The assembly error of flexible joints and the change in joint stiffness during movement make the actual value of joint parameters inconsistent with the given value, which affects the joint control accuracy. In order to suppress the influence of parameters error, a parameters identification method for flexible joint combined offline identification and online compensation is proposed. First, the offline identification model of inertia, mass, and damping and the online identification model of joint stiffness are established, respectively. Then, a hybrid tracking differentiator based on an improved Sigmoid function is designed to track the differential signals of joint motion parameters, and the Lyapunov function is designed to prove its convergence. The adaptive differential evolution is used as the identification algorithm, and the improved adaptive crossover, mutation factor, and Metropolis acceptance criterion are designed to improve the convergence speed. Finally, a feedforward control structure based on identification is designed to compensate for the model deviation. Simulation and experimental results show that the improved differentiator can effectively improve the tracking speed and derivation accuracy of the signals. Compared with other algorithms, the proposed identification method has a faster convergence speed and higher identification accuracy, and feedforward compensation control can effectively correct model parameters and improve control accuracy.
Extrusion has become one of the most popular techniques in food processing, and the process parameters are closely related to product quality. Purslane (Portulaca oleracea L.) can be used in medical and food products as a vegetable and herb. It has limited application in extrusion. The effects of extrusion process variables (screw speed, barrel temperature, and feed moisture) on system variables (specific mechanical energy [SME], die head pressure, and torque) and target variables (water absorption index, water solubility index, iodine blue value, color, pasting properties, and textural properties) of purslane powder compound rice were studied. The results showed that SME was moderately positively correlated with screw speed (r = 0.608, p < 0.05). However, torque was moderately negatively correlated with feed moisture (r = −0.574, p < 0.05), and die head pressure was moderately negatively correlated with barrel temperature (r = −0.635, p < 0.01). The target variables of extrudates were also correlated with the system parameters to varying degrees. These results are helpful to control and predict the texture, pasting properties, and other quality characteristics of extruded products containing purslane powder.
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