The steady-state region of attraction under linear feedback control: A numerical approach

In this paper, a numerical approach to operability analysis is developed. Based on the concept of the steady-state region of attraction, which indicates the initial operating conditions that can be driven to a given setpoint, this analysis helps design engineers assess whether a process can be effectively controlled by linear control systems. Using steady-state operating data that are generated with process simulators (such as ASPEN PLUS^®), the steady-state region of attraction are calculated by solving the proposed constrained nonlinear optimization problem. The objective function for the optimization problem is developed using the ellipsoid theory while the constraint functions are formulated from the complement set of the initially defined constraint set and the boundary of the available input space (AIS). Furthermore, as the solution of a nonlinear optimization problem generally depends on the initial starting point, a method of generating a set of ellipsoids in the hyperspace to start the calculation is also developed. The proposed constrained nonlinear optimization problem can be solved using numerical tools such as MATLAB^®. This analysis can be performed based on process flowsheets with process simulators and thus is useful in early stages of process design. The use of the proposed numerical framework is illustrated by a case study of a methyl acetate reactive distillation column.     

Robust satisfactory fault-tolerant control of uncertain linear discrete-time systems: an LMI approach

Fault-tolerant control is an important issue in practical systems. Based on satisfactory control and estimation theory, a passive fault-tolerant control strategy is proposed for a class of uncertain linear discrete-time systems in this article. Manipulating linear matrix inequality (LMI) technique, robust fault-tolerant state-feedback controllers are designed which take the possible actuator faults and sensor faults into consideration, respectively. The closed-loop systems are guaranteed by the designed controllers to meet the required constraints on regional pole index φ(q, r), steady-state variance matrix X index and control-cost function V ²(u) index simultaneously. Then, whether possible faults occur or not, the closed-loop systems would maintain the three desirable performance indices accordingly. Meanwhile, the consistency of the performance indices mentioned earlier is also discussed for fault-tolerant control.     

Adaptive neuro-fuzzy inference system-based grey time-varying sliding mode control for power conditioning applications

This paper develops an adaptive neuro-fuzzy inference system-based grey time-varying sliding mode control (TVSMC) for the application of power conditioning systems. The presented methodology combines the merits of TVSMC, grey prediction (GP), and adaptive neuro-fuzzy inference system (ANFIS). Compared with classic sliding mode control, the TVSMC accelerates reaching phase and guarantees the sliding mode existence starting at arbitrary primary circumstance. But, as a highly nonlinear loading occurs, the TVSMC will undergo chattering and steady-state errors, thus degrading PCS’s performance. The GP is therefore used to attenuate the chattering if the overestimate of system uncertainty bounds exists and to lessen steady-state errors if the underestimate of system uncertainty bounds happens. Also, the GP-compensated TVSMC control gains are optimally tuned by the ANFIS for achieving more precise tracking. Using the proposed methodology, the power conditioning system (PCS) robustness is increased expectably, and low distorted output voltage and fast transient response at PCS output can be achieved even under nonlinear loading. The analysis in theory, design process, simulations, and digital signal processing-based experimental realization for PCS are represented to support the efficacy of the proposed methodology. Because the proposed methodology is easier to implement than prior methodologies and provides high tracking accuracy and low computational complexity, the contents of this paper will be of interest to learners of correlated artificial intelligence applications.

     

Direct adaptive interval type-2 fuzzy control of multivariable nonlinear systems

A fuzzy logic controller equipped with a training algorithm is developed such that the H^∞ tracking performance should be satisfied for a model-free nonlinear multiple-input multiple-output (MIMO) system, with external disturbances. Due to universal approximation theorem, fuzzy control provides nonlinear controller, i.e., fuzzy logic controllers, to perform the unknown nonlinear control actions and the tracking error, because of the matching error and external disturbance is attenuated to arbitrary desired level by using H^∞ tracking design technique. In this paper, a new direct adaptive interval type-2 fuzzy controller is developed to handle the training data corrupted by noise or rule uncertainties for nonlinear MIMO systems involving external disturbances. Therefore, linguistic fuzzy control rules can be directly incorporated into the controller and combine the H^∞ attenuation technique. Simulation results show that the interval type-2 fuzzy logic system can handle unpredicted internal disturbance, data uncertainties, very well, but the adaptive type-1 fuzzy controller must spend more control effort in order to deal with noisy training data. Furthermore, the adaptive interval type-2 fuzzy controller can perform successful control and guarantee the global stability of the resulting closed-loop system and the tracking performance can be achieved.     

Delay‐range‐dependent control of nonlinear time‐delay systems under input saturation

This paper describes a delay‐range‐dependent local state feedback controller synthesis approach providing estimation of the region of stability for nonlinear time‐delay systems under input saturation. By employing a Lyapunov–Krasovskii functional, properties of nonlinear functions, local sector condition and Jensen's inequality, a sufficient condition is derived for stabilization of nonlinear systems with interval delays varying within a range. Novel solutions to the delay‐range‐dependent and delay‐dependent stabilization problems for linear and nonlinear time‐delay systems, respectively, subject to input saturation are derived as specific scenarios of the proposed control strategy. Also, a delay‐rate‐independent condition for control of nonlinear systems in the presence of input saturation with unknown delay‐derivative bound information is established. And further, a robust state feedback controller synthesis scheme ensuring L₂ gain reduction from disturbance to output is devised to address the problem of the stabilization of input‐constrained nonlinear time‐delay systems with varying interval lags. The proposed design conditions can be solved using linear matrix inequality tools in connection with conventional cone complementary linearization algorithms. Simulation results for an unstable nonlinear time‐delay network and a large‐scale chemical reactor under input saturation and varying interval time‐delays are analyzed to demonstrate the effectiveness of the proposed methodology. Copyright © 2015 John Wiley & Sons, Ltd.     

Operating system support for the management of hard real-time disk traffic

Emerging applications like C³I systems, real-time databases, data acquisition systems and multimedia servers require access to secondary storage devices under timing constraints. In this paper, we focus on operating system support needed for managing real-time disk traffic with hard deadlines. We present the design and implementation of a preemptive deadline-driven disk I/O subsystem suitable for real-time disk traffic management. Preemptibility is achieved with a granularity that is automatically controlled by the I/O subsystem according to current workload and filesystem data layout. An admission control test checks the current resource availability for a given workload. We show that contiguous layout is necessary to maintain hard real-time guarantees and a reasonable level of disk throughput. Finally, we show how buffering can be used to obtain utilization factors close to the maximum disk bandwidth possible.     

An efficient methodology for robust control of dynamic systems with interval matrix uncertainties

Interval models are frequently used for dealing with uncertainties of control systems. However, it is well known that direct analysis and synthesis of a controlled dynamic system with interval matrix uncertainties may be a NP-hard problem. In this work, an efficient methodology for robustness analysis and robust control design of dynamic systems with interval matrix uncertainties is presented systematically, in which the uncertainties appearing in the controlled plant and controller realisation are taken into account simultaneously in an integrated framework. The fundamental problems, such as quadratic stability, guaranteed cost control and H_∞ control of uncertain systems are taken as examples to show the methodology. Necessary and sufficient conditions for linear dynamic systems with interval matrices are derived by transforming all the interval matrices into some more tractable forms. The whole reasoning process is logical and rigorous, and NP-hard problem is successfully avoided. The presented formulations are within the framework of linear matrix inequality and can be implemented conveniently. In contrast to existing vertex-set methods, in which the vertices of interval matrices need to be constructed and checked, the presented methods are more efficient. Three numerical examples are investigated to demonstrate the effectiveness and feasibility of the presented method.     

A methodology for designing toolkits for specification level verification of interval-constrained information systems requirements

In developing automated tools for verification for an Information systems (IS), there exists a need for a methodology for the development of information requirements maintenance toolkits which will maintain IS with unconstrained and constrained requirements. In this paper, we present a methodology for building generalized designs of IS maintenance toolkits that maintain the requirements specification of IS. Our methodology will decrease the effort in building and increase the structural quality of IS maintenance toolkits that are used for verification of an IS in areas such as command, control, communication, computer, intelligence, surveillance, and reconnaissance (C⁴ISR) organizations. The methodology represents a reuse-oriented Unified Modeling Process (UMP) and consists of a method for developing an enterprise model, a method for developing use cases of the toolkit services, a method for developing logic designs and a method for developing the component view of the software.     

MPC for tracking with optimal closed-loop performance

In the recent paper [Limon, D., Alvarado, I., Alamo, T., & Camacho, E.F. (2008). MPC for tracking of piece-wise constant references for constrained linear systems. Automatica, 44, 2382-2387], a novel predictive control technique for tracking changing target operating points has been proposed. Asymptotic stability of any admissible equilibrium point is achieved by adding an artificial steady state and input as decision variables, specializing the terminal conditions and adding an offset cost function to the functional.In this paper, the closed-loop performance of this controller is studied and it is demonstrated that the offset cost function plays an important role in the performance of the model predictive control (MPC) for tracking. Firstly, the controller formulation has been enhanced by considering a convex, positive definite and subdifferential function as the offset cost function. Then it is demonstrated that this formulation ensures convergence to an equilibrium point which minimizes the offset cost function. Thus, in case of target operation points which are not reachable steady states or inputs for the constrained system, the proposed control law steers the system to an admissible steady state (different to the target) which is optimal with relation to the offset cost function. Therefore, the offset cost function plays the role of a steady-state target optimizer which is built into the controller. On the other hand, optimal performance of the MPC for tracking is studied and it is demonstrated that under some conditions on both the offset and the terminal cost functions optimal closed-loop performance is locally achieved.     

Optimal deterministic observer design for linear continuous-time systems with unknown output disturbances in a ball in L2

The problem of the existence and design of an optimal observer for linear systems with unknown disturbances additive to the output is considered. The disturbances are assumed to be arbitrary L² functions constrained to a ball in L². The problem of reconstructing the best estimate of the state with respect to the worst disturbances is reformulated in terms of finding an operator L²-Rⁿ Satisfying some linear equalities and of minimal norm. The necessary and sufficient condition for the existence of such an operator is proved to be the well-known observability condition. The optimal observer is in the form of an integral operator. An explicit formula for its integrand is given. In addition, differential equations fulfilled by the optimal state estimate for the cases of a fixed or time-variable observation interval are derived.     

Target mass control for uncertain compartmental systems

In this article we analyse the total mass target control problem for compartmental systems under the presence of parameter uncertainties. We consider a state feedback control law with positivity constraints tuned for a nominal system, and prove that this law leads the value of the total mass of the real system to an interval whose bounds depend on the parameter uncertainties and can be made arbitrarily close to the desired value of the total mass when the uncertainties are sufficiently small. Moreover, we prove that for a class of compartmental systems in ?³ of interest, the state of the controlled system tends to an equilibrium point whose total mass lies within the aforementioned interval. Taking into account the relationship between the mass and the state components in steady state, it is possible to use the proposed mass control law to track the desired values for the steady state components. This is applied to the control of the neuromuscular blockade level of patients undergoing surgery, by means of the infusion of atracurium. Our results are illustrated by several simulations and a clinical case.     

Learning control for a class of nonlinear differential-algebraic systems with application to constrained robots

In this article, a learning control design method for analyzing the convergence of nonlinear systems described by a class of differential-algebraic equations¹ is developed. This method generalizes the previous methods for the study of the learning control problem of constrained mechanical systems to include a wider class of systems. Furthermore, the proposed design method allows us to analyze the role of force learning in the learning control of such a control system. We derive a sufficient condition for the convergence of both the motion and contact force of the systems as the operations are repeated. An application of the proposed controller to robotic manipulators with holonomic constraints is discussed, and simulation results of a constrained cylindrical robot are presented. © 1996 John Wiley & Sons, Inc.     

MIXED H2/H∞ ADAPTIVE TRACKING CONTROL DESIGN FOR UNCERTAIN CONSTRAINED ROBOTS

In this study, a PID‐type controller incorporating an adaptive learning scheme for the mixed H₂/H_∞ tracking performance is developed for constrained robots under unknown or uncertain plant parameters and external disturbances. The mixed H₂/H_∞ control design has the advantage of both H₂ optimal control performance and H_∞ robust control performance and the adaptive control scheme is used to compensate the plant uncertainties. By virtue of the skew‐symmetric property of the constrained robotic systems and an adequate choice of state variable transformation, sufficient conditions are developed for the adaptive mixed H₂/H_∞ tracking control problems in terms of a pair of coupled algebraic equations instead of a pair of coupled nonlinear differential equations. The proposed methods are simple and the coupled algebraic equations can be solved analytically. Simulation results indicate that the desired performance of the proposed adaptive mixed H₂/H_∞ tracking control schemes for the uncertain constrained robotic systems can be achieved.     

A peak filtering method with improved transient response for narrow-band disturbance rejection in hard disk drives

Peak filtering methods are commonly used in track-following control of hard disk drives (HDDs) to suppress narrow-band disturbances around a specific frequency. When there are significant plant dynamics within the bandwidth of the filter, the closed-loop system is prone to be unstable due to the lightly damped poles of the filter, as well as lightly damped poles of the plant. On the other hand, settling response of such peak filters during shock disturbances is slow, and increases tremendously with decreasing damping ratios. In this article, we present a novel design of peak filters with improved transient responses using a phase scheduling method in addition to varying gain and damping ratio. By doing so, the stability margin of the closed-loop systems during both transient stage and steady-state stage will be improved. The effectiveness of the proposed methodology is verified with extensive simulations and the proposed method is then applied in an integrative servo analysis platform to carry out a scaling exercise to evaluate and predict servo performance to support 10 Terabits/in².     

Constrained hierarchical least square nonlinear equation solvers

The current paper develops a constrained hierarchical least square nonlinear equation solver. The procedure can handle the response behavior of systems which possess indefinite tangent stiffness characteristics. Due to the generality of the scheme, this can be achieved at various hierarchical application levels. For instance, in the case of finite element simulations, various combinations of either degree of freedom, nodal, elemental, substructural, and global level iterations are possible. Overall, this enables a solution methodology which is highly stable and storage efficient. To demonstrate the capability of the constrained hierarchical least square methodology, benchmarking examples are presented which treat structure exhibiting highly nonlinear pre- and postbuckling behavior wherein several indefinite stiffness transitions occur.     

持续有界扰动下的非线性H∞鲁棒预测控制

针对未知但有界的持续扰动, 提出了一种约束非线性 H∞ 鲁棒预测控制策略. 首先, 引入离散系统的输入状态稳定性概念; 其次, 采用仿射输入定义预测控制的控制律, 并给出相应终端约束集的估计解法. 进一步, 得到预测控制闭环系统的鲁棒稳定性结论. 最后, 数值仿真验证了上述策略的有效性.     

From commercial documents to system requirements: an approach for the engineering of novel CBTC solutions

Communications-based train control (CBTC) systems are the new frontier of automated train control and operation. Currently developed CBTC platforms are actually very complex systems including several functionalities, and every installed system, developed by a different company, varies in extent, scope, number, and even names of the implemented functionalities. International standards have emerged, but they remain at a quite abstract level, mostly setting terminology. This paper presents the results of an experience in defining a global model of CBTC, by mixing semi-formal modelling and product line engineering. The effort has been based on an in-depth market analysis, not limiting to particular aspects but considering as far as possible the whole picture. The paper also describes a methodology to derive novel CBTC products from the global model, and to define system requirements for the individual CBTC components. To this end, the proposed methodology employs scenario-based requirements elicitation aided with rapid prototyping. To enhance the quality of the requirements, these are written in a constrained natural language (CNL), and evaluated with natural language processing (NLP) techniques. The final goal is to go toward a formal representation of the requirements for CBTC systems. The overall approach is discussed, and the current experience with the implementation of the method is presented. In particular, we show how the presented methodology has been used in practice to derive a novel CBTC architecture.     

The Tethered Satellite System as a new remote sensing platform

Abstract

The Tethered Satellite System is a joint US-Italian programme for the study and design of a sub-satellite deployed from the Shuttle by means of a long tether. Two preliminary demonstration flights (the first upwards, the second downwards to 100 km) have been proposed to conduct several scientific and engineering experiments. Furthermore an improved multipurposes tethered platform is under study, to be deployed by future space stations at different low altitudes, where free-flying satellites have a short lifetime. Starting from the existing characteristics, the authors analyse the improvements necessary to achieve the performance required for remote sensing operational missions. Several authors have shown that, in station keeping, a tether control allows the longitudinal and in-plane/out-of-plane oscillations to be damped. Therefore the sub-satellite position can be accurately controlled and measured, also using active tracking systems during the short observation time interval. As far as attitude is concerned, a deeper study is needed to identify the attitude measurement and control systems of the future multipurpose platform. In order to obtain a design value representing the most stringent condition, the along-track stereoscopic coverage using linear arrays is considered. After an analysis of the attitude stability rate required by STEREOSAT and MAPSAT, and of the geometric errors involved in this kind of observation, it is shown that a value of 10^?4deg/s or better will allow the multipurpose tethered platform to be used for different remote sensing missions.     

输入约束系统的滚动时域输出反馈控制方法研究

This paper addresses the H∞ output feedback control problem for discrete-time systems with actuator saturation. Initially, a constrained H∞ output feedback control approach is presented in the framework of linear matrix inequalities (LMI) optimization. Under certain assumptions on the disturbance energy bound, closed-loop H∞ performance is achieved. Furthermore, the moving horizon strategy is applied to an online management of the control performance so that the closed-loop system can satisfy control constraints in the case of unexpected large disturbances. A dissipation constraint is derived to achieve the moving horizon closed-loop system dissipative. Simulation results show that the constrained H∞ controller works effectively under the disturbance assumption and that the moving horizon H∞ controller can trade-off automatically between satisfying control constraints and enhancing performance.