A Systematic Approach to Fuzzy-model-based Robust $$H_\infty$$ H ∞ Control Design for a Quadrotor UAV Under Imperfect Premise Matching

Sampled‐data control of fuzzy systems based on the intelligent digital redesign method via an improved fuzzy Lyapunov functional approach

“…The above non‐linear model can be represented as the following T–S fuzzy model [27]: on a compact set , where , …”

“…Using the continuous‐time disturbance attenuation control method given in [27], we have the continuous‐time gain matrices (see (70)).…”

Interval type‐2 fuzzy‐model‐based fault‐tolerant sliding mode tracking control of a quadrotor UAV under actuator saturation

“…The special structure of a quadrotor has a wide range of advantages in that they are easy to manoeuvre and have the abilities to hovering, vertical takeoff and landing (VTOL), and other features not found in fixed‐wing aircraft. With these advantages, many studies on the quadrotor UAV have been actively conducted and a field of researches can be classified as localisation [2], navigation [3], controller design [4–18], and others. However, the dynamics of the quadorotor UAV is not only highly non‐linear but also underactuated, which makes the controller design complex.…”

“…From a controller design point of view, linear or non‐linear control theories have been applied, such as proportional–integral–derivative (PID) control [4], linear quadratic regulator (LQR) control [5], back stepping control [6, 7], adaptive control [8, 9], and linear matrix inequality (LMI)‐based control approaches [11–18]. The existing methods, however, have the following limitations: the linear control methods such as PID or LQR are easily applicable, but due to the characteristics of the quadrotor with highly non‐linear dynamics, only the control performance in the hovering state can be guaranteed.…”

Disturbance observer‐based integral fuzzy sliding‐mode control and its application to wind turbine system

“…However, if the T–S fuzzy model membership functions are complicated, the hardware cost of the fuzzy controller membership functions will increase. To solve such a problem, an imperfect premise matching [24–26] condition was proposed. Under such a condition, the design flexibility in choosing the membership functions is increased.…”