On Constrained MMVC of Discrete‐Time First‐Order Linear Stochastic Systems with PSI I: The Critically Stable Case

This paper is devoted to the study of the modified minimal variance control (MMVC) of discrete‐time first‐order linear critically stable stochastic systems with prospective strong intervention (PSI) and control input constraints. Due to different evolutionary characteristics of systems with PSI, that is, the two modes of tending to infinity and having bounded oscillations, the discrete‐time first‐order linear critically stable systems can be partitioned into two types regarding the signs of a key system parameter a. A necessary and sufficient condition for the state mean convergence of a system with a = 1 is derived and the corresponding design of MMVC is formulated. For the critical stable system with a =? 1, its oscillation amplitudes of state means can be effectively suppressed or the means can converge under control. Finally, the effectiveness and advantages of the proposed control strategies comparing with MVC are confirmed by numerical simulations.     

A Saturating Extension of an Output Feedback Controller for Internally Damped Euler‐Lagrange Systems

In this research, a novel extension of the passivity‐based output feedback trajectory tracking controller is developed for internally damped Euler‐Lagrange systems with input saturation. Compared with the previous output feedback controllers, this new design of a combined adaptive controller‐observer system will reduce the risk of actuator saturation effectively via generalized saturation functions. Semi‐global uniform ultimate boundedness stability of the tracking errors and state estimation errors is guaranteed by Lyapunov stability analysis. An application of the proposed saturated output feedback controller is the stabilization of a nonholonomic wheeled mobile robot with saturated actuators towards desired trajectories. Simulation results are provided to illustrate the efficiency of the proposed controller in dealing with the actuator saturation.     

Adaptive Motion/Force Tracking Control for a Class of Mobile Manipulators

In this paper, modeling and adaptive motion/force tracking control is considered for a class of mobile manipulators under the holonomic and affine constraints with the presence of uncertainties and disturbances. Based on a suitable reduced dynamic model, adaptive controllers are proposed to ensure that the states of a closed‐loop system asymptotically track desired trajectories while the constraint force remains bounded by tuning design parameters. Detailed simulation results confirm the effectiveness of the control strategy.     

Robust‐Adaptive Control Strategies for a Time Delay Bioelectrochemical Process Using Interval Observers

The paper addresses the design and the analysis of adaptive and robust‐adaptive control strategies for a complex recycled wastewater treatment bioprocess. The design procedures are developed under the realistic assumptions that the bacterial growth rates are unknown and the influent flow rates are time‐varying and uncertain, but some lower and upper bounds of these uncertainties are known. The proposed control structures are achieved by combining a linearizing control law with an appropriately (asymptotic or interval based) state observer and with a parameter estimator used for on‐line estimation of unknown kinetics. These approaches are applied to a complex time delay bioprocess resulting from the association of a recycling bioreactor with an electrochemical reactor. Numerical simulations are performed in order to validate the proposed algorithms.     

A new robust observer-based adaptive type-2 fuzzy control for a class of nonlinear systems

In this paper, a novel robust observer-based adaptive controller is presented using a proposed simplified type-2 fuzzy neural network (ST2FNN) and a new three dimensional type-2 membership function is presented. Proposed controller can be applied to the control of high-order nonlinear systems and adaptation of the consequent parameters and stability analysis are carried out using Lyapunov theorem. Moreover, a new adaptive compensator is presented to eliminate the effect of the external disturbance, unknown nonlinear functions approximation errors and sate estimation errors. In the proposed scheme, using the Lyapunov and Barbalat's theorem it is shown that the system is stable and the tracking error of the system converges to zero asymptotically. The proposed method is simulated on a flexible joint robot, two-link robot manipulator and inverted double pendulums system. Simulation results confirm that in contrast to other robust techniques, our proposed method is simple, give better performance in the presence of noise, external disturbance and uncertainties, and has less computational cost.     

基于FPGA的DDR3存储控制的设计与验证

DDR3SDRAM是第三代双倍数据传输速率同步动态随机存储器,DDR3具有高速率、低电压、低功耗等特点[1-2];在DDR3控制器的实际使用中,如何将用户需要存储的数据在DDR3中快速存储非常重要,如果数据被送到DDR3接口的速度低,则会影响DDR3的存储速度,同时影响DDR3的实际应用,因此,针对DDR3存储器设计存储控制有重要的意义[2];基于此设计主要分为低速读写控制与高速流读写控制,低速读写控制主要用于小数据量的操作,高速流读写控制主要用于批量数据的存储操作;此设计在FPGA上通过了大量数据读写的验证,证明数据存储的正确性;经过测试,在高速流读写模式下,DDR3存储控制设计的带宽利用率最大为66.4%;此设计在功能和性能上均符合系统总体设计的要求。     

嵌入式Web控制终端的物联网移动E-Laboratory平台

为了进一步提高大学校园设备资源的利用率,实现多种实验装置的网络化控制和用户终端移动化,基于物联网技术,将LAMP移植到采用ARM架构的微处理器上,通过搭建嵌入式Web控制终端,对Web服务平台进行了详细的设计,实现了多种实验装置的网络化控制;将单自由度机械臂系统这一实验装置与EWC_T连接,基于Android操作系统上开发了一个应用,设计并搭建了Mobile Experiment系统,实现了网络化实验室平台的用户终端的移动化;通过实验证明该系统能够可靠地完成对实验装置的远程控制,并具有低功耗、低成本和便携性好等优点。     

基于改进粒子群优化算法的火电厂机组负荷分配

以坑口电厂厂级监控信息系统的机组负荷在线优化分配功能模块为应用背景,针对模块所运用的基本粒子群优化算法在优化过程中容易陷入局部收敛、收敛速度慢的缺点,提出一种基于惯性权重非线性减小策略的改进粒子群优化算法,使惯性权重呈对数减小;测试函数仿真结果表明,改进粒子群优化算法在收敛速度和寻优精度方面,优化性能均优于基本粒子群优化算法;通过MATLAB与Visual C++混合编程,开发了机组负荷在线优化分配功能模块,提高了算法的计算效率和工程应用价值。