In this paper, we present a novel PPP algorithm by applying the double difference for GNSS observables among multiple antennas (receivers), and apply improved VPPP algorithms. First of all, the GR models for double difference observables are shown which are similar to the GR models for the relative positioning algorithms, but both antennas’' positions are unknown. Then we derive the Kalman filtering algorithms for recursive estimation of all antennas’' positions and double difference integer ambiguity of all carrier-phases in GNSS observables. Then using the geometric constraints for all antennas’' positions, we derive the algorithms of updating the estimated parameters including antennas’' positions and integer ambiguities. Finally we show the experimental results of the proposed VPPP algorithm comparing with the previous VPPP algorithm.

In this paper, the liquid level control of separator in an ocean thermal energy conversion (OTEC) experimental plant with Uehara cycle is considered. A liquid level model of separator is constructed based on not only experimental data about the characteristics between the liquid level and the valve opening but also simulations using a stochastic model. The control system for the liquid level control of separator is designed by employing the LQG control theory. The usefulness of both the liquid level model and the control system is confirmed through simulations.

In this paper, a rotary-type unstable inverted pendulum system is modeled by using a parameter-dependent linear-time-invariant (PD-LTI) system. The pendulum systems operating at upright and downright positions are modeled by a PD-LTI system with a scheduling parameter that is fixed in each operation. The unknown parameters are estimated by taking a grey-box modeling approach to the pendulum system operating at the downright position. It is also considered how to choose the model structure by taking numerical condition into account.

The paper considers a non-fagile control design via dynamic output feedback controller for fuzzy stochastic systems that are subject to stochastic disturbances. In practical situations, robust control design methods should take case of disturbances into the system and variations in control gains, and they should assume that not all the states of the system are available for the feedback control. In addition, malfunction may occur in actuators. Hence, a non-fragile output feedback control design is desired. In this paper, robust stabilization via dynamic output feedback control with uncertain control gain for fuzzy stochastic systems is considered and a control design of robust stabilizing controllers is proposed. The robust stability analysis of the closed-loop system and non-fragile controller design via descriptor system approach are given in terms of LMI conditions. The resulting conditions are less conservative than the existing results. An illustrative example is provided to show the effectiveness of the proposed method.