随机变量导致工程问题具有不确定性.设计者希望设计方案不仅能满足目标性能最优,而且希望目标性能受不确定性的影响在可接受范围之内.对此,本文提出了考虑灵敏度区域的多目标鲁棒性优化方法(multi-objective robust optimization based ...随机变量导致工程问题具有不确定性.设计者希望设计方案不仅能满足目标性能最优,而且希望目标性能受不确定性的影响在可接受范围之内.对此,本文提出了考虑灵敏度区域的多目标鲁棒性优化方法(multi-objective robust optimization based on sensitivity region,SR–MORO).SR–MORO可以用来解决设计变量存在不确定性时目标鲁棒性优化设计问题.该方法假定不确定性变量属于区间变量,并不需要知道随机变量的概率分布.SR–MORO采用非梯度优化方法,所以,它可以解决目标函数和约束条件不连续的情况.当参数变化幅度大,超过目标函数线性变化范围,该方法也同样适用.最后,通过实例验证了本方法的适用性.展开更多
Addresses the design problems of robust L2-L∞ filters with pole constraint in a disk for uncertain continuous-time linear systems. The uncertain parameters are assumed to belong to convex bounded domains. The aim is ...Addresses the design problems of robust L2-L∞ filters with pole constraint in a disk for uncertain continuous-time linear systems. The uncertain parameters are assumed to belong to convex bounded domains. The aim is to determine a stable linear filter such that the filtering error system possesses a prescribed L2-L∞ noise attenuation level and expected poles location. The filtering strategies are based on parameter-dependent Lyapunov stability results to derive new robust L2-L∞ performance criteria and the regional pole placement conditions. From the proposed multi-objective performance criteria, we derive sufficient conditions for the existence of robust L2-L∞ filters with pole constraint in a disk, and cast the filter design into a convex optimization problem subject to a set of linear matrix inequality constraints. This filtering method exhibits less conservativeness than previous results in the quadratic framework. The advantages of the filter design procedures are demonstrated by means of numerical examples.展开更多
文摘随机变量导致工程问题具有不确定性.设计者希望设计方案不仅能满足目标性能最优,而且希望目标性能受不确定性的影响在可接受范围之内.对此,本文提出了考虑灵敏度区域的多目标鲁棒性优化方法(multi-objective robust optimization based on sensitivity region,SR–MORO).SR–MORO可以用来解决设计变量存在不确定性时目标鲁棒性优化设计问题.该方法假定不确定性变量属于区间变量,并不需要知道随机变量的概率分布.SR–MORO采用非梯度优化方法,所以,它可以解决目标函数和约束条件不连续的情况.当参数变化幅度大,超过目标函数线性变化范围,该方法也同样适用.最后,通过实例验证了本方法的适用性.
文摘Addresses the design problems of robust L2-L∞ filters with pole constraint in a disk for uncertain continuous-time linear systems. The uncertain parameters are assumed to belong to convex bounded domains. The aim is to determine a stable linear filter such that the filtering error system possesses a prescribed L2-L∞ noise attenuation level and expected poles location. The filtering strategies are based on parameter-dependent Lyapunov stability results to derive new robust L2-L∞ performance criteria and the regional pole placement conditions. From the proposed multi-objective performance criteria, we derive sufficient conditions for the existence of robust L2-L∞ filters with pole constraint in a disk, and cast the filter design into a convex optimization problem subject to a set of linear matrix inequality constraints. This filtering method exhibits less conservativeness than previous results in the quadratic framework. The advantages of the filter design procedures are demonstrated by means of numerical examples.
