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由于风力机独立变桨距控制系统是一个多变量、非线性以及带有时变性的控制系统,为了解决该复杂控制系统中多变量之间的耦合问题,在传统PID变桨控制的基础上提出了多桨耦合协调控制策略,并将仿真结果与传统PID变桨控制进行对比,仿真结果表明:基于协调控制技术的变桨控制系统变桨同步性大幅提高,且具有更高的变桨精度。 相似文献
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目的解决传统电弧喷涂送丝机的局限性,特别是柔性送丝结构存在的送丝速率低、送丝波动大等问题。方法设计了刚性送丝结构,进而成功研制了高稳定性电弧喷涂刚性送丝机,并通过送丝速率测试、喷涂电流测试及喷涂焰流观察等对比性试验,验证了设计的有效性和可行性。结果在无喷涂状态下,传统柔性送丝机和文中研制的刚性送丝机的送丝速率均随送丝电压的增大而增大,且刚性送丝速率呈近似线性变化趋势,而柔性送丝速率具有一定随机性。在相同送丝电压下,刚性送丝的速率高于柔性送丝,即具有更小的送丝阻力;且刚性送丝机两侧丝材送进平均速率的同步误差均小于3%,而柔性送丝机的同步误差为5%左右,说明刚性送丝机具有较好的送丝同步性。同时,柔性送丝机的送丝速率波动率为10%左右,而刚性送丝机的仅为2%左右,说明刚性送丝机在无喷涂状态下具有优异的送丝稳定性。在喷涂状态下,刚性送丝机和柔性送丝机的喷涂电流波动率分别为4.76%和29.36%,且刚性送丝机的喷涂焰流比柔性送丝机的更加集中稳定,说明刚性送丝机在喷涂状态下也能保持良好的送丝稳定性。结论刚性送丝结构可以有效减小送丝机的送丝阻力并保证两侧丝材送进的同步性,使送丝过程具有更高的稳定性。 相似文献
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本文研究以加工–运输–装配同步性和交货准时性的加权和为优化目标的三阶段装配集成调度问题(3sAISPSP),并基于问题特点设计混合分布估计算法(HEDA)进行求解.首先,分别建立3sAISP SP的数学规划模型和排列模型.其次,在对问题模型特点分析的基础上,设计合理的编码和解码规则,同时利用HEDA中基于概率模型的全局搜索以发现问题解空间存在优质解的区域.然后,为进一步提高算法性能,设计3种局部搜索策略对优质解区域进行细致搜索.进而,在小规模问题下,将HEDA得到的较优解与优化求解器GUROBI得到的最优解进行比较,验证HEDA的求解结果接近最优解;在较大规模问题下,将HEDA与其他有效智能优化算法进行比较,验证HEDA的求解性能.最后,通过对优化目标中不同权重设置的实验分析,给出加工–运输–装配同步性和交货准时性权重设置的合理范围,并得到考虑装配同步性有利于降低中间库存的结论. 相似文献
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针对Modbus/TCP协议的安全缺陷,基于密码学技术提出一种安全的Modbus协议(Sec_Modbus协议):采用对称加密和数字签名技术实现保密性要求及认证,利用同步性原理和哈希函数的单向性设计基于哈希链的防重放方法,通过随机函数产生索引号动态指定通信密钥,最终在不增加通信过程的情况下实现安全通信。实验结果表明:Sec_Modbus协议能够防止攻击者针对指令的认证类攻击、中间人攻击及重放攻击,与已有方法相比,该方法不仅安全性更高,且具有更好的时间性能,能更好地满足工业控制系统对安全性及实时性的要求。 相似文献
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The discovery of chaos in the sixties of last century was a breakthrough in concept,revealing the truth that some disorder behavior,called chaos,could happen even in a deterministic nonlinear system under barely deterministic disturbance.After a series of serious studies,people begin to acknowledge that chaos is a specific type of steady state motion other than the conventional periodic and quasi-periodic ones,featuring a sensitive dependence on initial conditions,resulting from the intrinsic randomness of a nonlinear system itself.In fact,chaos is a collective phenomenon consisting of massive individual chaotic responses,corresponding to different initial conditions in phase space.Any two adjacent individual chaotic responses repel each other,thus causing not only the sensitive dependence on initial conditions but also the existence of at least one positive top Lyapunov exponent(TLE) for chaos.Meanwhile,all the sample responses share one common invariant set on the Poincaré map,called chaotic attractor,which every sample response visits from time to time ergodically.So far,the existence of at least one positive TLE is a commonly acknowledged remarkable feature of chaos.We know that there are various forms of uncertainties in the real world.In theoretical studies,people often use stochastic models to describe these uncertainties,such as random variables or random processes.Systems with random variables as their parameters or with random processes as their excitations are often called stochastic systems.No doubt,chaotic phenomena also exist in stochastic systems,which we call stochastic chaos to distinguish it from deterministic chaos in the deterministic system.Stochastic chaos reflects not only the intrinsic randomness of the nonlinear system but also the external random effects of the random parameter or the random excitation.Hence,stochastic chaos is also a collective massive phenomenon,corresponding not only to different initial conditions but also to different samples of the random parameter or the random excitation.Thus,the unique common feature of deterministic chaos and stochastic chaos is that they all have at least one positive top Lyapunov exponent for their chaotic motion.For analysis of random phenomena,one used to look for the PDFs(Probability Density Functions) of the ensemble random responses.However,it is a pity that PDF information is not favorable to studying repellency of the neighboring chaotic responses nor to calculating the related TLE,so we would rather study stochastic chaos through its sample responses.Moreover,since any sample of stochastic chaos is a deterministic one,we need not supplement any additional definition on stochastic chaos,just mentioning that every sample of stochastic chaos should be deterministic chaos.We are mainly concerned with the following two basic kinds of nonlinear stochastic systems,i.e.one with random variables as its parameters and one with ergodical random processes as its excitations.To solve the stochastic chaos problems of these two kinds of systems,we first transform the original stochastic system into their equivalent deterministic ones.Namely,we can transform the former stochastic system into an equivalent deterministic system in the sense of mean square approximation with respect to the random parameter space by the orthogonal polynomial approximation,and transform the latter one simply through replacing its ergodical random excitations by their representative deterministic samples.Having transformed the original stochastic chaos problem into the deterministic chaos problem of equivalent systems,we can use all the available effective methods for further chaos analysis.In this paper,we aim to review the state of art of studying stochastic chaos with its control and synchronization by the above-mentioned strategy. 相似文献