PID Control of Planar Nonlinear Uncertain Systems in the Presence of Actuator Saturation

This paper investigates PID control design for a class of planar nonlinear uncertain systems in the presence of actuator saturation. Based on the bounds on the growth rates of the nonlinear uncertain function in the system model, the system is placed in a linear differential inclusion. Each vertex system of the linear differential inclusion is a linear system subject to actuator saturation. By placing the saturated PID control into a convex hull formed by the PID controller and an auxiliary linear feedback law, we establish conditions under which an ellipsoid is contractively invariant and hence is an estimate of the domain of attraction of the equilibrium point of the closed-loop system. The equilibrium point corresponds to the desired set point for the system output. Thus, the location of the equilibrium point and the size of the domain of attraction determine, respectively, the set point that the output can achieve and the range of initial conditions from which this set point can be reached. Based on these conditions, the feasible set points can be determined and the design of the PID control law that stabilizes the nonlinear uncertain system at a feasible set point with a large domain of attraction can then be formulated and solved as a constrained optimization problem with constraints in the form of linear matrix inequalities (LMIs). Application of the proposed design to a magnetic suspension system illustrates the design process and the performance of the resulting PID control law.      

能源土边界面模型的应力更新算法及算例分析

水合物的存在会显著影响能源土的刚度、峰值强度与剪胀性。针对已有能源土模型的不足，结合边界面模型的建模思想，构建一个新的能源土边界面模型，模型参数较少，能够恰当反映能源土的应力-应变关系。计算能源土变形问题的核心在于正确积分塑性本构方程，应用完全隐式回退Euler算法，建立模型应力及塑性内变量的更新公式，并给出显式的一致性切线模量表达式。基于ABAQUS软件提供的二次开发接口，编写模型的用户材料子程序，应用已有试验数据验证程序正确性。最后应用开发的子程序对能源土的平面应变试验进行模拟，分析水合物饱和度对剪切带倾角与孔隙比的影响。     

Structural load alleviation using distributed delay shaper: Application to flexible aircraft

Lightweight flexible aircraft suffers from unwanted oscillatory vibrations during aircraft manoeuvres. A recently developed distributed-delay signal (DZV) shaper is therefore proposed to be applied as a feedforward controller to alleviate the manoeuvre loads, as an alternative to traditional structural filters used routinely in this context. Structural filters are essentially linear low-pass filters with bandwidth below the significant flexible modes, applied to control signals generated either by the pilot’s direct input or by the flight control system. It has been showed that if instead a properly tuned signal shaper is used, better performance can be achieved: first, the target modes are significantly attenuated while the responsiveness of the aircraft is less compromised and secondly, the oscillatory nature of the vibrations are reduced. The high fidelity simulation results on a full scaled dynamic model of a highly flexible blended wing–body (BWB) aircraft show that in comparison to traditional structural filters, signal shapers significantly reduce the wing root loading (forces and moments) which provides potential structural benefits.     

亲油型聚结滤芯饱和度预测模型研究

纤维聚结滤芯广泛用于压缩空气净化、发动机曲轴箱通风、加工和切割等一系列工艺过程中，用于除去气流中的液体气溶胶颗粒。由于聚结滤芯饱和度对于过滤效率及阻力具有重要影响，因此建立饱和度与滤材参数及操作条件之间的关系将有助于优化滤芯结构并提高过滤性能。目前实际工业用聚结滤芯通常由多层微米级玻璃纤维材料组成，然而现有计算模型无法用于此类滤芯的饱和度预测。因此，本文基于多种常用亲油型聚结滤芯压降及饱和度实验测试结果，根据“跳跃-通道”模型及毛细管理论建立了新的饱和度预测模型。通过与大量已发表文献数据对比发现，当饱和值大于0.2时，预测值与实验结果吻合度较好，相对偏差≤20%。随着饱和度的降低，滤芯润湿区域和非润湿区域之间界限逐渐明显，此时无需对毛细管半径进行修正。然而，新模型仍然要依靠压降测量值进行计算，这一问题需在后续工作中加以解决。     

A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

Improved Input and State Estimation for Linear Stochastic Systems with Direct Feedthrough

This paper is concerned with the problem of joint input and state estimation for linear stochastic systems with direct feedthrough. Based on the fact that each unknown input between any two time steps is always bounded, a novel improved algorithm is proposed. Compared with existing results, this algorithm can effectively enhance estimation accuracy. Moreover, the stability of the algorithm is also discussed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach.     

用于机床减振的磁流变阻尼器优化设计

以三平动冗余驱动并联机床为研究对象,设计了一种具有位移放大功能的磁流变阻尼器,通过Ansys workbench有限元分析软件,对阻尼器的磁路饱和情况进行模拟仿真和分析,使阻尼器的阻尼出力达到最优。研究结果表明,通过优化使磁场分布更加合理,提高了阻尼器的力学性能,优化方法是可行有效的。     

Model recovery anti-windup for output saturated SISO linear closed loops

We define model recovery anti-windup for SISO linear control systems with output saturation. We address the problem by relying on a hybrid modification of the linear closed loop which employs a suitable logic variable to activate/deactivate various components of a control scheme. The scheme relies on a finite-time observation law, an open-loop observer and an open-loop input generator which is capable of driving the plant output within the saturation limits. Then the control scheme is based on suitable (hybrid) resetting laws allowing the controller to operate on the artificial output signal generated by the open-loop observer when the actual plant output is outside the saturation limits. Unlike existing results, not only we prove uniform global asymptotic stability of the closed loop, but we also prove the local preservation and global recovery properties, typical of model recovery anti-windup paradigms. We also illustrate the proposed technique on an example study.     

Performance investigation of multi-stage saturation cycle with natural working fluids and low GWP working fluids

Improving the efficiency of a vapor compression cycle and using low GWP working fluids have become more important than ever due to the environmental concerns. A saturation cycle consisting of saturation compression and saturation expansion was proposed in order to improve a vapor compression cycle performance by reducing thermodynamic losses associated with single phase gas compression and isenthalpic expansion. The saturation cycle can be approached by multi-stage cycles with two-phase refrigerant injection. In this paper, the performance of saturation cycle was theoretically investigated for low GWP working fluids including natural fluids under ASHRAE standard operating conditions and extreme heating condition. The simulation results indicate that the benefit of using the multi-stage cycle is higher for the cycle with higher pressure ratio. When the saturation cycle technique (four-stage cycle) is applied, the COP improvements of D2Y60 (mixture of R32 and R1234yf), CO₂ and propane are 46.9%, 43.2% and 38.2%, respectively under extreme heating condition.     

Input variable scaling for statistical modeling

Input variable scaling is one of the most important steps in statistical modeling. However, it has not been actively investigated, and autoscaling is mostly used. This paper proposes two input variable scaling methods for improving the accuracy of soft sensors. One method statistically derives the input variable scaling factors; the other one uses spectroscopic data of a material whose content is estimated by the soft sensor. The proposed methods can determine the scales of the input variables based on their importance in output estimation. Thus, it can reduce the negative effects of input variables which are not related to an output variable. The effectiveness of the proposed methods was confirmed through a numerical example and industrial applications to a pharmaceutical and a distillation processes. In the industrial applications, the proposed methods improved the estimation accuracy by up to 63% compared to conventional methods such as autoscaling with input variable selection.