71 results about "Differential game" patented technology

The invention relates to the technical field of control, and provides a process disturbance-oriented bidirectional anti-interference control system and method, and the system comprises the steps: receiving an external disturbance signal and controlled object state monitoring data in parallel through a process sensing module, generating a disturbance feature vector through frequency band decomposition, and processing the state monitoring data through a nonlinear manifold learning algorithm, deep recognition of response features is realized; the disturbance coupling module takes the feedforward control pre-estimated quantity and the feedback control compensation quantity as optimization variables and takes the disturbance suppression ratio and the response recovery time as revenue functions to construct a differential game model, and the revenue functions are optimized through a gradient iterative algorithm; the bidirectional fusion module realizes dynamic weighting of two types of control quantities based on the coupling weight matrix; and the intelligent control module obtains a control deviation integral and response recovery time in real time, and dynamically adjusts parameters of the revenue function and parameters of weighted fusion through the reward function.

The invention relates to the field of intelligent control of marine navigation, and discloses a formation dynamic interception path planning method and device based on a differential game theory, and the method comprises the steps: constructing a differential game model comprising a formation and intercepted ships; designing revenue functions for the two parties; obtaining a Nash equilibrium strategy by solving a Hamiltonian-Jacobian-Bellman equation of the game, and solving an individual optimal control instruction of each formation member; and fusing state information among formation members through a consistency protocol, adjusting individual instructions to meet anti-collision and formation cooperative constraints, and generating a final control instruction. According to the method, historical adversarial data is learned by using the neural network, and the weight of the revenue function is adaptively and dynamically adjusted to cope with different tactical scenes; and the whole decision-making process is set under a model prediction control framework for rolling optimization, so that the real-time performance, the collaboration and the intelligent level of interception path planning are greatly improved, and the interception efficiency is effectively improved.

The invention relates to the technical field of network security, and discloses a network security management method and system based on a big data model, and the method comprises the steps: 1, converting multi-source heterogeneous data into a graph node containing a device entity, an I P entity and a user entity, and an interaction edge containing a timestamp and a relation type; step 2, constructing an attack chain dynamic evolution equation based on graph nodes and interaction edges, wherein the equation comprises an attacker action parameter and a defender action parameter; and step 3, inputting a time fusion Transform model to obtain probability distribution of a future attack action sequence by using a state variable corresponding to the attack chain dynamic evolution equation. According to the method, the technical scheme of constructing an attack chain dynamic evolution equation based on a differential game model, predicting an attack action sequence through time fusion Transformer and dynamically updating a defense strategy through meta reinforcement learning is adopted, and the technical effects of accurately modeling an attack evolution path, predicting an attack behavior in advance and generating a self-adaptive defense strategy in real time are achieved.

The invention discloses a modular mechanical arm actuator additive fault optimal fault-tolerant control method and device of a zero sum differential game, and relates to the field of robot control algorithms, and the method comprises the steps: representing a nonlinear damping characteristic through a joint friction torque, describing the dynamic interaction of multiple joints through a cross-linking coupling item, and determining the optimal fault-tolerant control of the additive fault of the modular mechanical arm actuator; a dynamical model containing faults is constructed. And uncertain items in the model are updated online by adopting a radial basis function neural network identifier, so that the model precision is improved. A performance index function is constructed based on position errors, actuator faults and controller input are regarded as two opposite parties of a zero and differential game, the performance index function is approximated through a single evaluation neural network, a Hamiltonian-Jacobi-Axaxi equation is approximately solved, and an optimal fault-tolerant control strategy is obtained. According to the method, the game theory is combined with the neural network, the dynamic unknown fault problem of the modular mechanical arm is effectively solved while the system energy consumption integration is reduced, and real-time optimal control over the modular mechanical arm is achieved.

The invention discloses a multi-missile self-learning differential game cooperative guidance method based on disturbance feed-forward compensation, and the method comprises the steps: providing a finite-time convergence sliding-mode nonlinear expansion state observer for solving the problems of unknown partial parameters and external disturbance in a multi-missile cooperative guidance system; a sliding mode control method is combined with an extended state observer, a novel fixed-time convergence sliding mode surface and a sliding mode reaching law are constructed, and real-time estimation and efficient compensation of unknown disturbance in a system are achieved. Strictly proving the fixed convergence time of the observer by using a Lyapunov function, and analyzing a disturbance estimation error; compared with a traditional ESO, the method has the advantages that the speed and precision of state tracking are remarkably improved, and the anti-interference capability of the multi-missile cluster in a complex interference environment is effectively improved.

The invention discloses an APT (Advanced Persistent Threat) attack defense method based on edge intelligence, which aims to improve the dynamic perception capability, strategy response capability and resource adaptability of an edge network to APT attacks, and comprises the following steps of: firstly, constructing a topological adjacency matrix of an edge node communication network and defining five states and state conversion processes of a life cycle of edge equipment; the method comprises the following steps: firstly, designing an attack defense model based on optimal control and differential game, then introducing a system evolution model based on hidden confrontation, and accurately simulating dynamic interaction of attack and defense in an actual edge network, secondly, designing an attack defense model based on optimal control and differential game, and finally, adopting a Nash strategy reinforcement learning mechanism based on a multi-agent deep Q network, optimizing an edge game strategy, and finally, obtaining an attack defense result. And the attack detection performance is improved. According to the method disclosed by the invention, the modeling precision and defense effectiveness of the system in a complex APT attack scene are remarkably improved, and the method is suitable for key infrastructure network environments with relatively high requirements on safety, timeliness and expandability, such as industrial Internet and Internet of Things.

The invention discloses a rectangular area unmanned aerial vehicle hunting method based on differential game and reinforcement learning. The our unmanned aerial vehicle cluster obtains environment state information; spatial constraint loss is calculated through a rectangular flight area limitation loss function module, time sequence consistency loss is calculated through a batch time sequence behavior constraint module, and the spatial constraint loss and the time sequence consistency loss are combined to generate a state behavior joint hidden variable fusing space and time sequence constraints. And fusing the hidden variable with the current environment state, inputting the fused hidden variable and the current environment state into a differential game value evaluation module, obtaining a future expected value based on Nash equilibrium by solving a differential game between our part and the black flight unmanned aerial vehicle, and updating decision network parameters based on the future expected value. The cluster performs the optimized hunting action and stores empirical data for continuous training. According to the method, the decision stability, the cooperation efficiency and the task success rate of unmanned aerial vehicle cluster hunting in the rectangular limited flight area are effectively improved.

The present application relates to the technical field of smart water affairs and urban public safety, and particularly relates to a kind of artificial intelligence driven urban pipe network flood resilience evaluation method and system, comprising: constructing Riemann metric tensor by using metric matrix containing potential barrier function, and establishing the Riemann manifold embedding space of pipe network physical state;Then, based on fluid energy, a Hamilton function is constructed, and a dynamics prediction model with physical conservation is obtained by using symplectic neural network and symplectic discrete integral format training;Subsequently, a second-order Hamilton-Jacobi-Aleksandrov partial differential equation describing stochastic differential game is constructed, and a physical perception neural network is used to solve and extract the resilience safety boundary;Finally, real-time data is mapped to the manifold space, the Riemann gradient is calculated, and a quadratic programming problem is solved to generate control instructions. The problem of lack of physical constraints and safety bottom line in pipe network control under extreme random working conditions is solved, and real-time closed-loop control with physical consistency is realized.

The invention discloses a synchronous orbit electric propulsion satellite short-range game control method based on differential game, which comprises the following steps: under an LVLH coordinate system, establishing a near-circular orbit relative motion dynamic model of spacecrafts of both pursuit and escape parties, and further determining a state space form in a spacecraft pursuit and escape game process; based on a state space form in a spacecraft pursuit game process, introducing a Hamiltonian function, and constructing a short-distance pursuit game model with optimal time; introducing a co-state equation, and describing a short-range pursuit game process as a two-point boundary value problem; and converting the problem into a parameter optimization problem, and carrying out optimization solution on the problem by utilizing an improved difference method so as to realize short-range game control.

This invention provides a spacecraft escort control method based on zero-sum differential games, belonging to the field of aerospace technology. The control method includes the following steps: obtaining spacecraft escort problem parameters for both the pursuing and defending satellites; establishing a spacecraft escort model based on zero-sum differential games and inputting initial parameters into the model; transforming the spacecraft escort model into a two-point boundary value problem model; using a genetic algorithm to solve the two-point boundary value problem model to obtain the state trajectory within the game time, thus completing the spacecraft escort control. This spacecraft escort control method can effectively solve the spacecraft escort problem under continuous thrust, and is an effective extension of existing continuous thrust escort problem models and methods. The model employs a differential game method described by a zero-sum cost function, thus simplifying the solution of the difficult-to-solve weighted performance index escort problem and improving the solution efficiency of the spacecraft escort game problem.

The present application relates to the technical field of robot tracking control, and discloses a kind of man-machine shared tracking control method based on differential game, comprising: establishing man-machine differential game model;Estimate human control strategy and objective function parameter;Design robot shared control strategy;To the shared control strategy determined by robot, realize man-machine shared tracking control;The present application uses differential dynamic game to model the dynamic negotiation relationship between human participants and robot, so that the robot adjusts its own willingness under the game framework by estimating the willingness of human to eliminate tracking error, and designs robot tracking control strategy on this basis;Further, the present application considers the safety of man-machine cooperation, designs robot safety control strategy based on control barrier function, so that it can realize safe shared control together with robot tracking control strategy.

The present invention discloses a method and device for solving the differential game capture zone of continuous and pulse guidance laws, comprising the following steps: considering the continuous or pulse maneuvers of both the pursuer and the escaper, establishing a two-dimensional plane pursuit model with zero-control miss distance as the state variable; introducing pursuit scenarios based on the differential game guidance law form of both parties; solving the differential game guidance law in different pursuit scenarios, and writing the continuous guidance law and the pulse guidance law in a unified form; solving the existence condition of the differential game solution based on the fact that the denominator of the guidance law is not zero; and solving the differential game capture zone in different scenarios. The differential game capture zone solution method in the present invention reveals the difference between the capture zones of pulse and continuous guidance laws, and can provide a theoretical basis for the selection of continuous and pulse differential game guidance parameters with different acceleration ratios and time constant ratios. The analysis method is simple and has a wide range of applications.

This invention relates to the field of network security technology and discloses a network security management method and system based on a big data model, comprising: Step 1, converting multi-source heterogeneous data into graph nodes containing device entities, IP entities, and user entities, as well as interaction edges containing timestamps and relationship types; Step 2, constructing a dynamic evolution equation for an attack chain based on the graph nodes and interaction edges, wherein the equation includes attacker action parameters and defender action parameters; Step 3, using the state variables corresponding to the dynamic evolution equation of the attack chain, inputting them into a time fusion Transformer model to obtain the probability distribution of future attack action sequences. This invention employs a technical solution based on a differential game model to construct a dynamic evolution equation for the attack chain, a time fusion Transformer to predict attack action sequences, and meta-reinforcement learning to dynamically update defense strategies, achieving the technical effects of accurately modeling attack evolution paths, predicting attack behavior in advance, and generating adaptive defense strategies in real time.

The application relates to the field of energy management, and discloses an energy consumption management optimization method and system of a comprehensive energy station, which are used for improving the economic optimization ability and the autonomous collaborative operation level of the comprehensive energy station when facing complex uncertainty. The energy consumption management optimization method of the comprehensive energy station comprises the following steps: constructing a device characteristic model representing long memory dynamics of a device based on a fractional calculus theory; establishing a random scene based on an alpha-stable distribution theory, which describes non-Gaussian fluctuations of wind and light loads; constructing an economic cost density field representing energy quality space-time dissipation based on a local entropy production minimization principle; establishing a differential game framework taking the economic cost field as a target and the above model as a constraint; and finally realizing closed-loop optimization through rolling execution and model online correction. The application breaks away from the dependence on a machine learning model, and realizes the economic efficiency optimization and autonomous collaborative operation of the energy station under complex uncertainty from the physical mechanism.

The invention discloses a differential game collaborative guidance method under data packet loss and time delay, which comprises the following steps of: after a data retransmission mechanism is introduced to establish a mapping relation between a packet loss probability and a time delay size, designing a proportional time delay accumulation error based on a neighbor node signal received by a missile node and a reference signal, and ensuring that the probability of packet loss is reduced in the error conversion mode; when the error converges to zero, the states of all the missiles can achieve cooperation. And respectively designing feed-forward and feedback control components by using the smoothed error in combination with instruction filtering inversion control and a differential game method so as to improve the robustness and the optimal performance of the designed guidance law. Meanwhile, for the problem that the optimal performance index function is difficult to solve in the feedback component design process, an evaluation network fitting performance index function is introduced in combination with an adaptive dynamic programming technology. According to the scheme, the error bounded property can be proved through the designed Lyapunov function, and the stability performance of a missile cluster using the guidance scheme under the condition of communication data packet probability loss and communication time delay is guaranteed.

The present application relates to a kind of main satellite of star companion under the spacecraft main satellite cooperative evasion control method, it is applied to the non-cooperative target such as space debris, malfunction spacecraft when facing unknown intention approach, task spacecraft is cooperated with star companion in the vicinity of orbit and carries out evasion in one pursuit one escape one guard scene.First, the dynamic model of relative motion state including non-cooperative target, guard satellite and task spacecraft is established;Then, the cost function of both sides of differential game is constructed using the idea of differential game;After that, the Hamilton-Jacobi method is used to solve Riccati equation, and the full-state linear feedback control solution of task spacecraft and satellite is obtained.The present application can avoid non-cooperative target approaching important on-orbit task spacecraft as much as possible, and assist task spacecraft to evade the potential threat of direct collision from the target through the active shielding of satellite, which is consistent with the engineering practice.

The present disclosure provides a spacecraft pursuit control method, device, computer equipment and medium, comprising: acquiring a reference orbit in a two-spacecraft pursuit process; determining a spacecraft on-orbit pursuit orbit dynamics model that meets perturbation factors in the two-spacecraft pursuit process based on the reference orbit in the two-spacecraft pursuit process; determining a spacecraft on-orbit pursuit differential game model based on the spacecraft on-orbit pursuit orbit dynamics model and preset countermeasure parameters in the two-spacecraft pursuit process; and determining a pursuit game control strategy of the two spacecrafts based on the spacecraft on-orbit pursuit differential game model. Thus, by constructing a spacecraft on-orbit pursuit orbit dynamics model that meets perturbation factors in the two-spacecraft pursuit process, a spacecraft on-orbit pursuit differential game model is determined, the operation efficiency of the spacecraft pursuit differential game is effectively improved, and the pursuit game control strategy of the two spacecrafts is easily formulated.

This application discloses a dynamic emergency decision-making method, device, equipment, and storage medium for urban flood disasters, relating to the field of emergency management and response scheduling technology. The method includes: first, establishing a differential equation for the safety state transition of an urban area, dividing the area into four safety states: normal, affected, recovering, and paralyzed, and defining their transition relationships; based on this, constructing a stochastic differential game model for flood disaster emergency decision-making; solving for the saddle point strategy using a forward-backward scanning algorithm to obtain the optimal emergency prevention and control strategy; then, conducting multi-dimensional simulation verification using typical flood disaster events as samples; finally, adjusting the strategy based on the simulation results to form a target emergency prevention and control strategy for actual emergency decision-making. This application can take into account both spatiotemporal dynamic characteristics and stochastic uncertainties in urban flood disaster emergency decision-making, achieving dynamic adaptation and continuous, efficient decision-making between the disaster system and the emergency response system.

The application discloses a heterogeneous multi-agent multi-target defense decision control method based on differential game. The method can comprise: determining an agent team in a three-dimensional half space, including a defender and an attacker; constructing a multi-target defense game environment model and a heterogeneous multi-agent dynamics model; determining a termination condition and a benefit function of the multi-target attack and defense game; constructing a single-to-single attack and defense confrontation optimal control strategy and a corresponding value function based on the differential game according to the multi-target defense game environment model and the heterogeneous multi-agent dynamics model; and determining multi-agent game scene task allocation according to the benefit function and the value function. The application utilizes the advantages of air-ground cooperation to improve the success rate of target area defense, provides strict theoretical derivation and mathematical proof for the target defense game of air units and ground units, solves the multi-to-multi target defense problem of a large number of agents, and has practicality in solving the actual application of air-ground cooperative combat tasks.

The invention belongs to the technical field of collaborative interception guidance, and particularly relates to a bias differential game collaborative interception method based on region coverage. The method comprises the steps of establishing a probability distribution model of a target in an interception plane, performing Monte Carlo sampling, and converting a coverage strategy design into an optimal coverage problem of a finite center point in the interception plane; segmenting, iteratively solving the standard maneuver of each interceptor through a Voronoi diagram method to obtain the standard maneuver aTsi of each interceptor; and based on the standard maneuvering aTsi of each interceptor, deploying to a corresponding optimal array position and carrying out offset item design of a differential game guidance law to jointly realize the offset of the coverage range of each interceptor, and finally completing the optimal coverage and interception of the target. According to the method provided by the invention, the defects that an existing disc coverage model has limitation on maneuvering distribution simplification and only a fixed solution can be applied mechanically are overcome; the miss distance and the overload demand of the interceptor are obviously reduced, and the interception efficiency is improved.

The invention provides a distributed energy storage and power scheduling method and device based on a master-slave game, and relates to the technical field of distributed energy storage management, and the method comprises the steps: obtaining the energy storage capacity of an energy storage unit in each time period of the whole day, and constructing a power distribution matrix of the energy storage unit according to the divided time periods; a differential game is adopted to set an energy storage dynamic equation, a target revenue function is set according to the energy storage dynamic equation, and a dynamic weight distribution mechanism is adopted to calculate weight parameters of the target revenue function. Double-layer nested time division is adopted to realize dynamic decoupling of power distribution and real-time power; the dimensionality of the optimization problem is reduced through matrix modeling, and the solving speed is increased in combination with dynamic weight distribution; the differential game drives the dynamic equation, depicts the real-time game behavior of the energy storage and the external environment, and achieves the improvement of earnings.

This invention provides a method and system for the emergence of bionic swarm trajectories for drones using a spatiotemporal gradient field. This method relates to the technical field of drone swarm collaborative navigation and adaptive control. The method involves generating a four-dimensional spatiotemporal gradient field tensor matrix through a dynamic field-coupled convolutional network. A set of bionic swarm interaction rules is constructed through nonlinear differential game modeling, combining density-velocity response data of fish school escape behavior and drone dynamic constraints. Individual drone trajectory basis functions are determined using a spatiotemporal finite element discretization method combined with GPU-accelerated parallel solution. Swarm reorganization instructions are generated through Lyapunov function optimization processing. Finally, a bionic swarm trajectory emergence scheme for drones, enabled by the spatiotemporal gradient field, is generated by integrating the updated spatiotemporal gradient field, swarm reorganization instructions, and historical trajectory data. This invention provides drone swarms with high-precision, low-latency, and robust autonomous navigation capabilities, thereby improving mission success rates.

The present invention relates to a mean field game optimization method and system in an edge computing network based on content popularity, comprising: (1) setting a system model; including setting an edge computing network, the edge computing network including a cloud data center, a plurality of edge nodes with storage units, and a plurality of users; (2) modeling the video service caching decision problem in the edge computing network as a stochastic differential game problem, i.e., an SDG problem, based on the remaining storage space status of each edge node and the state change of the task popularity based on the content popularity; (3) using the mean field game method to solve the above SDG problem, obtaining the Nash equilibrium of the video service caching decision problem in the edge computing network, and obtaining the optimal caching strategy of each edge node. The present invention focuses on satisfying user needs and takes into account the caching benefits of edge nodes.

The present invention relates to an anti-interference penetration game control method for a hypersonic aircraft, and belongs to the field of aerospace. First, a hypersonic aircraft penetration game model and a measurement error interference model are established; second, an interference observer is designed to estimate and compensate for the measurement error interference in the penetration game model in real time; then, a differential game three-dimensional guidance law is designed to achieve maneuver avoidance of the hypersonic aircraft; finally, the differential game guidance law and the anti-interference control law are combined to ensure the stability of the closed-loop system by reasonably selecting the observer and controller parameters. The present invention designs an anti-interference penetration game control algorithm based on differential game and interference observer, realizes intelligent penetration under measurement error interference through active maneuvering under the optimal strategy of both the attacking and defending sides, and improves the anti-interference capability and penetration efficiency of the hypersonic aircraft.

The invention provides a multi-unmanned-ship safe arrival-avoidance differential game controller. The multi-unmanned-ship safe arrival-avoidance differential game controller comprises an unmanned ship kinematics mathematical model unit, a region protection design unit, an optimal interception point solving unit, an optimal interception point selection unit, an unmanned ship optimal differential game strategy design unit, an unmanned ship safety constraint unit and an unmanned ship input constraint unit. According to the invention, the defense unmanned surface vehicle can protect the target area and intercept the attack unmanned surface vehicle. Firstly, an optimal interception point is calculated by using a geometric method, and an optimal game strategy is designed for two groups of unmanned ships based on a differential game idea. And secondly, based on a fixed time control obstacle function and speed constraint, optimizing the designed control strategy by solving a quadratic programming problem so as to ensure the safety of the system. And finally, an optimal safe game guidance law is constructed by using an auxiliary variable method, so that the under-actuated unmanned ship can effectively complete a protection task on the target area.

The application discloses a spacecraft escort problem solving method based on LQR and differential game, constructs a game model of the escort problem based on a CW equation, and comprises a cost function, optimization variables, dynamic constraints, acceleration capacity constraints and the like; the cost function adopts a linear quadratic index, the optimization variables are continuous control force accelerations of both attack and defense sides, the dynamic constraints are described by using the CW equation, and the acceleration capacity constraints are modeled by using maximum acceleration limitation; the method has the advantages of simple model, clear physical meaning and convenient solving; in addition, the application converts a complex non-zero-sum game problem into a phased zero-sum game problem and an optimal control problem, can effectively solve the spacecraft escort problem under the action of continuous thrust, is an effective expansion of a continuous thrust escort problem model and method in the prior art, and significantly improves the solving efficiency of the problem. Through the method, an effective cooperative defense threat solution can be provided for on-orbit spacecraft.

This invention discloses a fault-tolerant game-theoretic control method for quadrotor helicopter swarm formations. It designs a quadrotor helicopter swarm formation mode, constructs an information interaction topology graph of the helicopter swarm, and establishes fault models for the rotating and translational subsystems. An adaptive fault diagnosis observer is designed to estimate actuator faults. Using the translational subsystem as the leader and the rotating subsystem as the follower, an inner and outer loop fault-tolerant game framework based on an incentive-based Steinberg differential graph game is constructed. Through full-drive system theory, fault-tolerant game controllers for the rotating and translational subsystems are designed separately, and a linear closed-loop system of the quadrotor helicopters is constructed. Performance indices for the rotating and translational subsystems are designed, and an optimal fault-tolerant game-theoretic control strategy is designed based on differential game theory. This invention enables stable formation control of quadrotor helicopter swarms, effectively improves the fault tolerance of helicopter swarms, and enhances the stability and intelligence of the helicopter swarm system.

The invention belongs to the technical field of man-machine cooperative control, and particularly relates to a man-machine sharing control method for an exogenous input system under Nash equilibrium, which comprises the following steps of: constructing a man-machine sharing control system model with exogenous input items, and setting a cost function of man-machine parties; a man-machine non-cooperative differential game model is considered, an information structure of man-machine interaction meets a closed-loop perfect state mode, a control target is Nash equilibrium between cost functions of the two parties, and a Nash equilibrium solution form of human and machine control input and an algorithm of control gain and additional items are provided; based on fuzziness and uncertainty of human input, constructing an adaptive observer, and combining a Lyapunov equation to obtain a human input estimation gain and an updating law of an additional item; the real-time Nash equilibrium solution of man-machine sharing control in an exogenous input system is provided while the influence of exogenous input on the system state is restrained, and the method has high scientific significance and application value.

The application provides a kind of Internet of Things botnet DDoS attack defense method, device and storage medium, it is related to Internet of Things technical field, by the conversion relationship between sleeping device, normal device, latent device and attack device is constructed botnet DDoS attack attack-defense differential game model;Calculate attacker legal packet loss income, defender legal packet loss loss and attack cost and defense cost;According to the attacker legal packet loss income, defender legal packet loss loss and attack cost and defense cost, build instantaneous payment function;Solve the equilibrium solution of attack-defense zero-sum differential game model, obtain optimal saddle point strategy, analyze DDoS attack in Internet of Things botnet from the overall and dynamic point of view, to control the traffic that can be within the scope of victim processing to reach victim, while reducing the security loss of Internet of Things attack-defense system to a lower level.

The invention discloses a wheel-legged all-terrain chassis longitudinal and transverse movement game optimization method, which comprises the following steps: constructing a wheel-legged all-terrain chassis longitudinal and transverse game optimization framework, the wheel-legged all-terrain chassis longitudinal and transverse game optimization framework comprises an information layer, a distribution optimization layer and an execution layer; in a distribution optimization layer of the game optimization framework, constructing a differential game optimization model, abstracting AFS and DYC into two rational game parties based on a game theory, and finally outputting performance game optimization distribution optimal values of the two parties; and inputting vehicle and road data collected from an information layer into the differential game optimization model, calculating an optimal distribution optimal value of AFS and DYC, sending a control instruction at a distribution optimization layer, realizing the control instruction at an execution layer, and achieving a coupling optimization target of longitudinal and transverse movement of an agricultural machinery chassis. According to the method, through differential game modeling, control quantity distribution is optimized, so that the longitudinal performance of the chassis of the hill agricultural machine is guaranteed, the yawing moment can be generated, and stability control and energy consumption optimization are achieved.