In this paper, a practical analysis of stability by simulation for the effect of incorporating a Kalman estimator in the control loop of the inverted pendulum with a neurocontroller is presented. The neurocontroller i...In this paper, a practical analysis of stability by simulation for the effect of incorporating a Kalman estimator in the control loop of the inverted pendulum with a neurocontroller is presented. The neurocontroller is calculated by approximate optimal control, without considering the Kalman estimator in the loop following the Theorem of the separation. The results are compared with a time-varying linear controller, which in noiseless conditions in the state or in the measurement has an acceptable performance, but when it is under noise conditions its operation closes into a state space range more limited than the one proposed here.展开更多
Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning ...Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.展开更多
文摘In this paper, a practical analysis of stability by simulation for the effect of incorporating a Kalman estimator in the control loop of the inverted pendulum with a neurocontroller is presented. The neurocontroller is calculated by approximate optimal control, without considering the Kalman estimator in the loop following the Theorem of the separation. The results are compared with a time-varying linear controller, which in noiseless conditions in the state or in the measurement has an acceptable performance, but when it is under noise conditions its operation closes into a state space range more limited than the one proposed here.
基金supported by the National Natural Science Foundation of China(U21A20166)in part by the Science and Technology Development Foundation of Jilin Province (20230508095RC)+1 种基金in part by the Development and Reform Commission Foundation of Jilin Province (2023C034-3)in part by the Exploration Foundation of State Key Laboratory of Automotive Simulation and Control。
文摘Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.
