This paper proposes synthesis algorithms for the design of passive state- and output-feedback fault-tolerant controllers. Sufficient conditions for the existence and the construction of such fault-tolerant controllers are given in terms of linear matrix inequalities (LMIs) which can be solved efficiently. The state-feedback fault-tolerant controller consists of a family of state-feedback gains switched appropriately according to a stabilizing switching signal so that the closed-loop system satisfies a performance requirement expressed in terms of system L2 norm. Similarly, the output feedback controller consists of a family of full-order linear, time-invariant controllers switched according to a stabilizing signal that depends only on the controller states. Both approaches are passive in the sense that they do not rely on the detection and/or the estimation of the faults. The proposed approaches are tested on a nonlinear model of a quadcopter. Simulation results show that satisfactory stability, tracking, and disturbance rejection are maintained despite of time-varying actuator faults.

This paper proposes two different ${\mathcal{H}}_2$ -state-feedback controller synthesis algorithms for uncertain linear, time-varying, switched systems. The synthesis algorithms are based on a dwell-time approach, which makes use of time-varying parameter-dependent Lyapunov functions. The control laws consist of state-feedback controllers that are switched according to external signals. The proposed synthesis algorithms are then employed to design switched ${\mathcal{H}}_2$ -state-feedback control laws for the longitudinal dynamics of the ADMIRE fighter benchmark model. The results obtained in simulation show the merits of the proposed approach.

Suspension systems in vehicles are crucial to both ride quality and driving security. The challenge of creating an effective control mechanism for automotive active suspension systems is addressed in this work. In the event of unforeseen road disturbances, the active suspension systems are intended to deliver a more pleasant ride and good handling. Fuzzy-Linear Quadratic Gaussian (FLQG) and Fuzzy-Linear Quadratic Regulator (FLQR) controllers adapting to road disturbances are proposed to enhance vehicle comfort through the reduction of the driver's overall body acceleration. The simulation findings demonstrate that the FLQR and FLQG controllers are efficient in adjusting the automotive suspension configuration under varying road profiles compared to those of the conventional LQR and LQG controllers.

This article addresses the challenge of integrated switched H2 control with disturbance rejection capabilities for switched systems, particularly when external disturbances are present. A novel anti-disturbance switched H2 control strategy is formulated, leveraging estimated disturbance values. The formulation is given in Linear Matrix Inequalities (LMIs), establishing sufficient conditions to ensure H2 performance while maintaining closed-loop stability. To validate the effectiveness of the proposed methodology, it is applied to a practical aero-engine model. Through simulations, it is demonstrated that the closed-loop aero-engine model exhibits remarkable transient performance even in the face of external disturbances. These results underscore the efficacy of the developed approach in enhancing the robustness and performance of switched systems subjected to disturbances. The integration of anti-disturbance capabilities within the H2 control framework offers a promising avenue for addressing real-world control challenges, particularly in systems characterized by switching dynamics and external perturbations.

In this work, a switching linear quadratic integral (LQI) controller based on fuzzy logic is designed for the load-factor tracking problem of high-performance aircraft referred to as the Aero-Data Model in Research Environment (ADMIRE). ADMIRE is a new generation aircraft and has a wide flight operation envelope in terms of altitude and speed. Hence, it is difficult to design a flight controller to achieve a high tracking performance. First, the LQI controller is selected due to good tracking performance and robustness in the model dynamics. Combining switching LQI controller and fuzzy logic improves the transient performance of the closed-loop switched system. The results obtained with the fuzzy switching controller have been compared with the conventional LQI and the switching LQI in terms of robust demand tracking. The simulation results have demonstrated that the fuzzy switching controller is superior to the conventional LQI and switching LQI controllers due to better transient performance and robust stability.