4 results about "Stability theory" patented technology

This invention discloses a fixed-time adaptive sliding mode control method and system for improving the disturbance rejection performance of downhole permanent magnet synchronous motors (PMSMs). The method includes: establishing a mathematical model of the PMSM considering parameter uncertainties and external load disturbances, defining parameter uncertainties and external load disturbances as lumped disturbances; constructing a fixed-time extended state observer to observe the lumped disturbances in real time based on fixed-time stability theory and obtain an estimate of the lumped disturbances; designing a fixed-time adaptive sliding mode control law based on the lumped disturbance estimate, generating a q-axis reference current, and realizing speed control of the PMSM; wherein, the adaptive sliding mode control law is derived by combining a non-singular fast terminal sliding surface, a fixed-time reaching law, an adaptive gain based on a variable gain rate smoothing factor, and the lumped disturbance estimate. This invention achieves fast and accurate convergence of disturbance errors within a fixed time.

This invention proposes a method and system for fixed-wing UAV habitat planning based on the attraction domain, belonging to the field of UAV control technology. The method includes step S1: acquiring the core state parameters and control parameters during the flight of the fixed-wing UAV; step S2: estimating the UAV's flight attraction domain based on the Lyapunov model, combined with the core state parameters and control parameters, to obtain an attraction domain set; and step S3: generating a reference flight trajectory based on the attraction domain set and landing target data. This invention also proposes a fixed-wing UAV habitat planning system based on the attraction domain. This invention ensures stable convergence throughout the entire UAV habitat landing process from the perspective of nonlinear system stability theory. Simultaneously, through lightweight modeling and simplified solution, it adapts to the onboard computing capabilities of small UAVs, effectively solving the core defects of existing technologies such as weak robustness, lack of stability guarantee, and complex calculations, enabling small fixed-wing UAVs to achieve precise habitat landing in small spaces without taxiing.

This invention discloses a sliding mode control method based on a neural network adaptive observer, belonging to the field of hydraulic position servo system control technology. The method involves: establishing a nonlinear mathematical model of the hydraulic servo system; designing a state observer based on a radial basis function neural network to estimate the states in the system, and designing the system's sliding mode control law using the observed parameters; designing a neural network adaptive law using Lyapunov stability theory; smoothing the controller output using a filter; and selecting appropriate controller hyperparameters to enable the system to achieve the desired control effect and accurately track the desired signal. The control strategy designed in this invention can estimate nonlinearities that are difficult to model online, accurately observe the system state, exhibit good steady-state performance, and is easy to apply in engineering.

The application discloses an inverted pendulum preview tracking control method and system based on double nonlinear constraints, and belongs to the field of robot control. The method establishes an inverted pendulum nonlinear model, and the nonlinear term satisfies the one-sided Lipschitz and quadratic inner bounded condition; a preview expanded error system is constructed, and the tracking problem is converted into a stability problem; a state feedback or static output feedback controller architecture is selected according to the measurable information type of the system; the Lyapunov stability theory and double nonlinear constraint lemmas are used to realize the asymptotic stability and H ∞ The disturbance attenuation performance requirement is converted into a linear matrix inequality, and the optimal feedback gain and preview compensation gain are obtained by solving; finally, the gain is configured in a control unit, and a control instruction is generated in combination with real-time feedback and preview information. The application reduces the conservativeness of nonlinear control, eliminates the phase lag of time-varying signal tracking, adapts to the composite output working condition, and significantly improves the tracking accuracy and robustness of the inverted pendulum.