面向性能增强的双惯量伺服系统状态反馈控制

为避免使用函数逼近器(神经网络或模糊系统),并提高双惯量伺服系统的瞬态响应和稳态性能,针对含外部扰动的双惯量伺服系统,提出一种基于预设性能函数(Prescribed performance function, PPF)的类比例状态反馈控制策略.首先,提出一种改进的带有最大超调、收敛速率以及稳态误差的预设性能函数,并将该函数融入控制器设计使二惯量伺服的跟踪误差保持在预定的边界之内.其次,基于预设性能函数设计了类比例状态反馈控制器实现跟踪控制.与传统基于函数逼近控制方法相比较,该方法可降低控制系统计算复杂度同时消除反演控制中存在的复杂度爆炸问题.最后,利用双惯量伺服系统实验平台开展了对比实验,验证了所提出方法的有效性.

State Feedback Control for Dual-inertia Servo Mechanisms With Performance Enhancement

To avoid using the function approximation (neural networks or fuzzy logic systems) and enhance the transient and steady-state control performance, this paper proposes a proportional-integral feedback control strategy for dual-inertia servo systems with external disturbance based on prescribed performance functions (PPF). First, a modified prescribed performance function with guaranteed convergence rate, maximum overshoot and steady-state error boundary is employed, so that both the transient response and steady-state errors are retained within a predefined boundary. Second, a state-feedback control with this proposed PPF is suggested. Compared with the classical function approximation-based control approaches, the computational complexity of the developed control system is reduced and the explosion of complexity in the backstepping methods could be remedied. Finally, comparative experiments based on a dual-inertial test-rig are provided to show the effectiveness and superior performance of the proposed control scheme.