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A robust constraint-following control (CFC) scheme is proposed for active suspension system to improve ride comfort of high-speed trains (HSTs) by employing nonlinear stiffness of bio-inspired structure (BIS). The control problem of driving active suspension system to emulate nonlinear dynamics of BIS is formulated as servo constraint-following. The disturbance observer is theoretically integrated into CFC framework to address critical practical issues, including parameter uncertainty, suspension nonlinearity and aerodynamic disturbance. The complex uncertainty decomposition and uncertainty bound function design can be avoided in the control design compared with past adaptive CFC. Lyapunov stability theory is applied to prove the uniform ultimate boundedness of proposed robust CFC, enabling the constraint-following error to converge to a very small range. The simulation results demonstrate that the active suspension system could exactly follow the servo constraints of reference BIS with high constraint-following accuracy regardless of parameter uncertainty and external disturbance. And the active suspension system can effectively suppress the vibration and improve the ride comfort steadily with random structure parameters and strong aerodynamic loads. This study also provides a new insight and an alternative approach for designing robust CFC in the active suspension of HSTs.

Articulating crane (AC) is used in various industrial activities. The articulated multisection arm exacerbates nonlinearities and uncertainties, making the precise tracking control challenging. This study proposes an adaptive prescribed performance tracking control (APPTC) for AC to robustly fulfill the task of precise tracking control, with adaptation to resist time-variant uncertainties, whose bounds are unknown but lie in prescribed fuzzy sets. Particularly, a state transformation is applied to simultaneously track the desired trajectory and satisfy the prescribed performance. Adopting the fuzzy set theory to describe uncertainties, APPTC does not invoke any IF-THEN fuzzy rules. There is no linearizations, or nonlinear cancelation for APPTC, thus making it approximation free. The performance of the controlled AC is twofold. First, deterministic performance in fulfilling the control task is ensured by the Lyapunov analysis using uniform boundedness and uniform ultimate boundedness. Second, fuzzy-based performance is further improved by an optimal design, which seeks the optima of control parameters by formulating a two-player Nash game. The existence of Nash equilibrium is theoretically proved, and its acquisition process is given. The simulation results are provided for validations. This is the first endeavor that explores the precise tracking control for fuzzy AC.

A tiltrotor aircraft (TRA) can both hover in the air (hover flight state) and cruise quickly (level flight state). Transition flight is a transitional state between these two flight states, during which tiltable rotors rotate, forming a unique state for TRA. Revolving of the tiltrotor shaft leads to strong nonlinearity and time-varying uncertainty, which weakens the stability of attitude control with linearization in transition flight. The safety of TRA is critical, but it can be easily harmed due to the weak control stability. This study is to regulate the TRA attitudes agilely and precisely simultaneously, by ensuring fast convergence speed and small convergence error, i.e., a prescribed transient and steady state performance (PTSSP). A constraint-based adaptive robust prescribed performance control (CARPPC) is proposed for TRA to follow the desired attitude while guaranteeing PTSSP, with no approximations or linearizations invoked. The desired attitudes and PTSSP are respectively described as equality and inequality servo constraints. A constraint-based control with state transformation is introduced to render both equality and inequality constraint-following. An adaptive law is established for online estimation of unknown uncertainty bounds to compensate time-varying uncertainty. Both theoretical proofs and simulation results demonstrated that CARPPC can realize agile and precise attitude control robustly in transition flight.