Multivariable quantitative feedback design for tracking error specifications

The use of tracking error specifications in quantitative feedback theory (QFT) design is discussed for multi-input, multi-output (MIMO) systems. These specifications bound the closed loop transfer function within a disk around some nominal (model) performance while preserving the QFT approach that allows treatment of highly structured (and unstructured) uncertainty. Because the specifications capture phase information, the level of over-design in certain MIMO QFT designs is reduced. The method presented allows independent, two-degree-of-freedom design.     

Lyapunov-based feedback design and experimental verification of IC engine speed control

In this paper, the speed control problem of internal combustion engines is investigated based on mean-value engine models. The dynamics of internal combustion engines is a complicated nonlinear system, and usually, it is difficult to know the exact values of the physical parameters. First, a Lyapunov-based design method is shown without requiring the full information of the physical parameters. Then, to improve transient performance, the design method is extended to several cases under different operation conditions. Numerical simulation results are presented for comparing the proposed design methods. Finally, experiments are conducted on an engine test bench and the results demonstrate the validity of the proposed design methods. Recommended by Editorial Board member Myotaeg Lim under the direction of Editor Hyun Seok Yang. The authors are grateful to Kai Zheng for his assistance of the model identification experiments. Jiangyan Zhang received the B.E. and M.E. degrees in Electrical Engineering, Yanshan University, China, in 2005 and 2008, respectively. Now, she is a Ph.D. candidate with the Department of Engineering and Applied Sciences, Sophia University, Tokyo, Japan. Her current research interests include nonlinear system control theory and applications to powertrain system control. Tielong Shen received the Ph.D. degree in Mechanical Engineering from Sophia University, Tokyo, Japan, March, 1992. From April 1992, he has been a faculty member of the Chair of Control Engineering in Department of Mechanical Engineering, Sophia University, where he currently serves as professor of the Department of Engineering and Applied Science. His research interests include control theory and application in mechanical systems, power systems, and automotive powertrain. Currently, he is an Associate Editor for the IEEE Control System Society Conference Editorial Board, and is serving as Associate Editor of Journal of Control Theory and Applications, and the Regional Editor Asia-Pacific for International Journal of Modeling, Identification and Control etc. Junichi Kako received the B.E. degree from Nagoya Institute of Technology, Nagoya, Japan. He joined Toyota Motor Corporation, Tokyo, Japan in 1989. He worked on various aspects of automotive powertrain control. From 1989 to 1994, he took part in the team for the development of Laboratory Automation (LA) system, Engineering Office Automation (EOD) system, and embedded system of powertrain control. During 1995–2001, he focused on the engine control systems in Powertrain Management Engineering Division. In 2002, he was with Future Project Division in which he was responsible for the R&D of model-based engine control system. Currently, he is developing engine control systems in the Powertrain Management Engineering Division, Toyota Motor Corporation. Shozo Yoshida received the M.S. degree in Engineering from Kyoto University, Kyoto, Japan. He joined Toyota Motor Corporation, Tokyo, Japan in 2000. From 2000 to 2004, he was with Future Project Division and worked on physical combustion modeling for Model-based Control Development. Since 2005, he has been with the Powertrain Management Engineering Division Toyota Motor Corporation, and is a member of the R&D of Model-based Engine Calibration.     

Modeling and control of the air system of a turbocharged gasoline engine

In order to reduce CO₂ emissions in the automotive industry, there is a trend to decrease the size of the engines and add turbocharging technologies to increase the engine efficiency while keeping performances. In this context, numerous studies have focused on the improvement of turbocharger control strategies. The strategy proposed in this paper is based on constrained motion planning and feedback linearization applied to a simplified model of the system. It takes advantage of the whole system bandwidth and requires a limited calibration effort. Thanks to its structure, it offers an interesting potential for generalization to more complex turbocharging systems. Extensive experimental tests are reported for a four-cylinder gasoline engine.     

Multi-input/single-output computer-aided control design using the quantitative feedback theory

The quantitative feedback theory is an engineering design technique of uncertain feedback systems having robust stability and robust performance specifications. The crux of the quantitative feedback theory is a transformation of robust stability and robust performance specifications into domains in the complex plane, referred to as bounds, where a nominal loop transmission should lie within. To date, a quantitative feedback theory design is being carried out using manual (i.e. graphical) procedures or search algorithms. This paper shows that there exists a formal map from the uncertain plant and each closed-loop specification to these bounds. In particular, it is shown that each map has a closed form consisting of a quadratic inequality. These maps greatly simplify the computational aspects of the quantitative feedback theory in design of single-loop feedback systems. Based on this new development, a simple-to-implement, efficient computer algorithm is outlined.     

Observer-based H-infinity output feedback control with feedback gain and observer gain variations for Delta operator system

Considering that the controller feedback gain and the observer gain are of additive norm-bounded variations, a design method of observer-based H-infinity output feedback controller for uncertain Delta operator systems is proposed in this paper. A sufficient condition of such controllers is presented in linear matrix inequality （LMI） forms. A numerical example is then given to illustrate the effectiveness of this method, that is, the obtained controller guarantees the closed-loop system asymptotically stable and the expected H-infinity performance even if the controller feedback gain and the observer gain are varied.     

Computer aided control system design applied to milk drying plants

This paper reviews a computer aided control system design facility that has been used to develop a set of control systems that have been implemented on a pilot scale industrial process. The facility caters for a broad range of control situations including those with interactions, time delays and disturbances. Online interactive graphics is used as a design aid for the identification of plant dynamics and for the assessment of control system performance. Control systems may be developed systematically to be structured in a hierarchical configuration on the plant. Particular applications to the plant, an evaporator and a spray drier, are discussed in detail.     

Cascaded control of combustion and pollutant emissions in diesel engines

Control of the emissions of diesel engines is an upcoming approach for complying with legislation while limiting the calibration effort. In this paper, a controller for engine-out NO_x and PM is combined with a controller for the center of main combustion and the indicated mean effective pressure. The inner cascade combustion controller effectively reduces unwanted influences on the combustion. These influences are partly coupled to the outer-loop manipulated variables and partly result from disturbances which commonly appear in diesel engines. Robust stability is analyzed and holds in a wide operating range. Performance of the control structure is demonstrated with experiments.     

离散系统鲁棒稳定的简化条件及其反馈控制方法

给出了一种离散系统鲁棒稳定性的分析方法。通过对离散系统不确定部分不同表达式的研究，提出一种系统鲁棒稳定判别不等式。为解决系统鲁棒稳定性的实际计算问题，给出了离散系统鲁棒稳定性的另一种描述，井由此描述和不等式恒等变形，得到新的鲁棒稳定性判据。该判据结构筒单，很容易判定系统的鲁棒性。在此基础上，给出了系统鲁棒反馈控制的设计方法。     

An alternative to standard nuclear core control using a multi-objective approach

This paper proposes an alternative to standard nuclear core control. The control objectives are standard and concern the Average Coolant Temperature, the Axial Offset and the rod bank position (Pbank in this study). They were carefully formalized before proceeding to LTI structured controllers synthesis at various operating points, using a multi-objective approach. This study relies on a point kinetic core model, embedding an AO estimator. A Non-smooth optimization technique is used to solve the control problems at each operating point. Then gain scheduling is performed, taking advantage of the parsimonious parameterization of the considered multivariable controller. Finally, simulations are carried out on a highly realistic reactor model including a Xenon model and show the benefits of the new control     

Experimental evaluation of linear time-invariant models for feedback performance control in real-time systems

In recent years a new class of soft real-time applications operating in unpredictable environments has emerged. Typical for these applications is that neither the resource requirements nor the arrival rates of service requests are known or available a priori. It has been shown that feedback control is very effective to support the specified performance of dynamic systems that are both resource insufficient and exhibit unpredictable workloads. To efficiently use feedback control scheduling it is necessary to have a model that adequately describes the behavior of the system. In this paper we experimentally evaluate the accuracy of four linear time-invariant models used in the design of feedback controllers. We introduce a model (DYN) that captures additional system dynamics, which a previously published model (STA) fails to include. The accuracy of the models are evaluated by validating the models with regard to measured data from the controlled system and through a set of experiments where we evaluate the performance of a set of feedback control schedulers tuned using these models. From our evaluations we conclude that second order models (e.g., DYN) are more accurate than first order models (e.g. STA). Further we show that controllers tuned using second order models perform better than controllers tuned using first order models.     

Self-tuning of quantitative feedback theory for force control of an electro-hydraulic test machine

The aim of this paper is to design and fabricate an electro-hydraulic test machine (EHTM) for conducting performance and stability test of force and/or position control in the bench system and to propose a robust adaptive controller—the self-tuning quantitative feedback theory (STQFT)—in order to improve the force control performance of electro-hydraulic actuators (EHAs). By using the gradient descent method to adjust the QFT parameters, the novel STQFT controller is able to adapt to a wide range of working conditions. Experiments were carried out to evaluate the effectiveness of the proposed control method applied to the EHTM.     

Extensions to “virtual reference feedback tuning: A direct method for the design of feedback controllers”

The papers [Campi, Lecchini & Savaresi (2002). Automatica, 38(8), 1337-1346; (2003). European Journal of Control, 9(1), 66-76] present a direct controller synthesis procedure that uses identification algorithms applied to filtered input-output plant data. This contribution discusses variations that, in some cases, may alleviate noise-induced correlation (in the open-loop case) and allow the applicability of the approach to unstable plants. Importantly, it also introduces an invalidation test step based on the available data (i.e., prior to experimental controller testing), to check if the flexibility of the controller parameterisation and the approximations involved are suitable for the design objectives or, on the contrary, the resulting closed loop may be unstable.     

Nonlinear robust state feedback control system design for nonlinear uncertain systems

This paper presents a systematic approach to the design of a nonlinear robust dynamic state feedback controller for nonlinear uncertain systems using copies of the plant nonlinearities. The technique is based on the use of integral quadratic constraints and minimax linear quadratic regulator control, and uses a structured uncertainty representation. The approach combines a linear state feedback guaranteed cost controller and copies of the plant nonlinearities to form a robust nonlinear controller with a novel control architecture. A nonlinear state feedback controller is designed for a synchronous machine using the proposed method. The design provides improved stability and transient response in the presence of uncertainty and nonlinearity in the system and also provides a guaranteed bound on the cost function. An automatic voltage regulator to track reference terminal voltage is also provided by a state feedback equivalent robust nonlinear proportional integral controller. Copyright © 2016 John Wiley & Sons, Ltd.     

模糊时滞系统的输出反馈控制及其稳定性分析

利用模糊T－S模型对一类不确定非线性时滞系统进行建模，在此基础上，提出了模糊不确定时滞系统的状态反馈控制及其输出反馈控制的设计，并给出了模糊闭环系统渐近稳定的充分条件，基于李亚普诺夫函数和线性矩阵不等式方法，证明了模糊系统的渐近稳定性。     

移动机器人无线实时反馈控制系统的设计

由于移动机器人左右两轮的非线性特征,其反馈调节无法克服这一特性,必须借助PC机来进行调节。为此提出了一种无线实时反馈控制方法,在PC机上加入PID控制算法,实现了对机器人的无线实时反馈控制。     

Identification for control of multivariable systems: Controller validation and experiment design via LMIs

This paper presents a new controller validation method for linear multivariable time-invariant models. Classical prediction error system identification methods deliver uncertainty regions which are nonstandard in the robust control literature. Our controller validation criterion computes an upper bound for the worst case performance, measured in terms of the -norm of a weighted closed loop transfer matrix, achieved by a given controller over all plants in such uncertainty sets. This upper bound on the worst case performance is computed via an LMI-based optimization problem and is deduced via the separation of graph framework. Our main technical contribution is to derive, within that framework, a very general parametrization for the set of multipliers corresponding to the nonstandard uncertainty regions resulting from PE identification of MIMO systems. The proposed approach also allows for iterative experiment design. The results of this paper are asymptotic in the data length and it is assumed that the model structure is flexible enough to capture the true system.     

基于反馈控制的嵌入式实时系统调度算法设计

针对嵌入式实时系统在系统负载模型不确定的情况下系统的实时任务错过率过高以及调度稳定性差的问题,提出了一个基于反馈控制的调度模型.该模型主要由改进的多级队列调度器和3个控制器(准入控制器、执行等级控制器、比例积分微分(PID)控制器)组成.任务的错过率偏差反馈到PID控制器,产生相应的调整量并作用于其他两个控制器,对实时任务的执行等级进行调整, 经过调整的任务被调度器调度执行.在对模型中每个部件进行了一些结构调整和改进设计之后,将该调度模型应用于嵌入式可配置操作系统(eCos)中.实验结果表明,该模型降低了任务的时限错过率,同时解决了系统频频超载的问题.     

网络化控制系统的时变采样及反馈调度策略

多处理器网络化控制系统中,信息传输的时延是使控制性能变差的主要原因之一。改进型混合调度算法通过在一个基本采样周期内的多次采样,形成时变的采样周期,缩减信息传输的截止期,可使信息传输的时延大为减少;同时构建网络化控制系统的反馈调度模型,通过调节基本采样周期,及时调度信息传输,能使网络的空闲时间始终保持在一个合理状态。仿真结果表明,网络利用率有所提高,网络化控制系统的动态性能有所改善。