This paper considers stabilization of a spacecraft with CMGs (Control Moment Gyros) via LPV (Linear Parameter-Varying) control theory, in which we obtain a GS (Gain-Scheduled) controller by using LMIs (Linear Matrix Inequalities). However, due to excess of the number of scheduling parameters, it is difficult to design a GS controller. In most cases, LMIs are infeasible. To reduce the number of scheduling parameters, in this study, we redefine the steering law of a spacecraft with CMGs. By using two types of steering laws, we attain stabilization of a spacecraft. In comparison of some designed results, we consider how to select the coefficient matrices of the performance output.
A method is proposed in this paper to give recommendations on styles of studying for junior high school students based on their individual properties. A Bayesian network for each academic subject is constructed from a questionnaire about grades and individual styles of studying. Then, for given individual properties, the styles of studying with a high probability of grade improvement are derived from the Bayesian network. The features of Bayesian networks constructed by the proposed method are examined.
In this paper we study the H∞ state estimation problems for a class of linear continuous-time systems with impulsive effects, stochastic uncertainties and discrete-time observation on the finite time interval. The systems include linear stochastic discrete-time systems. We adopt game theoretic and variational approach, and derive the impulsive Riccati equation which gives the necessary condition for the solvability of the H∞ estimation problems, the estimates and the form of H∞ estimators by calculating the stochastic first variation of the performance index under the dynamics constraint. By this approach the H∞ estimation problems are equivalent to the noncausal H∞ tracking control problems for the stochastic impulsive systems.
In this paper we study stochastic optimal tracking control theory with preview for linear continuous-time Markovian jump systems on the finite time interval by output feedback. We consider two different cases according to the structure of preview information and give the control strategies for them respectively. The necessary and sufficient conditions for the solvability of the stochastic optimal tracking problem with preview by state feedback are given by coupled Riccati differential equations with terminal conditions. In order to decide the gains of output feedback controllers, we need solutions of another type of coupled Riccati differential equations with initial conditions.
The dynamic model of variable speed hydro-turbine plant is proposed for controller design. The classical dynamic model of hydro-turbine plant includes a typical reverse response model. Then the response speed of the plant output is strictly limited in order not to respond reversely or oscillatory. In case of the variable speed hydro-turbine plant, faster response speed should be possible since the plant consists of winding-type synchronous generator whose output can be controlled by the excitation control. The proposed model is to design controller and analyze the plant dynamics. The model includes winding-type synchronous generator model and hydro-power plant water columnturbine characteristic model. The simulations by the model suggest that the reverse response problem can be avoided without serious water pressure rise and achieve much faster output power response.
Preemption is useful technique in real-time systems and several extensions of Merlin's time Petri net have been proposed to model the preemption. However, in timed Petri nets, the modeling of the preemption has not been studied. On the other hand, by optimization of a SAT/SMT solver, large scale problems are solvable in a realistic computation time by using a SAT/SMT formulation. In this paper, first, we define preemptive controlled timed Petri nets abbreviated as pCTdPNs, where the control of the preemption is done by external input places. Next, we represent their dynamics using SMT formulae. Finally, we apply pCTdPNs to modeling of distributed mediators with several tasks executed by multi-processor systems, and obtain a task assignment to each processor and task scheduling using an SMT solver.