7 results about "Affine nonlinear system" patented technology

The invention discloses a unified design method for a suboptimal controller of an aircraft system under multiple constraints, and the method comprises the steps: carrying out the modeling of an aircraft system and various constraint conditions in a control process; secondly, converting the aircraft system model into a form of an affine nonlinear system, and representing various constraints as state inequality constraints, input amplitude inequality constraints or input time delay constraints; then, respectively converting the state inequality constraint and the input amplitude inequality constraint into state equality constraints; meanwhile, a system containing input time delay is converted into a system without input time delay; then, establishing an unconstrained augmentation system comprising a no-input time-delay system and state equality constraints; and finally, designing a sub-optimal controller based on reinforcement learning for the unconstrained augmentation system by adopting an execution-evaluation network framework. By means of the multi-constraint control method, various constraints can be processed at the same time, and the multi-constraint control method is high in universality and can be used for diversified actual application scenes.

The application relates to the technical field of automatic control, in particular to a high-order iterative learning control method for saturation disturbance of a variable-length nonlinear system, which comprises the following steps: for a discrete-time affine nonlinear system simultaneously affected by input saturation, variable iteration length, random initial state offset and external disturbance, Bernoulli random variables are introduced to describe the variable iteration length, an extended control input sequence uniform time scale is constructed, and a modified tracking error is defined; a high-order feedforward and instantaneous feedback compound control law with dynamic time-varying characteristics is constructed: the high-order feedforward synthesizes the saturation extended control input and the modified tracking error of multiple historical iterations, and a saturation residual memory mechanism is introduced for adaptive anti-integral saturation compensation; the feedback term utilizes the current iteration error to suppress local fluctuations; a cooperative convergence condition of a time-varying learning gain matrix is given, the mathematical expectation of a tracking error is proved to converge to a bounded region related to the disturbance amplitude and the initial state offset; and under ideal conditions, the tracking error asymptotically converges to zero.

The application discloses a robot contact force constraint control method based on a control barrier function, and an affine nonlinear system model containing contact force is constructed based on a kinematics model, a dynamics model and a contact force model of the robot, which has better dynamic performance compared with a single contact force model, the control barrier function is applied to robot contact force safety constraint control, compared with existing position safety constraint control methods, the application of the control barrier function in the robot field is widened, the control barrier function can be combined with various existing force-position control methods, has good contact force constraint effect, high flexibility, good real-time performance, strong robustness, simple application, and effectively improves the problem that traditional force-position control is difficult to constrain contact force.

The invention belongs to the technical field of energy management and intelligent decision, and provides a self-adaptive dynamic programming hydrogen energy supply chain optimization decision method and system, which abstracts a hydrogen energy supply chain into a discrete-time affine nonlinear system, introduces a utility function, constructs a performance index function considering asymmetric constraint, and improves the performance of the hydrogen energy supply chain. The hydrogen storage state value is maintained at an expected level, and a control problem is converted into a double-person zero-sum game problem; a self-adaptive dynamic programming method based on a neural network is adopted to approximately solve the double-person zero-sum game problem, according to data collected along an actual running track of a system, the weight of each network is optimized and updated by taking error function minimization of each network in the neural network as a target, and a decision result after solving is obtained. The method does not depend on an accurate model, can adapt to environment changes online, effectively processes asymmetric constraints and can suppress demand disturbance.

The invention discloses a model simplification and control method of a nonlinear system. The method relates to the fields of computer systems based on specific calculation models, process control and the like. The method comprises the following steps: firstly, performing feedback linearization on an affine nonlinear model based on a Lie bracket and a Lie derivative of a differential geometry method, converting a nonlinear system into a linear system, and reducing the complexity of the model; secondly, on the basis of the genetic algorithm, by increasing the diversity of populations and the selection probability of high-quality individuals, the convergence speed and the global optimization capacity are improved, and it is ensured that better parameter configuration is obtained; compared with the prior art, the method has the advantages that a complex affine nonlinear system in the chemical process is simplified, the response speed and stability of a control system are improved, the production efficiency is improved, the global search capability of an optimization algorithm is enhanced, the dependency of parameter adjustment on manual adjustment is reduced, and the working efficiency is improved; the method has high technical innovation and application prospects in the chemical process of heat and mass transfer involving complex physical and chemical reactions.

The present invention proposes a disturbance rejection control method for a space manipulator based on zero-sum differential game, comprising the following steps: First, establish a dynamic system of the space manipulator with system disturbance uncertainty; then, represent the established dynamic system of the space manipulator as an affine nonlinear system; immediately afterwards, transform the control problem of the space manipulator into a zero-sum differential game problem and design a continuously differentiable objective function; then, use a single-layer neural network to online learn and solve the Nash equilibrium solution of the objective function; finally, obtain the disturbance rejection controller based on zero-sum game of the present invention, so that the space manipulator can complete space tasks under the condition of having system disturbance uncertainty. The present invention enables the space manipulator control system to have both robustness and optimality without continuous excitation conditions.

The invention discloses a feedback linearization-based non-linear control method and device for a network construction type converter. The method comprises the following steps: simplifying a network-forming converter in a grid-connected system into a constant voltage source, simulating a rotor motion equation and excitation regulation characteristics of a synchronous machine, and determining a control system model of the grid-connected system where the network-forming converter is located; converting the determined control system model of the grid-connected system where the grid-forming converter is located into a state space model; constructing a differential homeomorphism for the two-input and two-output affine nonlinear system; mapping the two-input and two-output affine nonlinear system into a linearization system by using the constructed differential homeomorphism; an output feedback linearization controller is constructed at the front end of the constructed differential homeomorphism, and a mapped linearization system is converted into an output feedback linearization network construction type converter grid-connected control system model; the designed control parameters and the constructed output feedback linearization controller are used for controlling the network-forming converter, the control precision is high, and the system is more stable.