Jul 2026· Bulletin of Shakarim University Technical Sciences· pp. 141-152· 0 citations· 8 references
Abstract
A new method is presented for synthesising a control algorithm for second-order nonlinear dynamic systems based on the concept of fixed-time stabilisation with output feedback. The study focuses on a broad class of planar nonlinear systems for which full access to state variables is not possible. The proposed methodology is based on a combination of the theory of bi-limit homogeneity and the principles of classical Lyapunov stability analysis. This approach has enabled the development of a continuous observer with a fixed convergence time, which reliably estimates the unmeasurable state of the system regardless of initial conditions and initial estimation errors. Based on this estimation, a continuous controller is constructed that ensures system stabilisation within a predetermined time.
The method has a number of advantages: stability and convergence do not depend on the magnitude and sign of the initial conditions; control remains continuous, which eliminates oscillation of the actuators; high robustness to limited external disturbances and measurement noise is achieved. The algorithm can be implemented on microcontrollers without the need for high-frequency sampling, making it attractive for practical use. As an example, the dynamics of a microelectromechanical system (MEMS) mirror are considered, which is a striking example of a highly non-linear electromechanical object. Numerical simulations were carried out, the results of which confirm the effectiveness of the proposed control scheme. Compared to existing finite-time controllers, the transient response time is reduced by more than a factor of four, whilst the system error and energy consumption are reduced by almost half. The results obtained confirm the applicability of the developed method to high-precision control of micro- and macro-mechanical actuators, as well as in intelligent robotic and vibro-optical systems.
The object of the study is a class of switched nonlinear systems with uncontrollable and unobservable linearized models, such as those arising in aerospace, power electronic, and robotics applications, where only output information is available for feedback. The problem to be solved is the global finite-time control fo...
K. Alimhan, Zhansaya Yergazy, A. Zhambulatova· Eastern-European Journal of...· 0 citations
This paper presents neural adaptive control methods for a class of nonlinear systems in the presence of actuator saturation by introducing alternative state variables and implementing state transformation, which ensures that the controllers can be developed without backstepping methodology.
Shigen Gao, Hairong Dong, B. Ning et al.· 0 citations
This paper investigates the predefined-time adaptive neural tracking control problem for a class of nonlinear pure feedback systems with full state constraints, and proves that all closed loop signals are predefined-time-bounded and the tracking error meets the preset performance specifications.
Yang Li, Ya-Qi Yu, Quan-Min Zhu et al.· Mathematics· 0 citations
A hyperbolic function is adopted to convert the unconstrained control command into a bounded signal so that the actuator constraints are strictly respected, and a Lyapunov-based design is carried out to derive the finite-time adaptive control protocol.
A practical finite-time adaptive fuzzy tracking controller is constructed, which guarantees the semi-global practical finite-time stability of the closed-loop system, with all closed-loop signals remaining bounded for all time and the tracking error converging to a residual set within finite time.
This paper proposes a novel adaptive state observer for nonlinear systems with uncertain mathematical models and output restrictions. The main contribution is the development of an observer architecture that does not require an accurate system model for its implementation. Instead, only a nominal reference model (A∗,B∗...
Iván Hernández, Isaac Chairez, Luis Ibarra· ISA transactions· 0 citations
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