<p>Mobile manipulators are time-varying, strongly coupled, nonlinear dynamical systems that are extremely susceptible to outside interference and system uncertainties. The position/force control problem of constrained mobile manipulators with time-varying disturbances and uncertainties in the system is addressed in this study. The design of the position/force control scheme first introduces a fractional-order sliding manifold, which guarantees a faster and fixed-time convergence of tracking errors with a precise assessment of the stopping time for the closed-loop dynamical system. Based on the fractional-order sliding manifold, a robust fixed-time fractional-order hybrid control scheme is proposed for position/force control of constrained mobile manipulators. The radial basis function neural network is employed in the proposed controller to approximate the nonlinear coupled states of the dynamics of the mobile manipulator system. A fast terminal sliding mode type reaching law is adopted for the faster response of system states toward their equilibrium points. The Lyapunov method and fractional-order Barbalat’s lemma are applied to examine the stability of the closed-loop system, and the weight matrices that make up the neural network’s structure are updated online. A numerical simulation investigation is carried out to demonstrate the superiority of the proposed control strategy over comparable ones that exist in the literature. Consequently, the robust position/force tracking control of the system’s states has been achieved and the tracking performance of the mobile manipulator is improved by the proposed control approach.</p>