In this paper, an adaptive gain tuning rule is designed for the nonlinear sliding mode speed control(NSMSC) in order to enhance the dynamic performance and the robustness of the permanent magnet assisted synchronous r...In this paper, an adaptive gain tuning rule is designed for the nonlinear sliding mode speed control(NSMSC) in order to enhance the dynamic performance and the robustness of the permanent magnet assisted synchronous reluctance motor(PMa-Syn RM) with considering the parameter uncertainties. A nonlinear sliding surface whose parameters are altering with time is designed at first. The proposed NSMSC can minimize the settling time without any overshoot via utilizing a low damping ratio at starting along with a high damping ratio as the output approaches the target set-point. In addition, it eliminates the problem of the singularity with the upper bound of an uncertain term that is hard to be measured practically as well as ensures a rapid convergence in finite time, through employing a simple adaptation law. Moreover, for enhancing the system efficiency throughout the constant torque region, the control system utilizes the maximum torque per ampere technique. The nonlinear sliding surface stability is assured via employing Lyapunov stability theory. Furthermore, a simple sliding mode estimator is employed for estimating the system uncertainties. The stability analysis and the experimental results indicate the effectiveness along with feasibility of the proposed speed estimation and the NSMSC approach for a 1.1-k W PMa-Syn RM under different speed references, electrical and mechanical parameters disparities, and load disturbance conditions.展开更多
Permanent magnet assisted synchronous reluctance motor(PMA-SynRM)is a kind of high torque density energy conversion device widely used in modern industry.In this paper,based on the basic topology of PMA-SynRM,a novel ...Permanent magnet assisted synchronous reluctance motor(PMA-SynRM)is a kind of high torque density energy conversion device widely used in modern industry.In this paper,based on the basic topology of PMA-SynRM,a novel PMA-SynRM of asymmetric rotor with position-biased magnet is proposed.The asymmetric rotor design with position-biased magnet realizes the concentration of magnetic field lines in the motor air gap to obtain higher electromagnetic torque,and makes both of magnetic and reluctance torque obtain the peak value at the same current phase angle.The asymmetric rotor configuration is theoretically illustrated by space vector diagram,and the feasibility of high torque performance of the motor is verified.Through the finite element simulation,the effect of the side barrier on output torque and the Mises stress under the rotor asymmetrical design are analyzed.Then the motor characteristics including airgap flux density,back EMF,magnetic torque,reluctance torque,torque ripple,losses,and efficiency are calculated for both the basic and proposed PMA-SynRMs.The results show that the proposed PMA-SynRM has higher torque and efficiency than the basic topology.Moreover,the torque ripple of the proposed PMA-SynRM is reduced by the method with harmonic current injection,and the torque characteristics in the whole current cycle are analyzed.Finally,the endurance to avoid PM demagnetization is confirmed based on the PM remanence calculation.展开更多
为了提高伺服电机系统的动态响应速度、抗干扰能力,解决输入饱和的问题,课题组基于扩张状态观测器(extended state observer,ESO)和抗饱和输入(anti-saturation input,ASI)辅助系统设计了伺服电机的运动控制方案。首先,建立了伺服电机...为了提高伺服电机系统的动态响应速度、抗干扰能力,解决输入饱和的问题,课题组基于扩张状态观测器(extended state observer,ESO)和抗饱和输入(anti-saturation input,ASI)辅助系统设计了伺服电机的运动控制方案。首先,建立了伺服电机的数学模型,将系统阻尼和系统不确定性归为扰动,将扰动设为系统的扩张状态;然后在等效反步滑模控制(backstepping sliding mode control,BSMC)的基础上,引入了ASI辅助系统和ESO,解决输入饱和问题,并抑制内、外干扰;采用双曲正切饱和函数替换符号函数以减小滑模控制的抖振;通过李雅普诺夫稳定性方法检验所提出控制器的稳定性。最后,将基于ESO和ASI的等效反步滑模控制与比例积分微分(proportional integral differential,PID)控制、滑模控制(sliding mode control,SMC)进行仿真对比。结果表明:相较于传统PID和SMC控制器,课题组所设计的控制器可以实现伺服电机的无超调快速响应,解决了输入饱和问题,并具有较好的抗干扰能力和减小输入冲击的作用。展开更多
Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligen...Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence.展开更多
文摘In this paper, an adaptive gain tuning rule is designed for the nonlinear sliding mode speed control(NSMSC) in order to enhance the dynamic performance and the robustness of the permanent magnet assisted synchronous reluctance motor(PMa-Syn RM) with considering the parameter uncertainties. A nonlinear sliding surface whose parameters are altering with time is designed at first. The proposed NSMSC can minimize the settling time without any overshoot via utilizing a low damping ratio at starting along with a high damping ratio as the output approaches the target set-point. In addition, it eliminates the problem of the singularity with the upper bound of an uncertain term that is hard to be measured practically as well as ensures a rapid convergence in finite time, through employing a simple adaptation law. Moreover, for enhancing the system efficiency throughout the constant torque region, the control system utilizes the maximum torque per ampere technique. The nonlinear sliding surface stability is assured via employing Lyapunov stability theory. Furthermore, a simple sliding mode estimator is employed for estimating the system uncertainties. The stability analysis and the experimental results indicate the effectiveness along with feasibility of the proposed speed estimation and the NSMSC approach for a 1.1-k W PMa-Syn RM under different speed references, electrical and mechanical parameters disparities, and load disturbance conditions.
基金supported in part by the National Natural Science Foundation of China under Grant 52077123 and 51737008in part by the Natural Science Foundation of Shandong Province of China for Outstanding Young Scholars,under Grant ZR2021YQ35。
文摘Permanent magnet assisted synchronous reluctance motor(PMA-SynRM)is a kind of high torque density energy conversion device widely used in modern industry.In this paper,based on the basic topology of PMA-SynRM,a novel PMA-SynRM of asymmetric rotor with position-biased magnet is proposed.The asymmetric rotor design with position-biased magnet realizes the concentration of magnetic field lines in the motor air gap to obtain higher electromagnetic torque,and makes both of magnetic and reluctance torque obtain the peak value at the same current phase angle.The asymmetric rotor configuration is theoretically illustrated by space vector diagram,and the feasibility of high torque performance of the motor is verified.Through the finite element simulation,the effect of the side barrier on output torque and the Mises stress under the rotor asymmetrical design are analyzed.Then the motor characteristics including airgap flux density,back EMF,magnetic torque,reluctance torque,torque ripple,losses,and efficiency are calculated for both the basic and proposed PMA-SynRMs.The results show that the proposed PMA-SynRM has higher torque and efficiency than the basic topology.Moreover,the torque ripple of the proposed PMA-SynRM is reduced by the method with harmonic current injection,and the torque characteristics in the whole current cycle are analyzed.Finally,the endurance to avoid PM demagnetization is confirmed based on the PM remanence calculation.
文摘Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence.
