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This paper investigates the problem of stabilization of sampled-data neural-network-based systems with state quantization. Different with previous works, the communication limitation of state quantization is considered for the first time. More specifically, it is assumed that the sampled state measurements from sensor to the controller are quantized via a quantizer. To reduce conservativeness, a novel piecewise Lyapunov-Krasovskii functional (LKF) is constructed by introducing a line-integral type Lyapunov function and some useful terms that take full advantage of the available information about the actual sampling pattern. Based on the new LKF, much less conservative stabilization conditions are derived to obtain the maximal sampling period and the minimal guaranteed cost control performance. The desired quantized sampled-data three-layer fully connected feedforward neural-network-based controllers are designed by a linear matrix inequality approach. A search algorithm is given to find the optimal values of tuning parameters. The effectiveness and advantage of proposed method are demonstrated by the numerical simulation of an inverted pendulum.

Given their hovering ability, static lift airships, such as airships and balloons, are proposed as stratospheric platforms flying at a high altitude of 20 km. The shape of the envelope has a major influence on the lift and drag efficiency of an airship. Furthermore, the efficiency of a conventional actuator, such as an aerodynamic control surface for stratospheric platforms, is decreased by the low-atmospheric density and flight speed. Thus, a new type of effector configuration must be proposed. A new multivectored thrust airship called flat peach is proposed in this paper. The name is attributed to the shape of the airship, which resembles a flat peach that is a cross between a ball and a water droplet. Thus, this airship has a smaller drag coefficient than the spherical airship and higher lift efficiency than a conventional airship. A control allocation strategy among the multivectored thrusters is proposed, and a composite control structure is designed for the airship to realize accurate position control and to decrease energy consumption.

A stratospheric airship is an airship flying at a high altitude of 20 km as a stratospheric platform. Due to the low atmospheric density and flight speed, the efficiency of a conventional actuator, such as an aerodynamic control surface, is decreased. Thus, a new multi-vectored thrust airship called a flat peach is discussed in this paper. This article describes the derivation, design and simulation implementation of a non-linear controller for an airship with multi-vector thrust. The controller is designed using a command-filtered, vector backstepping approach, and can set the airship track three Cartesian positions [Formula: see text] and yaw angle to their desired values and stabilize the pitch and roll angles. The controller is non-linear to address the kinematics and airship dynamics. The approach guarantees exponential stability of a compensated tracking error in the sense of Lyapunov. Both the stability analysis and simulation results are included.

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