This paper primarily investigates the event-triggered tracking control problem for quadcopter attitude systems, utilizing finite-time zero compensation technology. Unlike existing research results, a zero compensation technology is proposed to solve non-affine control input problems such as saturation, dead zones, and gaps. The command filtered compensation technology is used to solve ’differential explosion’ and filtering errors. A novel Tanh type filter and a neural network are employed to approximate virtual control signals and account for un-modeled dynamics, respectively. Moreover, the finite-time convergence theory is used to prove that the state, tracking error, and filtered error compensation signals in the entire closed-loop system converge to an arbitrarily small neighborhood of the equilibrium origin. Finally, the advantages of the proposed control algorithm in improving tracking accuracy and reducing communication load were demonstrated through simulation.
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