11 results about "Continuous time system" patented technology

The invention relates to the technical field of power system control, solves the problems of network attack, limited bandwidth and transmission delay of a power system in a signal transmission process and conservative DET parameter selection and controller design, and particularly relates to a power system dynamic event triggered load frequency control method under Dos attack and random delay. Comprising obtaining a continuous time system parameter matrix; setting an event triggering threshold function; state parameters facing Dos attack and random time delay conditions are set; constructing a state feedback controller; and collaborative design optimization is carried out by applying a GA optimization algorithm. Compared with a traditional control method, the method has the advantages that on the premise of ensuring the stability of the system, by optimizing event triggering conditions, the communication requirement and bandwidth occupation are remarkably reduced, the utilization efficiency of communication resources is improved, network congestion and delay possibly caused by frequent communication are reduced, and the service life of the system is prolonged. And the operation efficiency of the whole power system is improved.

The invention relates to the technical field of power buoys, in particular to a power buoy self-positioning control method based on an MPC algorithm and a power buoy. The method comprises the following steps: firstly, establishing a kinematic model of a buoy, converting the kinematic model into a continuous state space model, secondly, establishing a continuous time system equation according to the kinematic model, and then, discretizing the continuous state space model to obtain a continuous time system equation; discretizing a state transition matrix and an input influence matrix in the continuous state space model according to a continuous time system equation, then establishing an objective function, constraining control parameters in a kinematic model, and finally solving an optimal solution of the objective function in a constraint range by adopting a linear quadratic programming function, so as to obtain a continuous state space model. Optimal control parameters are obtained, and optimal positioning and navigation control are achieved. A positioning control system and a power propelling system are arranged, the posture and position of the buoy can be rapidly and automatically adjusted, and the adaptability and flexibility of the buoy are greatly improved.

The embodiment of the present invention provides a method and device for linear resonant motor parameter identification. The LRA parameter identification uses the zero-input response discrete-time system model of the second-order linear resonant system to construct a second-order forward prediction error filter, and uses the augmented Wienerhof equation to solve the coefficients of the discrete-time system model to obtain the minimum mean square error estimate, which has the advantages of strong anti-noise ability and good robustness. Through the estimated discrete-time system model, the impulse response invariant method can directly calculate the poles, free oscillation frequency and damping coefficient of the continuous-time system without iterative calculations.

The present application relates to the technical field of power buoy, in particular to a power buoy self-positioning control method based on MPC algorithm and a power buoy. First, the kinematic model of the buoy is established and converted into a continuous state space model, then the continuous time system equation is established according to the kinematic model, then the continuous state space model is discretized, then the state transition matrix and the input influence matrix in the continuous state space model are discretized according to the continuous time system equation, then the objective function is established, and the control parameters in the kinematic model are constrained, finally the optimal solution of the objective function is solved in the constraint range by using the linear quadratic programming function, the optimal control parameters are obtained, and the optimal positioning and navigation control are realized. The present application is equipped with a positioning control system and a power propulsion system, can quickly and autonomously adjust the attitude and position of the buoy itself, and greatly improves the adaptability and flexibility of the buoy.

The invention relates to a non-linear control system-oriented micro neural control barrier function security verification method, which supports more efficient verification of NCBF of micro monotonic activation functions such as tanh in a framework for verifying NCBF by a CROWN-based method, and is suitable for analysis of a continuous time system because the NCBF is micro. The derivative interval is not indirectly derived through linear relaxation of the activation value, but the real extreme value of the sigma '(z) is directly solved on the pre-activation interval, and the derivative boundary is tighter. As the derivative boundary is more accurate, back propagation accumulative relaxation is significantly reduced, and the final Jacobian interval is closer to a real value. Compared with a traditional SMT / MIP / CROWN method, the method has the advantages that acceleration is achieved by several times while strict safety is kept, and near-real-time deployment is facilitated.

The invention discloses a subsynchronous oscillation mode identification method and device based on SMSST-CDSSI, and the method comprises the steps: employing a ridge extraction method, screening out a time-frequency coefficient representing each subsynchronous oscillation component according to the energy of the time-frequency coefficient in each second-order multiple synchronous compression transformation coefficient matrix, and obtaining an optimal instantaneous frequency track; performing time domain reconstruction of each oscillation mode according to the optimal instantaneous frequency trajectory; the method comprises the following steps: constructing a state space model of an n-order system according to input and output signals of a power system and considering deterministic and random noise, and constructing a corresponding Hankle matrix according to input and output variables; performing LQ decomposition on the input / output Hankel matrix to calculate an oblique projection matrix Oi; and performing singular value decomposition on the oblique projection matrix Oi, calculating a state matrix A of a discrete system, performing eigenvalue decomposition on the state matrix A, solving a discrete eigenvalue of the state matrix A, and solving the frequency fi and the modal damping ratio xii of the subsynchronous oscillation according to the relationship between the discrete system and the continuous time system. The device comprises a processor and a memory.

The application discloses a missile guidance control integration method based on a neural network mechanism modeling, which comprises the following steps: in a continuous time system, a vertical plane missile guidance control integration model is established; according to the dynamic equation of the vertical plane missile guidance control integration, a state transition equation in a discrete time system is established; a data set for fitting the dynamic model of a neural network is established, and a neural network parameter model obtained through neural network regression calculation is used as a non-mechanism fitting model of a missile control system; and according to the neural network parameter model, a guidance control integration mechanism model used in a control cycle is obtained. The method uses the input and output data of a control process to perform self-modeling of a time-varying control system, meanwhile, the model is equivalent to a mechanism method, and the modeling result can be used for the control of a discrete time system, and the modeling principle has interpretability and reliability.

This invention discloses a method for equipment operation scheduling decision-making considering resource constraints, belonging to the field of equipment scheduling management technology. This invention embeds equipment operation scheduling conflicts into the continuous time domain by constructing a temporally coupled conflict analysis graph model and establishing an event-driven state transition mechanism, achieving unified modeling of discrete decision-making and continuous-time system dynamics. By transforming the decision objective into a utility density function and integrating it along the state trajectory, the cumulative utility value of path dependence is obtained, generating a preference ranking of each decision-maker for the state trajectory. The stability of each state trajectory is tested through a temporally coupled stability definition, and state trajectories that satisfy the temporally coupled stability definition are determined as balanced scheduling schemes. This invention achieves deep integration of resource constraints, multi-objective trade-offs, and multi-agent strategy interactions in the continuous time domain, and is applicable to multi-agent resource-constrained scheduling scenarios such as equipment rotation and industrial equipment cluster maintenance.

The invention provides a steering and torque distribution integrated control method for a four-wheel independent drive vehicle based on nonlinear predictive control, which comprises the following steps of: firstly, establishing a nonlinear state-space equation of the four-wheel independent drive vehicle, and establishing an optimal control problem based on the state-space equation; and then the optimal control problem of the original continuous time system is converted into a nonlinear optimization problem by using a forward Euler method and a multiple targeting method, and the singularity of the nonlinear optimization problem is effectively eliminated and the convexity of the nonlinear optimization problem is improved by adding a regular term in an optimization target. Finally, a moderate-scale sequential quadratic programming mode is designed, and compared with the prior art adopting hierarchical nonlinear predictive control, an open source solver IPOPT and the like, the control precision and the solving speed can be effectively improved.

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 provides a kind of fast flexible full pure embedded automatic driving lateral motion control method, including establishing vehicle system dynamic model;Vehicle system dynamic model is carried out continuous time system discretization processing, and the discrete time system for model predictive controller is obtained;The cost function and constraint condition of model predictive controller are constructed;The optimal control decision of model predictive controller is calculated according to the cost function and constraint condition.The application can improve the calculation efficiency of automatic driving lateral control MPC to meet the needs of real-time control;The application solves MPC problem through three main steps of series expansion, rational approximation and piecewise continuation, and the calculation speed is faster and the calculation accuracy is higher in the same time, solves the deficiencies such as low calculation efficiency and slow convergence speed of existing method, meets the needs of automatic driving real-time control.