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In this article, a tracking controller for flexible-joint robot manipulators with non-full-state feedback is investigated based on virtual decomposition control (VDC) theory. First, virtual decomposition principle is applied to decouple the entire system of flexible-joint robot manipulator into rigid-link subsystems and flexible-joint subsystems; then, subcontrollers are designed correspondingly for each link or joint subsystem. Importantly, to realize the closed-loop tracking control without state measurements on the link side, an extended Kalman filter is designed to achieve the proposed VDC approach via non-full-state feedback. In addition, strict stability analysis of the control system is given according to the theory of virtual stability and Lyapunov stability. Finally, validation example is provided to verify the proposed control approach.

This paper concerns the problem of dynamic parameter identification of robot manipulators and proposes a closed-loop identification procedure using modified Fourier series (MFS) as exciting trajectories. First, a static continuous friction model is involved to model joint friction for realizable friction compensation in controller design. Second, MFS satisfying the boundary conditions are firstly designed as periodic exciting trajectories. To minimize the sensitivity to measurement noise, the coefficients of MFS are optimized according to the condition number criterion. Moreover, to obtain accurate parameter estimates, the maximum likelihood estimation (MLE) method considering the influence of measurement noise is adopted. The proposed identification procedure has been implemented on the first three axes of the QIANJIANG-I 6-DOF robot manipulator. Experiment results verify the effectiveness of the proposed approach, and comparison between identification using MFS and that using finite Fourier series (FFS) reveals that the proposed method achieves better identification accuracy.

The duct of a robot vacuum cleaner is the length of the flow channel between the inlet of the rolling brush blower and the outlet of the vacuum blower. To cope with the pressure drop problem of the duct flow field in a robot vacuum cleaner, a method based on Pressure Implicit with Splitting of Operators (PRISO) algorithm is introduced and the optimisation design of the duct flow field is implemented. Firstly, the duct structure in a robot vacuum cleaner is taken as a research object, with the computational fluid dynamics (CFD) theories adopted; a three‐dimensional fluid model of the duct is established by means of the FLUENT solver of the CFD software. Secondly, with the k‐ε turbulence model of three‐ dimensional incompressible fluid considered and the PRISO pressure modification algorithm employed, the flow field numerical simulations inside the duct of the robot vacuum cleaner are carried out. Then, the velocity vector plots on the arbitrary plane of the duct flow field are obtained. Finally, an investigation of the dynamic characteristics of the duct flow field is done and defects of the original duct flow field are analysed, the optimisation of the original flow field has then been conducted. Experimental results show that the duct flow field after optimisation can effectively reduce pressure drop, the feasibility as well as the correctness of the theoretical modelling and optimisation approaches are validated.

To deal with the problem of the output feedback tracking (OFT) control with bounded torque inputs of robot manipulators, we propose a generalized fuzzy saturated OFT controller based on singular perturbation theory. First, considering the fact that the output toque of joint actuators is limited, a general expression for a class of saturation functions is given to be applied in the control law. Second, to carry out the whole closed-loop control with only position measurements, linear and nonlinear filters are optionally involved to generate a pseudo signal to surrogate the actual velocity tracking error. As a third contribution, a fuzzy regulator is added to obtain a self-tuning performance in tackling the disturbances. Moreover, an explicit but strict stability proof of the system based on the stability theory of singularly perturbed systems is presented. Finally, numerical simulations on several sample controllers are implemented to verify the effectiveness of the proposed approach.