10 results about "Stability proof" patented technology

The invention relates to the technical field of robot control, and discloses a mechanical arm specified performance fault-tolerant control method based on a fuzzy logic system, and the method comprises the steps: building a kinematics and dynamics model and a fault model of an agricultural robot; establishing a relative error dynamic equation between the actual position and the expected position; designing a specified performance function, and constraining the tracking error within an expected range by using the specified performance function; on the basis, designing a virtual control law by using a backstepping method under the condition of meeting error constraints; designing an adaptive control law by adopting a fuzzy logic system based on an uncertain item, unknown environment interference and a fault model in the kinetic model; a specified performance controller is designed based on a virtual control law, fuzzy logic adaptive control and full-state feedback agricultural robot, and specified performance fault-tolerant control of the agricultural robot is realized. The stability proves that the tracking error of the agricultural robot converges to any small neighborhood near zero within fixed time.

The application belongs to the technical field of distributed vehicle platoon control, and provides a vehicle platoon control method and system with a time-varying gain extended state observer, which comprises establishing a vehicle dynamics model; external disturbances are estimated in real time based on the time-varying gain extended state observer, and the initial differential peak value phenomenon is effectively inhibited; the stability analysis of the observer system is discussed in different cases, and it is verified that the time-varying gain extended state observer has a more rigorous and simple stability proof process; an extended state observer for compensating external disturbances and unknown nonlinear terms of the model is designed, a virtual controller and an actual controller are constructed by using the backstepping method based on the extended state observer and the fixed-time stability theory; by designing a fast fixed-time backstepping control method, the system state converges to the expected signal in a fixed time, and the system obtains good tracking performance.

The invention relates to an impact load-oriented electro-hydraulic servo active suspension feedback linearization sliding mode robust control method, which belongs to the technical field of vehicle active suspension and electro-hydraulic servo control, and comprises the following steps of: firstly, establishing a quarter vehicle two-degree-of-freedom active suspension model; the method comprises the following steps: step 2, constructing a nonlinear dynamic model of the electro-hydraulic servo actuator of the valve-controlled cylinder; step 3, designing a feedback linearization sliding mode composite controller and giving a stability proof; and step 4, carrying out controller parameter setting and simulation comparison. According to the feedback linearization sliding mode robust control method provided by the invention, the nonlinearity and parameter uncertainty of the actuator can be effectively compensated under the impact working conditions of a deceleration strip and the like, the piston displacement tracking error and sliding mode buffeting are remarkably reduced, sprung mass vibration is reduced, the vehicle driving smoothness and attitude stability are improved, and the method is suitable for large-scale popularization and application. The method is suitable for the field of vehicle hydraulic active suspension control.

This invention discloses a sliding mode model predictive control method and system for permanent magnet motors. Based on sliding mode control theory, the invention establishes a model predictive control cost function that satisfies the definition of a Lyapunov function. This cost function can adjust the current error by selecting a voltage vector, thereby enabling the cost function to converge within a finite time. The cost function designed in this invention not only undergoes rigorous stability proofs, but when applied to model predictive control strategies, it selects the voltage vector with the minimum cost function as the optimal voltage vector for motor control. This process eliminates the need for current prediction; it directly evaluates the control error of the voltage vector using the reference current, actual current, and voltage vector, thus simplifying the control process and avoiding the influence of motor parameters on control performance. Compared to vector control, this invention retains the advantages of model predictive control in terms of speed and flexible multi-objective control.

The invention discloses a hydraulic arm position sliding mode control method based on an expansion state observer, which belongs to the technical field of electro-hydraulic position servo control, and comprises the following steps: step 1, establishing a state space model of a hydraulic mechanical arm joint position system; step 2, establishing a mathematical model of the extended state observer; 3, designing an improved sliding-mode active disturbance rejection controller based on an extended state observer, and replacing linear feedback with an improved sliding-mode control law while performing real-time observation and compensation on the comprehensive disturbance quantity of a joint position system of the hydraulic mechanical arm; and 4, carrying out stability proving on the improved sliding-mode active-disturbance-rejection controller by using a Lyapunov stability theory. According to the method, the disturbance quantity of the joint position system of the hydraulic mechanical arm is observed and compensated in real time, meanwhile, the improved sliding mode control law is adopted to replace linear feedback, the response lag phenomenon can be improved, and the control precision and robustness of the joint position system of the hydraulic mechanical arm are improved.

The present invention discloses a method for sliding mode control of a permanent magnet synchronous motor based on predetermined time. The method specifically includes: modeling a mathematical model of the system and establishing a local model of the speed loop based on model-free theory; designing a predetermined time sliding mode controller based on predetermined time stability theory and proving its stability; treating the unknown parts of the model and external disturbances as lumped disturbances, defining an intermediate variable, designing an extended state observer to estimate the disturbances, and proving its stability. The present invention models the system based on model-free theory and designs a predetermined time sliding mode controller and an extended state observer based on the established model. Ultimately, the system converges and stabilizes within the predetermined time, and the convergence time is independent of the initial state of the system. The method can effectively suppress the chattering of traditional sliding mode control methods and improve the control accuracy, anti-interference capability, and robustness of the permanent magnet synchronous motor.

The invention relates to the technical field of electro-hydraulic position servo control systems of excavators, in particular to a trajectory tracking control method and device for a mechanical arm of an excavator, and the method comprises the following steps: S1, establishing a mathematical model of an electro-hydraulic position servo system of the mechanical arm; s2, identifying system parameters on line based on samples of a proportional pressure reducing valve and a multi-way valve of the excavator; s3, based on the mathematical model of the electro-hydraulic position servo system of the mechanical arm in the S1 and the identification parameters in the S2, a self-adaptive backstepping sliding mode controller based on a parameter layering strategy is designed, and tracking control is conducted on the track of the mechanical arm of the excavator through the self-adaptive backstepping sliding mode controller; and S4, a Lyapunov stability theory is used to carry out stability proving on the adaptive backstepping sliding mode controller in the S3, and an asymptotically stable system tracking error is obtained.

The application provides a robust reliable H∞ control method for offshore steel jacket platform models, first establishes a mathematical model of OSJPs, and considers the first main vibration mode. Then, a controller based on memory SDC is designed, which can realize effective control by reducing data transmission amount under the condition that the state of the continuous time system is only available at the sampling time. In addition, a back loop function method, an integral inequality based on a free matrix (FMB) and a linear matrix inequality (LMI) technology are introduced to obtain sufficient conditions about the uncertain offshore platform system, so that the stabilization of the OSJPs is solved, and the reliable SDC design with disturbance suppression level is realized. The simulation result of the application shows that the proposed method can not only effectively reduce the vibration of the OSJPs, but also maintain the stability of the system in the case of model uncertainty and actuator failure, proving the effectiveness and importance of the proposed control strategy.

The application discloses a kind of based on reinforcement learning's mechanical arm adaptive compliant force control method, belong to robot technology and automation field.The method is based on the " reinforcement learning-adaptive compliant force control " integrated framework of mechanical arm-dexterous hand-six-dimensional force / torque sensor system, aims at through intelligent control strategy, completely eliminate the existing problems such as the need for manual parameter setting, contact dynamics modeling, model parameter estimation, adaptive law needs frequent stability proof, realize upper task planning, low-level compliant force / position control self-learning, self-adaptation.Deployment is not needed artificial repeated parameter adjustment for different working conditions, so that the same control strategy can maintain high assembly success rate and low peak contact force for small gap, easy deformation, multi-material workpieces, eliminate artificial calibration and environment modeling, parameter online estimation bottleneck, realize flexible production line " zero downtime " fast switching.