执行依赖启发式动态规划PMSM控制策略研究

永磁同步电机算法中的PID参数固定不变,自适应能力较差;近似动态规划具有自学习能力,能动态调整参数,增强系统的自适应能力;文章将近似动态规划中的代表性算法——执行依赖启发式动态规划与类PI网络相结合,根据环境反馈对各个策略进行评价,选取评价最优的策略在线调整动作网络参数,对永磁同步电机进行自适应最优控制;仿真结果表明,执行依赖启发式动态规划加PI控制算法在系统速度变化和负载变化过程中,动态效果和稳态精度优于传统PID控制.     

Research on ADHDP energy management strategy for fuel cell hybrid power system

Fuel cell hybrid power system is a prospective power source for electrical vehicles. To reduce hydrogen consumption and enhance dynamic performance of the system, Action Dependent Heuristic Dynamic Programming (ADHDP) energy management strategy for the fuel cell hybrid power system was proposed. Firstly, topology of the system was analyzed and mathematical model was established through mechanism analysis. Secondly, framework of the ADHDP algorithm was presented, and it was followed by training algorithm for evaluating network and executing network of ADHDP based on Back Propagation (BP) algorithm. Finally, hardware-in-the-loop (HIL) simulation of the fuel cell hybrid power system was carried out to demonstrate the proposed ADHDP algorithm under real operating conditions. The results show that evaluating network and executing network of ADHDP have good convergence performance under different operating conditions. Compared with the other algorithms, the proposed ADHDP energy management strategy has better fuel economy and dynamic performance.     

Maximum wind power tracking for PMSG chaos systems – ADHDP method

Aiming at the chaotic behavior of PMSG under certain parameters, the new ADHDP method based on Cloud RBF neural network is proposed to track the point of maximum wind power, which can make the system out of chaos and track the point of maximum power stably, and the optimal control problems of the complex nonlinear system can be solved effectively. This method is realized by using the optimal power–speed curve and the vector control principle, and by adjusting the stator output voltage to control the electromagnetic torque, then the rotor speed of wind turbine can operate at the optimal speed that corresponds to the point of maximum power, meanwhile, the measure of wind speed also can be avoided. The simulation results show the effectiveness of the proposed method.     

自适应评价设计的执行依赖方法

自适应评价设计(ACD)是一种适用于非线性系统的近似最优控制方法。介绍了自适应评价设计的执行依赖启发式动态规划(ADHDP)和执行依赖双启发式动态规划(ADDHP)方法,该方法可以解决由对象非线性或者系统建模不良所造成的不确定性问题,适于处理时变的复杂系统和动态变化的复杂任务。阐述了两种方法的结构、计算和评价网络输出上的不同,并通过仿真分析了两种方法各自的学习能力、控制效果。     

基于执行依赖启发式动态规划的船舶减摇鳍在线最优控制

针对船舶线性横摇系统,设计了一种基于执行依赖启发式动态规划(ADHDP)方法的在线学习最优减摇鳍控制器.在设计过程中直接使用输入输出数据获取系统状态值.利用评价网络来逼近针对船舶减摇鳍控制系统设计的性能指标函数,并通过执行网络获得最优控制律,这两个网络都是多层前馈神经网络,即反向传播(BP)神经网络.在训练过程中,这两个神经网络不仅可以使用实时测量数据,也可以减少船舶横摇模型的内部误差和不确定性干扰的影响,从而提高系统的鲁棒性.最后,仿真结果表明所提出的ADHDP控制器对于降低船舶横摇有很好的控制效果.     

ADHDP方法在静止无功补偿器优化控制中的应用

介绍了静止无功补偿器SVC和自适应动态规范的执行方法ADHDP的基本原理,基于PI控制法的电压负反馈控制策略,应用ADHDP方法对输入PI调节器的电压偏差进行了优化,并在Matlab/Sim-ulink环境下对SVC控制系统进行了仿真实验。仿真结果表明,经优化后的控制系统响应速度明显提高,动态性能得到了较好的改善。