Immersion and Invariance Based Robust Adaptive Control of High‐Speed Train with Guaranteed Prescribed Performance Bounds

Abstract

This paper proposes a novel robust adaptive algorithm for train tracking control with guaranteed prescribed transient and steady-state performance. As speed increases, the inherent time-varying uncertainties and unmodeled dynamics in the longitudinal dynamics of a high-speed train seriously impacts the tracking performance of automatic train operation. To improve train operation performance, an estimator based on immersion and invariance technology is developed to recover the unknown and time-varying plant parameters, and it renders the estimation error converging to a bounded residual set exponentially while providing more freedom for the controller. After certain error transformation, the prescribed tracking performance is introduced into the controller design. Then, an input-to-stable stable controller is developed through the backstepping technique, and it is proven that stabilization of the transformed system is sufficient to guarantee the prescribed performance. Rigorous theoretical analysis for the presented algorithm is provided, and a series of simulation studies also are given to verify the effectiveness of it.

Composite Disturbance‐Observer‐Based Control and Control for High Speed Trains with Actuator Faults

“…Consider the closed-loop system in the form of (16) and (17). For a given constant , there exists a disturbance-observer-based controller (14) such that the closed-loop system (16) is asymptotically stable and the ℋ ∞ performance with the guaranteed performance index is satisfied, if there exist a scalar 1 > 0, matrices 1 > 0, 2 > 0 and 3 , 4 , such that the following linear matrix inequality holds:…”

“…Based on the above either the single point‐mass model or the multiple point‐mass model, a wide range of control algorithms are used to tackle complex problems of the HSTs system, such as adaptive control , optimal control , and predictive control . In , Khmelnitsky handled with the optimal control problem of train operation.…”

Nonlinear Hybrid Multipoint Model of High‐Speed Train with Traction/Braking Dynamic and Speed Estimation Law

“…HST can operate safely and efficiently mainly depending on the performance of ATO (Automatic Train Operation) system, and the accurate dynamic model is the first stepstone for designing ATO control law [1]; therefore, many researchers have paid more attention to it during the past few decades [2][3][4][5][6][7][8][9][10][11][12][13]. There are mainly two types of models: single-point model and multipoint model.…”

“…There are mainly two types of models: single-point model and multipoint model. The former model ignores in-train dynamics and considers the train as a single mass point [2], which is widely used in energy saving optimization [3], automatic driving [4], and precise stopping [5]. However, the train is connected by couplers to transmit large traction and braking force, and this nonlinear force has a strong effect on the longitudinal motion of HST [6].…”

Boundary Control of a Flexible Robotic Manipulator With Output Constraints

“…Recently, a novel prescribed performance constraint method was developed in . In these studies, using a prescribed error transformation function, a prescribed performance can be guaranteed, which means that the tracking performance of the transient and steady state error can be regulated.…”