In this technical note, the sliding-mode control (SMC) problem is investigated for T-S fuzzy-model-based nonlinear Markovian jump singular systems subject to matched/unmatched uncertainties. To accommodate the model characteristics of such a hybrid system, a novel integral-type fuzzy sliding surface is put forward by taking the singular matrix and state-dependent projection matrix into account simultaneously, which is the key contribution of the note. The designed surface contains two important features: 1) local input matrices for different subsystems in the same system mode are allowed to be different; and 2) the matched uncertainties are completely compensated, and the unmatched ones are not amplified during sliding motion. Sufficient conditions for the stochastic admissibility of the corresponding sliding-mode dynamics are presented, and a fuzzy SMC law is constructed to ensure the reaching condition despite uncertainties. The applicability and effectiveness of our approach are verified by simulations on an inverted pendulum system.

This paper addresses the sampled-data stabilization problem for chaotic systems represented by Takagi-Sugeno (T-S) fuzzy models. If the upper bounds for the time derivative of membership functions are available, combining the fuzzy blending for some quadratic functions together with the introduction of some new useful terms, a novel fuzzy time-dependent Lyapunov-Krasovskii functional (LKF) is proposed to fully capture the available characteristics of the actual sampling pattern and membership functions simultaneously. Based on the proposed LKF, a new criterion dependent on the upper bounds for the time derivative of membership functions is presented to guarantee the asymptotic stability of the whole closed-loop system. Moreover, a stability criterion independent of the upper bounds is also provided based on the corresponding common time-dependent LKF. Then, the designed fuzzy sampled-data controller can be synthesized by analyzing the corresponding stabilization conditions. Moreover, a search algorithm is provided to find the optimal tuning parameters. Finally, one practical example of the Lorenz system is given to illustrate that much less conservativeness can be achieved compared with the earlier results by using the corresponding common LKF, and the results can be further improved when adopting the fuzzy time-dependent LKF within large upper bounds.

This brief presents a new guaranteed H performance state estimation criterion for delayed static neural networks. To facilitate the use of the slope information about activation function, the estimation error of activation function is separated into two parts for the first time. Then, a novel Lyapunov-Krasovskii functional (LKF) is constructed, which has fully captured the slope information of the activation. Based on the new LKF, a less conservative design criterion of estimator is derived to ensure the asymptotic stability of estimation error system with H performance. The desired estimator gain matrices and the performance index are obtained by solving a convex optimization problem. The simulation results show that the proposed method has much better performance than the most recent

The problem of station-keeping attitude tracking control for an autonomous airship with system uncertainties and external disturbances is investigated. Adaptive laws are applied to estimate the upper bounds of uncertainties and disturbances, and a nonlinear finite time control scheme is proposed by combing input/output feedback linearization with integral sliding mode technique. Different from the existing works on attitude control of airship, the developed controller can guarantee the yaw, pitch and roll angle trajectories track the desired attitude in finite time in spite of uncertain system uncertainties and external disturbances. Simulation results are provided to illustrate the attitude tracking performance.

Stratospheric airships have much potential in military and commercial applications. Design, analysis and optimization of stratospheric airships involves complex trade-off of different disciplines, and hence a multidisciplinary approach is essential. This paper describes a methodology coupling several disciplines and involving seven design variables to obtain the optimal design of a stratospheric airship powered by solar arrays. A numerical method is established to calculate the output power of the solar array in the optimization process. The optimal solutions are obtained using hybrid algorithms. The methodology can obtain the optimal envelope shape, solar array layout and other general configurations of subsystems. Results show that the methodology was able to achieve a solution with a 19.2% reduction in airship volume compared to the value being part of an arbitrary initial set of airship parameters. In addition, a comparative study is carried out to highlight the importance of considerations of solar array layouts and array circumferential location. Furthermore, detailed sensitivity analysis shows that operating parameters of latitudes, heading angles and average resisting wind speeds have significant effects on the airship design and solar array layouts.