Abstract: The present disclosure provides a design method for an active disturbance rejection roll controller of a vehicle under disturbance of complex sea conditions, including: step 1: establishing a vehicle roll attitude control model; step 2: designing an active disturbance rejection controller (ADRC) on the basis of the control model in step 1 and a pole placement method; and step 3: performing an active disturbance rejection roll control by using the active disturbance rejection controller in step 2. The present disclosure solves the problem of a stable control of the vehicle under the disturbance of the complex sea conditions.

Abstract: The present disclosure provides a design method for an active disturbance rejection roll controller of a vehicle under disturbance of complex sea conditions, including: step 1: establishing a vehicle roll attitude control model; step 2: designing an active disturbance rejection controller (ADRC) on the basis of the control model in step 1 and a pole placement method; and step 3: performing an active disturbance rejection roll control by using the active disturbance rejection controller in step 2. The present disclosure solves the problem of a stable control of the vehicle under the disturbance of the complex sea conditions.

Abstract: An intelligent ammunition co-evolution task assignment method is disclosed. The method includes the following steps. A chromosome gene encoding of genetic algorithm for ammunition assignment scheme of multi-platform interception operation is performed. A fitness of chromosome individual function in a genetic population is calculated according to a threat degree of an intercepting target in the ammunition assignment scheme and an interception probability of the intercepting target by different ammunition launching platforms. A probability ranking sequence of effective interception of the intercepting target by different ammunition launching platforms is obtained, and a genetic algorithm selection operation is performed on the chromosome individuals according to probability values of effective interception in descending order of priority.

Abstract: A three-dimensional track planning method based on improved particle swarm optimization algorithm is disclosed. During the process of searching an optimal three-dimensional track in a track space, Different inertia weights are set in different particle swarm iterative evolution stages. A maximum inertia weight is used to make global convergence in a set early stage of evolution, and a minimum inertia weight is used to make local convergence in a set late stage of evolution. Disturbance mutation operation in a motion process of particles is added based on swarm diversity. Infeasible particles are selected based on constraints. Constraint violation functions of infeasible particles are compared, and infeasible particles with small constraint violation functions are kept.