The proportional-integral-derivative (PID) controller parameters tuning is critical for improving the performance of permanent magnet synchronous motor (PMSM) systems. To improve the performance of particle swarm opti...
The proportional-integral-derivative (PID) controller parameters tuning is critical for improving the performance of permanent magnet synchronous motor (PMSM) systems. To improve the performance of particle swarm optimization (PSO) in the PID parameters tuning, the chaos particle swarm optimization (CPSO) is adopted to tune PI parameters in this work. The PMSM vector control system is selected as the research object, and its speed loop PI controller using CPSO algorithm is implemented. The optimal PI controller parameters are obtained using the CPSO algorithm with ten iterations. The simulation is conducted using MATlab/Simulink to evaluate to the PI controller performance. Four performance indicators including overshoot, rise time, peak time and ITAE are used to evaluate the PI controller with CPSO, and the results suggest that the CPSO algorithm has better performance and stability compared with other tuning methods.
In this work, we present a Long Short-Term Memory Model (LSTMM) for gait phase classification based on sEMG signals to control the lower limb exoskeleton robot which can recognize 2 phases (Stand and Swing) of leg pha...
In this work, we present a Long Short-Term Memory Model (LSTMM) for gait phase classification based on sEMG signals to control the lower limb exoskeleton robot which can recognize 2 phases (Stand and Swing) of leg phases between the foot and ground. This model only needs four sEMG signals to control the lower limb exoskeleton robot helping the hemiplegia patient walking. Compared with the existing methods, the proposed model not only avoids the complex sensor systems but also enhances the accuracy of gait phase classification. The experimental results first verify the availability of sEMG data acquisition system on the lower limb exoskeleton robot made by the Shenzhen Institutes of advanced Technologies (SIAT) by quantify the system with gold standard optoelectronic system Vicon, then show that the proposed LSTMM is significantly higher on prediction accuracy and has better robustness for gait phase classification to control the lower limb exoskeleton robot with different speeds. Finally, the maximum accuracy of LSTMM on the gait phase classification is 97.89%.
In this article, after introducing the RoboWalk body weight support assistive device, the forward kinematics of human and the inverse kinematics of the assistive robot are introduced. Then, a method for obtaining an a...
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ISBN:
(纸本)9781728101286;9781728101279
In this article, after introducing the RoboWalk body weight support assistive device, the forward kinematics of human and the inverse kinematics of the assistive robot are introduced. Then, a method for obtaining an analytical dynamics of the system is presented. This method is based on modeling the human body without modeling its constraints and contact forces. Then, the contact forces are taken into account and mapped into joint space of the robot using the jacobian matrices of interaction points. This method of modeling is then compared and verified by the numerical Recursive Newton Euler Algorithm. Since the numerical method is more efficient and has less computational complexities, it can be used in implementing the control algorithms on the robot. After the model is verified, a control strategy for assisting the user is designed and implemented on the developed model of RoboWalk. The performance of this control strategy is evaluated by comparing the floor reaction force and user joint torques if using Robowalk or not. Finally, the actuator's specification to fulfill our requirements is discussed.
This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of he...
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Humanity has long sought inspiration from nature to innovate materials and devices. As science advances, nature-inspired materials are becoming part of our lives. Animate materials, characterized by their activity, ad...
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The sliding mode observer (SMO) can effectively achieve the permanent magnet synchronous motor (PMSM) to perform position sensorless control, but there are still drawbacks of system chattering and high complexity. In ...
The sliding mode observer (SMO) can effectively achieve the permanent magnet synchronous motor (PMSM) to perform position sensorless control, but there are still drawbacks of system chattering and high complexity. In this paper, an improved SMO is established based on hyperbolic tangent function and Kalman filter. The system chattering is effectively suppressed, and the accuracy of position and speed observation error is significantly improved without phase compensation. It is found that the convergence rate of the hyperbolic tangent function has a strong correlation with the system chattering degree and the speed observation error. When a is between 3 and 4, the speed error accuracy of the improved SMO is the optimum situation.
In order to improve the control precision of permanent magnet synchronous motor servo drive, a Proportional-Integral-Differential (PID) control method based on particle swarm optimization (PSO) algorithm is proposed. ...
In order to improve the control precision of permanent magnet synchronous motor servo drive, a Proportional-Integral-Differential (PID) control method based on particle swarm optimization (PSO) algorithm is proposed. Firstly, the mathematical model of the permanent magnet synchronous motor was established. Then the PSO algorithm was used to adjust the parameters of the PID controller. Finally, the simulation experiment was carried out under the MATlab/Simulink environment to test its performance. Compared with the traditional manual parameters tuning, the PID controller based on PSO algorithm had better performance and better stability.
Rearranging objects on a tabletop surface by means of nonprehensile manipulation is a task which requires skillful interaction with the physical world. Usually, this is achieved by precisely modeling physical properti...
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Atomic force microscopy(AFM) is originally used to observe the sample surface,and then extended to the area of *** can be quite valuable in the further study of maneuvering *** of the influence of the tip morphology o...
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ISBN:
(纸本)9781538629185
Atomic force microscopy(AFM) is originally used to observe the sample surface,and then extended to the area of *** can be quite valuable in the further study of maneuvering *** of the influence of the tip morphology on the tip pushing direction,it is difficult to establish an effective operating model for stably manipulating nanoparticles with controllable manipulation *** resolve this problem,the acting force of manipulating the nano-particle is analyzed firstly based on the least action *** the influence of the contact point between the nano-particle and the tip is taken into account on the pushing direction,and manipulation of the nano-particle is modeled to predict its position after ***,the model parameter is calibrated through several ***,the proposed model is verified by assembling the *** experimental results illustrate that the model can effectively predict the nano-particle position after maneuvering,and can improve the manipulation efficiency.
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