Robust fuzzy observer-based tracking control of natural resource management for spatial agricultural systems

Ying-Po Lin, Chen, Bor-Sen

System Science and Engineering(2011)

引用 0|浏览2
暂无评分
摘要
Natural resource management (NRM) has become an important global issue, due to the increasing population and human activities. Natural ecosystems are exposed to spatial environmental factors and unexpected stochastic disturbances may occur in ecosystems, with concomitant losses or gains of ecological and economic resources. Such spatial environmental factors and disturbances may impede management and recovery strategies for natural resources. In drylands, the water-limited ecosystem, vegetation is strikingly patterned, showing a heterogeneous distribution which has an adverse effect on agriculture productivity. In this study, a robust fuzzy observer-based tracking controller is designed to manage the productivity in spatial agricultural systems under stochastic disturbances. A fuzzy spatial state space model derived via finite difference approach is introduced to represent the nonlinear spatial agricultural system. Based on this model, a fuzzy robust observer-based tracking controller is proposed to control nonlinear spatial agricultural system to track a desired reference trajectory. The main objective of this work is to provide a robust tracking control to efficiently manage nonlinear spatial agricultural systems with stochastic disturbances in the fields to achieve some desired nature resource management or recovery.
更多
查看译文
关键词
agriculture,ecology,finite difference methods,fuzzy control,observers,robust control,agriculture productivity,finite difference approach,fuzzy spatial state space model,natural ecosystems,natural resource management,robust fuzzy observer-based tracking control,spatial agricultural systems,spatial environmental factors,stochastic disturbances,vegetation,water-limited ecosystem,fuzzy interpolation method,robust tracking control,spatial state space model,water resources,finite difference,biomass,robustness,state space model
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要