RESUMEN
A novel hierarchical control framework combining computed-torque-like control (CTLC) with disturbance-observer-based event-triggered robust model predictive control (DO-ET-RMPC) is proposed for the trajectory tracking control of robotic manipulators with bounded disturbances and state and control input constraints. The CTLC approach is first used to cancel the exact nonlinear dynamics of the original tracking error system to obtain a set of decoupling linear tracking error subsystems, thus reducing the optimization complexity of model predictive control (MPC). The composite DO-ET-RMPC scheme is then developed based on the so-called dual-mode MPC approach to robustly stabilize the tracking error subsystems, which could improve the robustness of MPC and save its computational resources simultaneously. The continuous-time theoretical properties of the DO-ET-RMPC scheme, considering disturbances and state and control input constraints simultaneously, are provided for the first time, including the avoidance of Zeno behavior, robust constraint satisfaction, recursive feasibility, and stability. In the end, the superiorities of the proposed control scheme are verified by the comparative simulations.
RESUMEN
The time-varying frequency disturbance rejection problem is addressed for a class of nonlinear uncertain system. A novel refined disturbance observer (RDO) is developed composed of auxiliary observer and calibration observer. At first, the disturbance is redescribed using auxiliary observer after coordinate transformation, which contains a parametric form about frequency and a decay term. The derivative of frequency and system uncertain are absorbed in the decay term, furthermore, the correlation between disturbance frequency and disturbance can be derived. Then the key parameter, i.e. frequency factor is estimated by calibration observer characteristic with two-degree-freedom, the decay term associated with derivative of frequency can be attenuated in feedback control loop. Thus, the composite controller including a refined disturbance observer (RDO) and a robust feedback controller is designed, which inherits the elegant feature of disturbance observer based control (DOBC). The H∞ index performance can be guaranteed to attenuate the estimation error driven by disturbance time-varying frequency together with system uncertainty.
RESUMEN
This paper proposes a composite fault detection scheme for the dynamics of high-speed train (HST), using an unknown input observer-like (UIO-like) fault detection filter, in the presence of wind gust and operating noises which are modeled as disturbance generated by exogenous system and unknown multi-source disturbance within finite frequency domain. Using system input and system output measurements, the fault detection filter is designed to generate the needed residual signals. In order to decouple disturbance from residual signals without truncating the influence of faults, this paper proposes a method to partition the disturbance into two parts. One subset of the disturbance does not appear in residual dynamics, and the influence of the other subset is constrained by H∞ performance index in a finite frequency domain. A set of detection subspaces are defined, and every different fault is assigned to its own detection subspace to guarantee the residual signals are diagonally affected promptly by the faults. Simulations are conducted to demonstrate the effectiveness and merits of the proposed method.
