Multi-model predictive control with local constraints based on model switching

Because model switching system is a typical form of Takagi-Sugeno（T-S） model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical （MLD） system and use it in model predictive control （MPC） in this paper. Considering that each local model is only valid in each local region,we add local constraints to local models. The stability of proposed multi-model predictive control （MMPC） algorithm is analyzed, and the performance of MMPC is also demonstrated on an inulti-multi-output（MIMO） simulated pH neutralization process.

Functionally Graded Cellular Structure Design Using the Subdomain Level Set Method with Local Volume Constraints

Functional graded cellular structure(FGCS)usually shows superiormechanical behaviorwith lowdensity and high stiffness.With the development of additivemanufacturing,functional graded cellular structure gains its popularity in industries.In this paper,a novel approach for designing functionally graded cellular structure is proposed based on a subdomain parameterized level set method(PLSM)under local volume constraints(LVC).In this method,a subdomain level set function is defined,parameterized and updated on each subdomain independently making the proposed approach much faster and more cost-effective.Additionally,the microstructures on arbitrary two adjacent subdomains can be connected perfectly without any additional constraint.Furthermore,the local volume constraint for each subdomain is applied by virtue of the augmented Lagrange multiplier method.Finally,several numerical examples are given to verify the correctness and effectiveness of the proposed approach in designing the functionally graded cellular structure.From the optimized results,it is also found that the number of local volume constraints has little influence on the convergence speed of the developed approach.

Influence of local environmental target constraints on enterprise OFDI

By collecting the environmental target constraints in the annual government work report of prefecture-level cities,this paper studies its impact on local enterprises’OFDI.The main conclusions are as follows:(1)Both direct and indirect constraints have a significant positive impact on enterprises’OFDI,and the degree of direct constraints is stronger than that of indirect constraints.(2)Environmental target constraints of local governments will affect corporate OFDI behavior by affecting production costs,local economic development level and local openness,and(3)There are regional heterogeneity and investment type heterogeneity in the impact of environmental goal constraints on corporate OFDI.The suggestions are as follows:government departments can appropriately strengthen the constraint intensity of environmental targets and formulate specific restraint rules for industries with different levels of pollution,so as to effectively make use of the technology spillover effects brought about by OFDI to promote the upgrading of domestic industrial structure.When making OFDI,enterprises should clarify the investment motivation,strengthen corporate social responsibility,and make use of technology spillover effect to promote the upgrading and development of home country industry while being beneficial to their own development.

Distributed cooperative localization for sparse communication network with multi-locating messages

In cooperative localization with sparse communication networks, an agent maybe only receives part of locating messages from the others. It is difficult for the receiver to utilize the part instead of global knowledge. Under the extended Kalman filtering, the utilization of the locating message is maximized by two aspects： the locating message generating and multi-locating messages fusing. For the former, the covariance upper-bound technique, by introducing amplification coefficients, is employed to remove the dependency of locating messages on the global knowledge. For the latter, an optimization model is setup; the covariance matrix determinant of the receiver＇s state estimate, expressed as a function of the amplification coefficients, is selected as the optimization criterion, under linear constraints on the amplification coefficient characteristics and the communication connectivity. Using the optimization solution, the local optimal state of the receiver agent is obtained by the weighting fusion. Simulation with seven agents is shown to evaluate the effectiveness of the proposed algorithm.

Three-dimensional gravity inversion based on optimization processing from edge detection

Gravity inversion requires much computation,and inversion results are often non-unique.The first problem is often due to the large number of grid cells.Edge detection method,i.e.,tilt angle method of analytical signal amplitude(TAS),helps to identify the boundaries of underground geological anomalies at different depths,which can be used to optimize the grid and reduce the number of grid cells.The requirement of smooth inversion is that the boundaries of the meshing area should be continuous rather than jagged.In this paper,the optimized meshing strategy is improved,and the optimized meshing region obtained by the TAS is changed to a regular region to facilitate the smooth inversion.For the second problem,certain constraints can be used to improve the accuracy of inversion.The results of analytic signal amplitude(ASA)are used to delineate the central distribution of geological bodies.We propose a new method using the results of ASA to perform local constraints to reduce the non-uniqueness of inversion.The guided fuzzy c-means(FCM)clustering algorithm combined with priori petrophysical information is also used to reduce the non-uniqueness of gravity inversion.The Open Acc technology is carried out to speed up the computation for parallelizing the serial program on GPU.In general,the TAS is used to reduce the number of grid cells.The local weighting and priori petrophysical constraint are used in conjunction with the FCM algorithm during the inversion,which improves the accuracy of inversion.The inversion is accelerated by the Open Acc technology on GPU.The proposed method is validated using synthetic data,and the results show that the efficiency and accuracy of gravity inversion are greatly improved by using the proposed method.

Influence of cyclic dynamic disturbance on damage evolution and zoning effect of coal-rock under local static load constraint

In order to obtain the characteristics of the effects of cyclic impact loading on the damage of coal-rock in the presence of a local static load constraint,the evolution of the damage factor and the fracture rate during the process and incremental cyclic impact on raw coal and briquettes has been studied.Experimental results show that the presence of local static load restraint improves the impact resistance of the coal-rock,and the damage factor of the coal-rock shows obvious zoning characteristics.When the coal-rock is in an elastic state,the partition with a larger static load restraint area has stronger impact resistance,when the coal-rock is in a plastic state,the partition with a larger static load restraint area has a weaker impact resistance.Increasing impulsive cyclic impacts have a higher damage efficiency to coal-rock than constant impulsive cyclic impacts.The difference in rock breaking efficiency between the two cyclic impact methods is mainly reflected in the partition with the largest constrained area.The crack propagation on the coal-rock surface is more consistent with the partition characteristics of the damage factor.When the static load constrained zone is in an elastic state,the static load has an inhibitory effect on the crack growth.When the static load confinement zone is in a plastic state,the cracks mainly propagate in the static load confinement zone,and the constrained zone mainly consists of tensile cracks that grow in the vertical direction,while the cracks in the non-constrained zone mainly grow in an oblique direction.Finally,fracture mechanics was applied to analyze the failure type of the sample.

Detecting Designated Building Areas From Remote Sensing Images Using Hierarchical Structural Constraints

Automatic detection of a designated building area(DBA)is a research hotspot in the field of target detection using remote sensing images.Target detection is urgently needed for tasks such as illegal building monitoring,dynamic land use monitoring,antiterrorism efforts,and military reconnaissance.The existing detection methods generally have low efficiency and poor detection accuracy due to the large size and complexity of remote sensing scenes.To address the problems of the current detection methods,this paper presents a DBA detection method that uses hierarchical structural constraints in remote sensing images.Our method was conducted in two main stages.(1)During keypoint generation,we proposed a screening method based on structural pattern descriptors.The local pattern feature of the initial keypoints was described by a multilevel local pattern histogram(MLPH)feature;then,we used one-class support vector machine(OC-SVM)merely to screen those building attribute keypoints.(2)To match the screened keypoints,we proposed a reliable DBA detection method based on matching the local structural similarities of the screened keypoints.We achieved precise keypoint matching by calculating the similarities of the local skeletal structures in the neighboring areas around the roughly matched keypoints to achieve DBA detection.We tested the proposed method on building area sets of different types and at different time phases.The experimental results show that the proposed method is both highly accurate and computationally efficient.