations in a beam-machine system more efficiently than the conventional LQG method.