| With the increasing complexity of control objects,the control function of the system needs to be diversified,which puts forward new requirements for the research of multidimensional system.The dimension of the multidimensional system state-space realization is not only related to the computational complexity,but also directly affects the operating cost of the actual system.Therefore,it's of great theoretical and practical significance to carry out the research on the realization of multidimensional systems based on multiple independent variables.To further carry out the accurate simulation for real systems,the applicant is going to propose a novel realization approach to the multi-dimensional N-order system based on Fornasini-Marchesini II(F-M II)model to address these problems.It uses of the previous state and the input associated with it to control the current state.The property of this kind of local computation not only greatly simplifies the mathematical expression of the multi-dimensional system,but also makes the analysis of the system convenient.The realization of low order is closely related to the computational complexity,but also directly affects the actual system of the operating costs.F-M II state-space model is a common multi-dimensional system model based on practical engineering problems.Therefore,it's of great theoretical and practical significance to carry out the research on the realization of F-M II state-space model.Based on the F-M II model,this paper proposes a new method of matrix transformation based on multidimensional system theory,which makes the F-M II achieve a lower and easier matrix achieve.The property of this kind of local computation can reduce effectively simplify the computational complexity and the realization order and solve the lengthiness of time-consuming.In addition,this paper discusses the feasibility of modeling the grid wireless sensor network with the F-M II state space model and analyzes the real-time implementation problem of the F-M II model which is based on the practical application of wireless sensor network. |