A quasi - newton method on convex optimization 求解凸規(guī)劃問題的一種擬牛頓算法
For some special cases , the deterministic convex optimization problems are derived 對(duì)某些特殊的情形,我們導(dǎo)出了魯棒線性最優(yōu)化的確定性等價(jià)問題。
This paper presents an interior trust region method for linear constrained lc ^ 1 convex optimization problems 摘要本文提出一種解線性約束凸規(guī)劃的數(shù)值方法。
Then by building and solving the convex optimization problem , the optimal upper bound of performance index and parameters of the state feedback controller is given 通過(guò)建立、求解凸優(yōu)化問題得到最優(yōu)極小極大控制器參數(shù)和性能指標(biāo)的最小上界。
Abstract : this paper considers the decentralized stabilization problem via local state feedback control laws for a class of large - scale linear discrete - time systems with delay interconnections . a sufficient condition for decentralized stabilizability is derived and is expressed as a system of linear matrix inequalities . furthermore , the problem of designing a decentralized state feedback control law with smaller feedback gain parameters is formulated as a convex optimization problem , and latter can be solved by using existing efficient convex optimization techniques . the obtained controller enables the closed - loop systems to be not only stable , but also of any prescribed stability degree 文摘:用一組線性矩陣不等式給出一類線性離散時(shí)滯大系統(tǒng)分散能鎮(zhèn)定的一個(gè)充分條件,進(jìn)而,通過(guò)建立和求解一個(gè)凸優(yōu)化問題,提出了具有較小反饋增益參數(shù)的分散穩(wěn)定化狀態(tài)反饋控制律的設(shè)計(jì)方法.所得到的控制器不僅使得閉環(huán)系統(tǒng)是穩(wěn)定的,而且還可以使得閉環(huán)系統(tǒng)狀態(tài)具有給定的衰減度
Convex minimization, a subfield of optimization, studies the problem of minimizing convex functions over convex sets. The convexity property can make optimization in some sense "easier" than the general case - for example, any local minimum must be a global minimum.