Research on Visual Servo Grasping of Household Objects for Nonholonomic Mobile Manipulator

This paper focuses on the problem of visual servo grasping of household objects for nonholonomic mobile manipulator. Firstly, a new kind of artificial object mark based on QR (Quick Response) Code is designed, which can be affixed to the surface of household objects. Secondly, after summarizing the vision-based autonomous mobile manipulation system as a generalized manipulator, the generalized manipulator’s kinematic model is established, the analytical inverse kinematic solutions of the generalized manipulator are acquired, and a novel active vision based camera calibration method is proposed to determine the hand-eye relationship. Finally, a visual servo switching control law is designed to control the service robot to finish object grasping operation. Experimental results show that QR Code-based artificial object mark can overcome the difficulties brought by household objects’ variety and operation complexity, and the proposed visual servo scheme makes it possible for service robot to grasp and deliver objects efficiently

Research on Improved Deadbeat Control Strategy Based on Interpolation Prediction and Online Inductance Identification

Aiming at the problem of control delay and inductance deviation, which exist in the traditional deadbeat control of the full-bridge circuit, an improved deadbeat control strategy was proposed. An improved Newton interpolation prediction algorithm was proposed to compensate the delay problem of deadbeat control, and an on-line inductance identification algorithm based on double frequency sampling was proposed to correct the inductance deviation. A mathematical model of deadbeat control for full-bridge inverter was established; besides, the performance of different interpolation prediction algorithms was analyzed. An online inductor identification model is established, on the basis of which the online inductance identification compensation formula is derived. It is indicated that an output constant current of 10 A is available with the deadbeat control relative error of only 0.2%, the grid-connected power factor up to 0.999, and the output current’s total harmonic distortion of only 2.37%. The prototype experiment shows that the output current’s total harmonic distortion is as low as 2.403% and the power factor is as high as 0.998. The results show that the improved deadbeat control strategy can effectively improve the control accuracy and the quality of grid-connected power

Resonant Power Supply for Plasma Cleaning Based on Fuzzy Logic Power Tracking

The coaxial cylindrical reactor with a rotary nozzle is proposed to be used as the plasma torch of the plasma cleaning machine. The phase-shifted full bridge series resonance circuit is used as the power circuit topology. Because the voltage source load resonance circuit technology is mature, the cycle and difficulty of research and development on this basis are relatively small, and the corresponding control strategy and algorithm are relatively easy to achieve. At the same time, the voltage source circuit is smaller than the current source circuit, in line with the development trend of plasma cleaning equipment. In this paper, based on the phase shift full bridge series resonant circuit, the control strategy is compared and analyzed. Considering the response speed, control precision and efficiency, a PSPWM-PFM (Phase Shift Pulse Width Modulation- Pulse Frequency Modulation) hybrid modulation control strategy is proposed, which makes the system not only have a fast response speed but can also construct a soft switch and has a high efficiency. A maximum power tracking algorithm based on a fuzzy PFM was proposed to solve the problem that the plasma power supply deviated from the resonant frequency point easily due to environmental perturbation, and thus deviated from the maximum power point

Energy-Feedback Load Simulation Algorithm Based on Fuzzy Control

In order to solve the problem that the traditional Proportional Integral (PI) controller cannot take into account both response speed and input current overshoot and cannot adapt to complex working conditions, an energy-feedback DC load simulation control algorithm based on fuzzy control was proposed. By adding a fuzzy adaptive PI setting to the traditional load simulation control algorithm, the dynamic response performance of the system and the accuracy of load simulation were improved. A small-signal model of a load analog boost circuit was established based on the state average method. Based on the phase margin, the PI parameter setting of series correction was completed, and the corresponding fuzzy control rules were formulated to identify the response state. Simulation results show that the regulation time of constant current load simulation based on a fuzzy control strategy is shortened by 75.2%, the steady-state error is reduced by 60%, and the overshoot is reduced from 28.3% to 7.47%. The prototype test results show that the maximum relative error of input current load simulation is only 4.50%, and the system response speed can meet the requirements of variable load simulation. The results show that the load simulation control algorithm based on fuzzy control has the characteristics of high precision and excellent dynamic characteristics

Energy-Feedback Load Simulation Algorithm Based on Fuzzy Control

In order to solve the problem that the traditional Proportional Integral (PI) controller cannot take into account both response speed and input current overshoot and cannot adapt to complex working conditions, an energy-feedback DC load simulation control algorithm based on fuzzy control was proposed. By adding a fuzzy adaptive PI setting to the traditional load simulation control algorithm, the dynamic response performance of the system and the accuracy of load simulation were improved. A small-signal model of a load analog boost circuit was established based on the state average method. Based on the phase margin, the PI parameter setting of series correction was completed, and the corresponding fuzzy control rules were formulated to identify the response state. Simulation results show that the regulation time of constant current load simulation based on a fuzzy control strategy is shortened by 75.2%, the steady-state error is reduced by 60%, and the overshoot is reduced from 28.3% to 7.47%. The prototype test results show that the maximum relative error of input current load simulation is only 4.50%, and the system response speed can meet the requirements of variable load simulation. The results show that the load simulation control algorithm based on fuzzy control has the characteristics of high precision and excellent dynamic characteristics