Fuel cell starvation control using model predictive technique with Laguerre and exponential weight functions

Fuel cell system is a complicated system that requires an efficient controller. Model predictive control is a prime candidate for its optimization and constraint handling features. In this work, an improved model predictive control (MPC) with Laguerre and exponential weight functions is proposed to control fuel cell oxygen starvation problem. To get the best performance of MPC, the control and prediction horizons are selected as large as possible within the computation limit. An exponential weight function is applied to place more emphasis on the current time and less emphasis on the future time in the optimization process. This leads to stable numerical solution for large prediction horizons. Laguerre functions are used to capture most of the control trajectory, while reducing the controller computation time and memory for large prediction horizons. Robustness and stability of the proposed controller are assessed using Monte-Carlo simulations. Results verify that the modified MPC is able to mimic the performance of the infinite horizon controller, discrete linear quadratic regulator (DLQR). The controller computation time is reduced approximately by one order of magnitude compared to traditional MPC scheme. Results from Monte-Carlo simulations prove that the proposed controller is robust and stable up to system parameters uncertainty of 40%.     

Generalized eigenvalue minimization for uncertain first-order plus time-delay processes

This paper shows how to apply generalized eigenvalue minimization to processes that can be described by a first-order plus time-delay model with uncertain gain, time constant and delay. An algorithm to transform the uncertain first-order plus time delay model into a state-space model with uncertainty polyhedron is firstly described. The accuracy of the transformation is studied using numerical examples. Then, the uncertainty polyhedron is rewritten as a linear-matrix-inequality constraint and generalized eigenvalue minimization is adopted to calculate a feedback control law. Case studies show that even if uncertainties associated with the first-order plus time delay model are significant, a stable feedback control law can be found. The proposed control is tested by comparing with a robust internal model control. It is also tested by applying it to the temperature control of air-handing units.     

Improved design of constrained model predictive tracking control for batch processes against unknown uncertainties

In this paper, an improved constrained tracking control design is proposed for batch processes under uncertainties. A new process model that facilitates process state and tracking error augmentation with further additional tuning is first proposed. Then a subsequent controller design is formulated using robust stable constrained MPC optimization. Unlike conventional robust model predictive control (MPC), the proposed method enables the controller design to bear more degrees of tuning so that improved tracking control can be acquired, which is very important since uncertainties exist inevitably in practice and cause model/plant mismatches. An injection molding process is introduced to illustrate the effectiveness of the proposed MPC approach in comparison with conventional robust MPC.     

具有状态约束的电液伺服系统模型参考鲁棒自适应控制

针对电液伺服系统中的模型不确定性和状态约束问题,设计了一种模型参考鲁棒自适应控制(MRRAC)方法。将电液伺服系统的近似模型作为模型预测控制(MPC)的设计对象,在设计过程中考虑状态约束,并生成受约束的状态期望,作为后续伺服控制方法的参考指令。为了克服液压系统中的模型不确定性,基于反步法设计了鲁棒自适应控制器(RAC),实现了兼顾模型不确定性和状态约束的伺服控制。基于Lyapunov稳定性理论证明了所设计控制策略的闭环渐近稳定性,且系统所有信号均有界。仿真结果表明,控制器对于系统模型不确定性具有较强的鲁棒性,且可实现对指定状态的有效约束,充分验证了该控制策略的有效性。     

基于参数和代理模型不确定性的冲压稳健性设计优化

在传统的基于代理模型的冲压稳健性设计中,由于代理模型与真实模型间存在着误差,必然会导致优化结果存在一定的误差。将实验设计、Kriging模型相结合,综合考虑参数不确定性和代理模型不确定性的影响,提出了一种新的冲压稳健性优化设计方法。通过因素敏感性分析筛选出相应的设计变量和噪声因素,基于Kriging模型构建设计参数和质量指标的代理模型,采用蒙特卡罗分析方法以及遗传算法获得最优工艺解。实例分析结果表明,综合两种不确定因素的稳健设计方法能有效地降低拉裂、起皱约束失效概率,提高冲压件成形质量和工艺稳健性。     

光电跟踪系统鲁棒自调整内模控制设计与分析

光电跟踪系统广泛应用于制导武器、航空航天观测设备以及靶场光电测量仪器等领域。针对光电成像测量时滞和模型不确定性,设计了一种鲁棒自调整内模控制算法。给出基于相位裕度和幅值裕度指标的系统控制器整定方程,分析得到了模型失配情况下的系统鲁棒稳定条件以及参数的设计准则,引入基于二次型性能指标的优化方法在线自适应调整控制滤波器参数来提高系统的控制性能和鲁棒性。在光电跟踪转台上的实验结果表明,所设计算法可有效地克服光电图像跟踪器测量时滞所造成的跟踪偏差,跟踪精度小于1密位,保证了成像传感器对目标的快速准确跟踪。     

A comparison of a novel robust decentralised control strategy and MPC for industrial high purity,high recovery,multicomponent distillation

In this work we have developed a novel, robust practical control structure to regulate an industrial methanol distillation column. This proposed control scheme is based on a override control framework and can manage a non-key trace ethanol product impurity specification while maintaining high product recovery. For comparison purposes, a MPC with a discrete process model (based on step tests) was also developed and tested. The results from process disturbance testing shows that, both the MPC and the proposed controller were capable of maintaining both the trace level ethanol specification in the distillate (X_D) and high product recovery (β). Closer analysis revealed that the MPC controller has a tighter X_D control, while the proposed controller was tighter in β control. The tight X_D control allowed the MPC to operate at a higher X_D set point (closer to the 10 ppm AA grade methanol standard), allowing for savings in energy usage. Despite the energy savings of the MPC, the proposed control scheme has lower installation and running costs. An economic analysis revealed a multitude of other external economic and plant design factors, that should be considered when making a decision between the two controllers. In general, we found relatively high energy costs favour MPC.     

鲁棒的多学科设计协同决策方法

针对产品设计过程中的多学科冲突解耦问题,提出一种鲁棒的协同决策方法。该方法采用区间形式表示不确定性的设计参数并基于非合作博弈理论将多学科协同决策描述成基于区间的约束求解问题,对此,采用两步求解策略获得产品设计的鲁棒决策方案。首先用约束一致性算法过滤掉决策变量区间中肯定不包含有效解的冗余部分,得到设计参数的一致性区间矢量;然后在一致性区间内以设计性能指标为准则搜索鲁棒的参数决策值,并设计基于可行性审查的免疫混沌搜索算法。以一个单元盘弹性转子系统为例,进行摩擦学和动力学冲突解耦的设计决策,得到较好的设计结果,验证方法的合理性与可靠性。     

并行工程环境下的鲁棒设计

提出了一种基于约束网络的鲁棒设计方法。与传统的统计学鲁棒设计方法不同,该方法能够利用约束网络对并行设计中的一类不确定性参数进行有效的描述和处理。利用基于区间代数的一致性算法,在设计的初期就监控设计过程,使设计者在确定参数前能够通过约束网络定量地考虑下游的约束条件,并能够及早发现设计中的冲突,以避免后期出现大的返工,本文的研究是实现并行工程中“一次成功”的技术基础。     

Robust discrete time tracking control using sliding surfaces

This paper deals with the robustness issues associated with the feedforward tracking control with respect to unmodeled plant uncertainties. Based on the Diophantine equation, a new discrete time sliding functions has been defined and utilized for the robust feedforward tracking control law. The robustness is achieved by using a sliding function-based nonlinear feedback. As for model/plant mismatches the plant order uncertainty and parameter uncertainty are taken into account for robustness analysis. Noncircular machining has been adopted as an application example of this algorithm. Through computer simulation it has been shown that the robust discrete time tracking control is effective for unmodeled plant uncertainties.     

Robust model predictive control design with input constraints

The paper addresses the problem of designing a robust output/state model predictive control for linear polytopic systems with input constraints. The new predictive and control horizon model is derived as a linear polytopic system. Lyapunov function approach guarantees the quadratic stability and guaranteed cost for closed-loop system. The invariant set and an algorithm approach similar to Soft Variable-Structure Control (SVSC), ensures input constraints for the model predictive plant control system. In the proposed control scheme, the required on-line computation load is significantly less than in MPC literature, which opens the possibility to use these control design schemes not only for plants with slow dynamics, but also for faster ones.     

Model predictive controller-based multi-model control system for longitudinal stability of distributed drive electric vehicle

Distributed drive electric vehicle(DDEV) has been widely researched recently, its longitudinal stability is a very important research topic. Conventional wheel slip ratio control strategies are usually designed for one special operating mode and the optimal performance cannot be obtained as DDEV works under various operating modes. In this paper, a novel model predictive controller-based multi-model control system (MPC-MMCS) is proposed to solve the longitudinal stability problem of DDEV. Firstly, the operation state of DDEV is summarized as three kinds of typical operating modes. A submodel set is established to accurately represent the state value of the corresponding operating mode. Secondly, the matching degree between the state of actual DDEV and each submodel is analyzed. The matching degree is expressed as the weight coefficient and calculated by a modified recursive Bayes theorem. Thirdly, a nonlinear MPC is designed to achieve the optimal wheel slip ratio for each submodel. The optimal design of MPC is realized by parallel chaos optimization algorithm(PCOA)with computational accuracy and efficiency. Finally, the control output of MPC-MMCS is computed by the weighted output of each MPC to achieve smooth switching between operating modes. The proposed MPC-MMCS is evaluated on eight degrees of freedom(8DOF)DDEV model simulation platform and simulation results of different condition show the benefits of the proposed control system.     

证据理论和区间分析相结合的可靠性优化设计方法

提出一种基于证据理论和区间分析方法的可靠性优化设计方法。对于给定的失效概率许用值f0,通过证据理论求出可靠性约束条件的似真度Pl(F),以Pl(F)f0作为可靠性约束条件的替代模型,进而提出基于证据理论的广义可靠性优化设计建模方法。当仅考虑随机不确定性时,所建立的模型退化为传统的随机可靠性优化设计模型。给出似真度Pl(F)的数值计算方法,并引入区间分析理论计算约束函数的值域,提高似真度的计算效率和可靠性优化的求解速度。开发基于证据理论和区间分析的可靠性优化设计遗传算法程序。给出了内压容器的可靠性优化设计实例。设计实例表明,所提出的方法正确、有效。     

Predictive control for voltage collapse avoidance using a modified discrete multi-valued PSO algorithm

Voltage stability is one of the most challenging concerns that power utilities are confronted with, and this paper proposes a voltage control scheme based on Model Predictive Control (MPC) to overcome this kind of instability. Voltage instability has a close relation with the adequacy of reactive power and the response of Under Load Tap Changers (ULTCs) to the voltage drop after the occurrence of a contingency. Therefore, the proposed method utilizes reactive power injection and tap changing to avoid voltage collapse. Considering discrete nature of the changes in the tap ratio and also in the reactive power injected by capacitor banks, the search area for the optimizer of MPC will be an integer area; consequently, a modified discrete multi-valued Particle Swarm Optimization (PSO) is considered to perform this optimization. Simulation results of applying the proposed control scheme to a 4-bus system confirm its capability to prevent voltage collapse.     

Design of robust discrete control with desirable quadratic stability

In this paper, a design of robust discrete control with desirable quadratic stability is proposed. The design procedure is the extended discrete version of the continuous robust quadratic stabilization technique proposed by Gu et al. [K. Gu, Y.H. Chen, M.A. Zohdy, N.K. Loh, Quadratic stabilizability of uncertain systems: a two level optimization setup, Automatica 27 (1) (1991) 161–165.]. The effect of the sampling time selection, and the effect of the domain on the robustness, is examined. The presented algorithm is applied to a discrete mass spring system, and a discrete simplified car steering system to demonstrate the feasibility of the procedure, and the effect of the time sampling on the robustness. The robustness increases in both examples considered, as the sampling time decreases to some degree.     

A PSO-based optimal tuning strategy for constrained multivariable predictive controllers with model uncertainty

This paper describes the development of a method to optimally tune constrained MPC algorithms with model uncertainty. The proposed method is formulated by using the worst-case control scenario, which is characterized by the Morari resiliency index and the condition number, and a given nonlinear multi-objective performance criterion. The resulting constrained mixed-integer nonlinear optimization problem is solved on the basis of a modified version of the particle swarm optimization technique, because of its effectiveness in dealing with this kind of problem. The performance of this PSO-based tuning method is evaluated through its application to the well-known Shell heavy oil fractionator process.     

ROBUST CONTROL OF AN ELECTRO- HYDRAULIC PROPORTIONAL SPEED CONTROL SYSTEM WITH A SINGLE- ROD HYDRAULIC ACTUATOR

A robust control algorithm is proposed to focus on the non-linearity and parameters' uncertainties of an electro-hydraulic proportional speed control system (EHPSCS) with a single-rod hydraulic actuator.The robust controller proposed does not need to design stable compensator in advance,is simple in design and has large scope of uncertainty applications.The feedback gains of the robust controller proposed are small,so it is easily implemented in engineering applications. Experimental research on the speed control under the different conditions is carried out for an EHPSCS.Experimental results show that the robust controller proposed has better robustness subject to parametric uncertainties,and adaptability of parameters' variation of control system itself and plant parameter variation.     

HYBRID CONTROL OF HYDRAULIC PRESS MACHINE BASED ON ROBUST CONTROL

A robust control algorithm is proposed to focus on the non-linearity and variables of the hydraulic press machine with the proportional vatve. The proposed robust controller does not need to design stable compensator in advance, which is simple in design and has large scope of uncertainty applications. The feedback gains of the proposed robust controller are small, so it is easily implemented in engineering applications. The theoretical and experimental research on the position and speed control of the hydraulic press machine is carried out. The control requirements of the hydraulic press machine during the working process are met in the position and speed at the same time. Experimental results show that the proposed controller has better robustness subject to load variables and adaptability of parameter variations of the hydraulic press machine with the proportional valve.