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
The water medium hydraulic retarder is the latest type of auxiliary braking device and has the characteristics of high power density,large braking torque,and compact structure.During traveling,this device can convert ...The water medium hydraulic retarder is the latest type of auxiliary braking device and has the characteristics of high power density,large braking torque,and compact structure.During traveling,this device can convert the kinetic energy of a vehicle to the heat energy of the cooling liquid and replace the service brake under non-emergency braking conditions.With regard to the constant-speed function of the water medium hydraulic retarder,this study designs a controller based on the neural network proportional-integral-derivative(PID)algorithm to achieve the steady traveling of the vehicle at constant velocity during a downhill course by controlling the filling ratio of the water medium hydraulic retarder.To validate the algorithm’s effectiveness,the dynamic model of the heavy-duty vehicle in the downhill process and the physical model of the water medium hydraulic retarder are developed.Three operating conditions,including a fixed slope,step-changing slope,and continuous changing slope,are set,and a simulation test is carried out in the MATLAB/Simulink environment.The neural network PID algorithm has better adaptability in controlling than the traditional PID algorithm.Thus,it controls the water medium hydraulic retarder such that the braking requirements of heavy-duty vehicles under a changing slope working condi-tion are satisfied,and it performs constant-speed control when the vehicle travels downhill.Therefore,the proposed control method can significantly improve the safety of road traffic.展开更多
The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise m...The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise mathemati- cal model for control. So, a new method for establishing a hydraulic roll bending control system is put forward by cerebellar model articulation controller （CMAC） neural network and proportional-integral-derivative （PID） coupling control strategy. The non-linear relationship between input and output can be achieved by the concept mapping and the actual mapping of CMAC. The simulation results show that, compared with the conventional PID control algo- rithm, the parallel control algorithm can overcome the influence of parameter change of roll bending system on the control performance, thus improve the anti jamming capability of the system greatly, reduce the dependence of con- trol performance on the accuracy of the analytical model, enhance the tracking performance of hydraulic roll bending loop for the hydraulic and roll bending force and increase system response speed. The results indicate that the CMAC-P1D coupling control strategy for hydraulic roll bending system is effective.展开更多
A decentralized PID neural network(PIDNN) control scheme was proposed to a quadrotor helicopter subjected to wind disturbance. First, the dynamic model that considered the effect of wind disturbance was established vi...A decentralized PID neural network(PIDNN) control scheme was proposed to a quadrotor helicopter subjected to wind disturbance. First, the dynamic model that considered the effect of wind disturbance was established via Newton-Euler formalism.For quadrotor helicopter flying at low altitude in actual situation, it was more susceptible to be influenced by the turbulent wind field.Therefore, the turbulent wind field was generated according to Dryden model and taken into consideration as the disturbance source of quadrotor helicopter. Then, a nested loop control approach was proposed for the stabilization and navigation problems of the quadrotor subjected to wind disturbance. A decentralized PIDNN controller was designed for the inner loop to stabilize the attitude angle. A conventional PID controller was used for the outer loop in order to generate the reference path to inner loop. Moreover, the connective weights of the PIDNN were trained on-line by error back-propagation method. Furthermore, the initial connective weights were identified according to the principle of PID control theory and the appropriate learning rate was selected by discrete Lyapunov theory in order to ensure the stability. Finally, the simulation results demonstrate that the controller can effectively resist external wind disturbances, and presents good stability, maneuverability and robustness.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.
基金funded by The National Key R&D Program of China(2016YFB0101402).
文摘The water medium hydraulic retarder is the latest type of auxiliary braking device and has the characteristics of high power density,large braking torque,and compact structure.During traveling,this device can convert the kinetic energy of a vehicle to the heat energy of the cooling liquid and replace the service brake under non-emergency braking conditions.With regard to the constant-speed function of the water medium hydraulic retarder,this study designs a controller based on the neural network proportional-integral-derivative(PID)algorithm to achieve the steady traveling of the vehicle at constant velocity during a downhill course by controlling the filling ratio of the water medium hydraulic retarder.To validate the algorithm’s effectiveness,the dynamic model of the heavy-duty vehicle in the downhill process and the physical model of the water medium hydraulic retarder are developed.Three operating conditions,including a fixed slope,step-changing slope,and continuous changing slope,are set,and a simulation test is carried out in the MATLAB/Simulink environment.The neural network PID algorithm has better adaptability in controlling than the traditional PID algorithm.Thus,it controls the water medium hydraulic retarder such that the braking requirements of heavy-duty vehicles under a changing slope working condi-tion are satisfied,and it performs constant-speed control when the vehicle travels downhill.Therefore,the proposed control method can significantly improve the safety of road traffic.
基金Item Sponsored by National High-Tech Research and Development Program(863Program)of China(2009AA04Z143)Natural Science Foundation of Hebei Province of China(E2006001038)Hebei Provincial Science and Technology Project of China(10212101D)
文摘The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise mathemati- cal model for control. So, a new method for establishing a hydraulic roll bending control system is put forward by cerebellar model articulation controller （CMAC） neural network and proportional-integral-derivative （PID） coupling control strategy. The non-linear relationship between input and output can be achieved by the concept mapping and the actual mapping of CMAC. The simulation results show that, compared with the conventional PID control algo- rithm, the parallel control algorithm can overcome the influence of parameter change of roll bending system on the control performance, thus improve the anti jamming capability of the system greatly, reduce the dependence of con- trol performance on the accuracy of the analytical model, enhance the tracking performance of hydraulic roll bending loop for the hydraulic and roll bending force and increase system response speed. The results indicate that the CMAC-P1D coupling control strategy for hydraulic roll bending system is effective.
基金Project(2011ZA51001)supported by National Aerospace Science Foundation of China
文摘A decentralized PID neural network(PIDNN) control scheme was proposed to a quadrotor helicopter subjected to wind disturbance. First, the dynamic model that considered the effect of wind disturbance was established via Newton-Euler formalism.For quadrotor helicopter flying at low altitude in actual situation, it was more susceptible to be influenced by the turbulent wind field.Therefore, the turbulent wind field was generated according to Dryden model and taken into consideration as the disturbance source of quadrotor helicopter. Then, a nested loop control approach was proposed for the stabilization and navigation problems of the quadrotor subjected to wind disturbance. A decentralized PIDNN controller was designed for the inner loop to stabilize the attitude angle. A conventional PID controller was used for the outer loop in order to generate the reference path to inner loop. Moreover, the connective weights of the PIDNN were trained on-line by error back-propagation method. Furthermore, the initial connective weights were identified according to the principle of PID control theory and the appropriate learning rate was selected by discrete Lyapunov theory in order to ensure the stability. Finally, the simulation results demonstrate that the controller can effectively resist external wind disturbances, and presents good stability, maneuverability and robustness.
