Mean Square Stability of the Composite Milstein Method for Nonlinear Stochastic Differential Delay Equations

In this paper, we construct a composite Milstein method for nonlinear stochastic differential delay equations. Then we analyze the mean square stability for this method and obtain the step size condition under which the composite Milstein method is mean square stable. Moreover, we get the step size condition under which the composite Milstein method is global mean square stable. A nonlinear test stochastic differential delay equation is given for numerical tests. The results of numerical tests verify the theoretical results proposed.

A Fiber Optic Sensor for 2,4-dichlorophenol Analysis based on Optical Composite Oxygen-sensitive Film

A novel fiber optic sensor based on optical composite oxygen-sensitive film was developed for determination of 2,4-dichlorophenol(DCP).The optical composite oxygen-sensitive film consists of tris(2,2’-bipyridyl)dichloro ruthenium(II)hexahydrate(Ru(bpy)3Cl2)as the fluorescence indicator and iron(III)tetrasulfophthalocyanine(Fe(III)PcTs)as bionic enzyme.A lock-in amplifier was used for detecting the lifetime of the composite oxygen-sensitive film by measuring the phase delay of the sensor head.The different variables affecting the sensor performance were evaluated and optimized.Under the optimal conditions(i e,pH 6.0,25℃,Fe(III)PcTs concentration of 5.0×10^-5 mol/L),the linear detection range,detection limit and response time of the fiber optic sensor are 3.0×10^-7-9.0×10^-5 mol/L,4.8×10^-8 mol/L(S/N=3),and 220 s,respectively.The sensor displays high selectivity,good repeatability and stability,which have good potentials in analyzing DCP concentration in practical water samples.

A Composite State Convergence Scheme for Bilateral Teleoperation Systems

State convergence is a novel control algorithm for bilateral teleoperation of robotic systems. First, it models the teleoperation system on state space and considers all the possible interactions between the master and slave systems. Second, it presents an elegant design procedure which requires a set of equations to be solved in order to compute the control gains of the bilateral loop. These design conditions are obtained by turning the master-slave error into an autonomous system and imposing the desired dynamic behavior of the teleoperation system. Resultantly, the convergence of master and slave states is achieved in a well-defined manner. The present study aims at achieving a similar convergence behavior offered by state convergence controller while reducing the number of variables sent across the communication channel. The proposal suggests transmitting composite master and slave variables instead of full master and slave states while keeping the operator's force channel intact. We show that,with these composite and force variables;it is indeed possible to achieve the convergence of states in a desired way by strictly following the method of state convergence. The proposal leads to a reduced complexity state convergence algorithm which is termed as composite state convergence controller. In order to validate the proposed scheme in the absence and presence of communication time delays, MATLAB simulations and semi-real time experiments are performed on a single degree-of-freedom teleoperation system.

Observer-based Adaptive Iterative Learning Control for Nonlinear Systems with Time-varying Delays

An observer-based adaptive iterative learning control （AILC） scheme is developed for a class of nonlinear systems with unknown time-varying parameters and unknown time-varying delays. The linear matrix inequality （LMI） method is employed to design the nonlinear observer. The designed controller contains a proportional-integral-derivative （PID） feedback term in time domain. The learning law of unknown constant parameter is differential-difference-type, and the learning law of unknown time-varying parameter is difference-type. It is assumed that the unknown delay-dependent uncertainty is nonlinearly parameterized. By constructing a Lyapunov-Krasovskii-like composite energy function （CEF）, we prove the boundedness of all closed-loop signals and the convergence of tracking error. A simulation example is provided to illustrate the effectiveness of the control algorithm proposed in this paper.

数字化脉冲延时器

较详细介绍了数字化脉冲延时器的性能指标,工作原理及电路特点。还阐述了采用CL602六位多功能计数组合电路作为本机的定时单元概况。

一种新型高段延期药的研制及应用

文中采用一种新型缓燃剂,调整合适的配比,代替铅丹—硅系延期药中的硫化锑,组合成一种新型延期药剂。该药剂具有良好的化学安定性和长储稳定性,良好的耐高温高湿性和可靠的火焰感度,成本低廉,工艺简单,代替通常高段别使用的钨系延期药,有很高的实际应用价值。

Decomposing a Kind of Weakly Invertible Finite Automata with Delay 2

Some properties of a finite automaton composed of two weakly invertible finite automata with delay 1 are given, where each of those two automata has the output set of each state with the same size. And for a weakly invertible finite automaton M with delay 2 satisfying the properties mentioned in this paper, two weakly invertible finite automata with delay 1 are constructed such that M is equivalent to a sub-finite-automaton of the composition of those two. So a method to decompose this a kind of weakly invertible finite automata with delay 2 is presented.

Adaptive Iterative Learning Control for Nonlinearly Parameterized Systems with Unknown Time-varying Delay and Unknown Control Direction

This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separation technique and signal replacement mechanism,the approach can overcome unknown time-varying parameters and unknown time-varying delay of the nonlinear systems.By incorporating a Nussbaum-type function,the proposed approach can deal with the unknown control direction of the nonlinear systems.Based on a Lyapunov-Krasovskii-like composite energy function,the convergence of tracking error sequence is achieved in the iteration domain.Finally,two simulation examples are provided to illustrate the feasibility of the proposed control method.