<p>This work deals with the tracking issue for multi-input multi-output flexible-joint manipulator systems with stochastic noise and performance constraints. By combining the speed function with the neural network control method, an accelerated fixed-time control has been developed that exhibits several attractive features: (1) the proposed fixed-time control scheme has been custom-designed for multi-input multi-output flexible-joint manipulator systems to eliminate the influence of initial conditions on the tracking performance of the manipulator; (2) the phenomenon of the complexity explosion is effectively avoided by employing command filters, thereby significantly enhancing computational efficiency of flexible-joint manipulator systems; (3) prescribed performance control is employed to ensure that the tracking error of link position in the flexible-joint manipulator is strictly confined within predefined boundaries; (4) the introduction of the speed function <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\beta \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>β</mi> </math></EquationSource> </InlineEquation> enables each component of the manipulator to converge according to a predefined pattern and speed before entering the residual region. Finally, numerical simulations and physical experiments conducted on the Quanser flexible-joint manipulator platform validate the efficacy of the proposed approach.</p>