Conventional open-loop deep brain stimulation(DBS)systems with fixed parameters fail to accommodate interindividual pathological differences in Parkinson's disease(PD)management while potentially inducing adverse ...Conventional open-loop deep brain stimulation(DBS)systems with fixed parameters fail to accommodate interindividual pathological differences in Parkinson's disease(PD)management while potentially inducing adverse effects and causing excessive energy consumption.In this paper,we present an adaptive closed-loop framework integrating a Yogi-optimized proportional–integral–derivative neural network(Yogi-PIDNN)controller.The Yogi-augmented gradient adaptation mechanism accelerates the convergence of general PIDNN controllers in high-dimensional nonlinear control systems while reducing control energy usage.In addition,a system identification method establishes input–output dynamics for pre-training stimulation waveforms,bypassing real-time parameter-tuning constraints and thereby enhancing closed-loop adaptability.Finally,a theoretical analysis based on Lyapunov stability criteria establishes a sufficient condition for closed-loop stability within the identified model.Computational validations demonstrate that our approach restores thalamic relay reliability while reducing energy consumption by(81.0±0.7)%across multi-frequency tests.This study advances adaptive neuromodulation by synergizing data-driven pre-training with stability-guaranteed real-time control,offering a novel framework for energy-efficient and personalized Parkinson's therapy.展开更多
A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of ind...A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.展开更多
The paper describes a closed-loop system identification procedure for hybrid continuous-time Box–Jenkins models and demonstrates how it can be used for IMC based PID controller tuning. An instrumental variable algori...The paper describes a closed-loop system identification procedure for hybrid continuous-time Box–Jenkins models and demonstrates how it can be used for IMC based PID controller tuning. An instrumental variable algorithm is used to identify hybrid continuous-time transfer function models of the Box–Jenkins form from discretetime prefiltered data, where the process model is a continuous-time transfer function, while the noise is represented as a discrete-time ARMA process. A novel penalized maximum-likelihood approach is used for estimating the discrete-time ARMA process and a circulatory noise elimination identification method is employed to estimate process model. The input–output data of a process are affected by additive circulatory noise in a closedloop. The noise-free input–output data of the process are obtained using the proposed method by removing these circulatory noise components. The process model can be achieved by using instrumental variable estimation method with prefiltered noise-free input–output data. The performance of the proposed hybrid parameter estimation scheme is evaluated by the Monte Carlo simulation analysis. Simulation results illustrate the efficacy of the proposed procedure. The methodology has been successfully applied in tuning of IMC based flow controller and a practical application demonstrates the applicability of the algorithm.展开更多
尽管比例−积分−微分(Proportional Integral Derivative,PID)控制算法被广泛应用在双电机差速小车控制当中,但是PID参数的整定过程一直是一个繁琐的过程。为了简化这一过程,文章基于双电机差速小车的传递函数模型,通过灰狼算法自动调节...尽管比例−积分−微分(Proportional Integral Derivative,PID)控制算法被广泛应用在双电机差速小车控制当中,但是PID参数的整定过程一直是一个繁琐的过程。为了简化这一过程,文章基于双电机差速小车的传递函数模型,通过灰狼算法自动调节PID控制器的参数。仿真展示了双电机差速小车的巡线结果,并对比了四种人工智能优化算法,进一步展示了灰狼算法(Grey Wolf Optimizer,GWO)在整定PID控制器参数时的有效性。展开更多
针对开关磁阻电机PID(Proportional Integral Derivative)控制中存在的稳定性差、参数调节困难等问题,文中基于传统开关磁阻电机PID调速系统引入鲸鱼优化算法,将改进时间绝对误差函数作为适应度函数对K_(p)、K_(i)、K_(d)这3个控制参数...针对开关磁阻电机PID(Proportional Integral Derivative)控制中存在的稳定性差、参数调节困难等问题,文中基于传统开关磁阻电机PID调速系统引入鲸鱼优化算法,将改进时间绝对误差函数作为适应度函数对K_(p)、K_(i)、K_(d)这3个控制参数进行整定。在MATLAB/Simulink仿真平台搭建了三相6/4极开关磁阻电机的PID参数整定系统,分析了传统经验PID调参和算法整定参数的效果对比,并将鲸鱼算法的优化效果与粒子群算法、遗传算法和灰狼优化算法结果进行对比。仿真结果表明,所提方法获得的PID参数较精确,其效果优于3种对比算法。相比于经验法整定参数,鲸鱼算法整定参数响应速度提升了51.10%,误差减小了0.67%,使调速系统具有更快、更稳定的响应特性。展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12372064 and 12172291)the Youth and Middle-Aged Science and Technology Development Program of Shanghai Institute of Technology(Grant No.ZQ2024-10)。
文摘Conventional open-loop deep brain stimulation(DBS)systems with fixed parameters fail to accommodate interindividual pathological differences in Parkinson's disease(PD)management while potentially inducing adverse effects and causing excessive energy consumption.In this paper,we present an adaptive closed-loop framework integrating a Yogi-optimized proportional–integral–derivative neural network(Yogi-PIDNN)controller.The Yogi-augmented gradient adaptation mechanism accelerates the convergence of general PIDNN controllers in high-dimensional nonlinear control systems while reducing control energy usage.In addition,a system identification method establishes input–output dynamics for pre-training stimulation waveforms,bypassing real-time parameter-tuning constraints and thereby enhancing closed-loop adaptability.Finally,a theoretical analysis based on Lyapunov stability criteria establishes a sufficient condition for closed-loop stability within the identified model.Computational validations demonstrate that our approach restores thalamic relay reliability while reducing energy consumption by(81.0±0.7)%across multi-frequency tests.This study advances adaptive neuromodulation by synergizing data-driven pre-training with stability-guaranteed real-time control,offering a novel framework for energy-efficient and personalized Parkinson's therapy.
文摘A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.
基金Supported by the National Natural Science Foundation of China(61573052,61174128)
文摘The paper describes a closed-loop system identification procedure for hybrid continuous-time Box–Jenkins models and demonstrates how it can be used for IMC based PID controller tuning. An instrumental variable algorithm is used to identify hybrid continuous-time transfer function models of the Box–Jenkins form from discretetime prefiltered data, where the process model is a continuous-time transfer function, while the noise is represented as a discrete-time ARMA process. A novel penalized maximum-likelihood approach is used for estimating the discrete-time ARMA process and a circulatory noise elimination identification method is employed to estimate process model. The input–output data of a process are affected by additive circulatory noise in a closedloop. The noise-free input–output data of the process are obtained using the proposed method by removing these circulatory noise components. The process model can be achieved by using instrumental variable estimation method with prefiltered noise-free input–output data. The performance of the proposed hybrid parameter estimation scheme is evaluated by the Monte Carlo simulation analysis. Simulation results illustrate the efficacy of the proposed procedure. The methodology has been successfully applied in tuning of IMC based flow controller and a practical application demonstrates the applicability of the algorithm.
文摘尽管比例−积分−微分(Proportional Integral Derivative,PID)控制算法被广泛应用在双电机差速小车控制当中,但是PID参数的整定过程一直是一个繁琐的过程。为了简化这一过程,文章基于双电机差速小车的传递函数模型,通过灰狼算法自动调节PID控制器的参数。仿真展示了双电机差速小车的巡线结果,并对比了四种人工智能优化算法,进一步展示了灰狼算法(Grey Wolf Optimizer,GWO)在整定PID控制器参数时的有效性。
文摘针对开关磁阻电机PID(Proportional Integral Derivative)控制中存在的稳定性差、参数调节困难等问题,文中基于传统开关磁阻电机PID调速系统引入鲸鱼优化算法,将改进时间绝对误差函数作为适应度函数对K_(p)、K_(i)、K_(d)这3个控制参数进行整定。在MATLAB/Simulink仿真平台搭建了三相6/4极开关磁阻电机的PID参数整定系统,分析了传统经验PID调参和算法整定参数的效果对比,并将鲸鱼算法的优化效果与粒子群算法、遗传算法和灰狼优化算法结果进行对比。仿真结果表明,所提方法获得的PID参数较精确,其效果优于3种对比算法。相比于经验法整定参数,鲸鱼算法整定参数响应速度提升了51.10%,误差减小了0.67%,使调速系统具有更快、更稳定的响应特性。
