Simultaneous design and control of processes under uncertainty: A robust modelling approach

This paper presents a new methodology to integrate process design and control. The key idea in this method is to represent the system’s closed-loop nonlinear behaviour as a linear state space model complemented with uncertain model parameters. Then, robust control tools are applied to calculate bounds on the process stability, the process feasibility and the worst-case scenario. The new methodology was applied to the simultaneous design and control of a mixing tank process. The resulting design avoids the solution of computationally intensive dynamic optimizations since the integration of design and control problem is reduced to a nonlinear constrained optimization problem.     

The scenario approach for systems and control design

The ‘scenario approach’ is an innovative technology that has been introduced to solve convex optimization problems with an infinite number of constraints, a class of problems which often occurs when dealing with uncertainty. This technology relies on random sampling of constraints, and provides a powerful means for solving a variety of design problems in systems and control. The objective of this paper is to illustrate the scenario approach at a tutorial level, focusing mainly on algorithmic aspects. Its versatility and virtues will be pointed out through a number of examples in model reduction, robust and optimal control.     

Nonlinear system identification and control of chemical processes using fast orthogonal search

The use of the fast orthogonal search (FOS) method is presented for model estimation and control of nonlinear chemical processes. FOS provides a nonlinear approximation used in an inner-loop that allows for simpler linear control methods to be used as an outer-loop controller. It is a straightforward, simple-to-use method for linearization of systems based on orthogonal system identification. The control concept is derived from the method of inverse dynamic control (IDC). The novel combination of this with the FOS method of system identification results in a very efficient and effective method of control. The method is demonstrated and tested on two nonlinear chemical process control simulations and the results are shown to compare very favourably to published results on the same problems.     

化工过程工艺与控制系统集成设计研究进展

传统的序贯设计法将过程工艺设计与控制系统的设计分割成两个独立的部分进行设计,其忽略了工艺设计与过程动态性能之间的内在联系,因而无法得到整体性能最优的过程系统。过程工艺与控制系统集成设计方法相较于传统的分步序贯设计方法能获得更优的设计参数和更好的控制效果。近年来,该领域取得了大量研究成果。本文从两方面对近年来该领域的研究进展进行综述。首先,根据过程工艺与控制集成设计在求解方法上的不同,从基于可控性指标的方法、动态规划方法、鲁棒方法、嵌入式控制优化方法等方面进行综述,并详细讨论各种方法优缺点。其次,从文献中采取不同控制策略的角度,对该领域的研究进展进行综述。最后对过程工艺与控制系统集成优化设计方法进行了总结和展望。     

Quantitative feedback design of air and boost pressure control system for turbocharged diesel engines

For modern diesel engines, variable geometry turbocharger (VGT) is used to boost engine power output. In addition, exhaust gas recirculation (EGR) is utilized to reduce engine out NO_x emission. To realize these functions, a multivariable control system needs to control both VGT and EGR valve to deliver desired intake manifold (or boost) pressure, and desired EGR flow rate. This two-input and two-output system is nonlinear with cross-couplings between the boost and EGR responses to the input actuators, the system parameters are varying with different engine operating conditions. This paper proposes a closed loop design of a multivariable VGT/EGR control system for a turbocharged diesel engine. The control system is synthesized based on quantitative feedback theory to maintain robust stability and performance via sequential MIMO loop shaping in the frequency domain. Experiment results are included from a turbocharged diesel engine to show the effectiveness of the proposed control design.     

Robust controller design for a class of nonlinear uncertain chemical processes

This article considers the issue of designing robust controllers for single-input/single-output nonlinear chemical processes whose uncertainties satisfy the so-called generalized matching condition. The nominal system (mathematical model) is assumed to be input–output linearizable and the only assumption on uncertainties is that they are bounded. A design methodology of combining the techniques of the differential geometric feedback linearization, the sliding mode control strategy and the adaptive state feedback is presented. Based on the nominal system and the related bounds of uncertainties, a hybrid nonlinear controller, which is more practicable and easily implemented than many other existing ones in the literature, is proposed. A Lyapunov-based approach is utilized to guarantee the robust stability and behavior of the closed-loop system. For demonstrating the effectiveness and applicability of the proposed scheme, we applied it to the control of a continuously stirred tank reactor (CSTR) in the presence of uncertainties including unmodeled side reaction, measuring error, and/or extra unmeasured disturbances. The potential use of a sliding observer along with the proposed scheme is also investigated in this work. Extensive simulation results reveal that the proposed scheme appears to be a practical and promising approach to the robust control of nonlinear uncertain chemical processes.     

Advanced methods of process computer control for industrial processes

In recent years, the requirements for the performance of multilevel process control, including feedforward and feedback control, monitoring and optimization have increased. Applying process computers and micro computers, the functions of analog equipment and hardwired logic devices cannot only be replaced. Extended or quite new methods can be realized improving the performance of multilevel process control. These advanced methods for process control are characterized by: more sophisticated, better adjusted control algorithms, forecasting of process variables, estimation of not directly measurable variables, computer aided design of algorithms and adaptive or selftuning algorithms. The basis of these advanced methods are mathematical models of the processes and their signals, often gained by the process computer itself during on-line operation.The present paper discusses first how process models in open and closed loop can be obtained by on-line identification methods. Then, based on these models, the computer aided design of control algorithms, adaptive control algorithms and adaptive steady-state on-line optimization will be regarded. Monitoring of not direct measurable variables will be mentioned. For some methods, practical results with real and simulated processes are shown. Interactive process computer software packages are used which can easily be transferred to other process computers.     

Analyses of cognitive processes in train traffic control

The study of complex information processing and problem-solving situations in practice is discussed, in particular the methods of analysing the cognitive aspects in train dispatcher's work. Some parallels are drawn with related work in processing industries. A prerequisite for the approach to the issue was that the results would have to yield very concrete starting-points for the design of technical aids. The research started from the assumption that it would be extremely difficult to derive design indications from apparently observable actions of the train dispatchers. This led to the choice of a combination of a preliminary simulation study followed by analysis of cognitive processes in the train dispatcher's behaviour in every day practice. It turned out to be helpful for the analysis to draw parallels between the cognitive processes in the behaviour of the train dispatchers and the way of working/thinking shown by test subjects in complex problem-solving experiments.     

New filters for internal model control design

In this paper we study the design of a new two-degree-of-freedom filter for the internal model control (IMC) method. The new filter alleviates some disadvantages of the standard IMC filter when the IMC method is applied to unstable plants that do not have non-minimum-phase zeros. We show that by employing the new filter, the resulting system has a flatter frequency response, better stability robustness, and little overshoot in the step response. Furthermore, one of its design parameters can be related directly to the closed-loop bandwidth and the other parameter can be used to control the recovery time after an overshoot has occurred in the step response. These features are important in the application of the IMC method to a new approach of adaptive robust control. Examples are given in the paper to illustrate the new filter design.     

An improved nonlinear control design for series DC motors

A series DC motor must be represented by a nonlinear model when nonlinearities such as magnetic saturation are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. In this paper, the recursive design method is applied to generate nonlinear control, nonlinear PI control, and robust control, and these controls are shown to be efficient and robust in the simulation study compared to existing results.     

Robust H∞ control design for systems with structured parameter uncertainty

In a recent paper a unification of the H₂ (LQG) and H_∞ control-design problems was obtained in terms of modified algebraic Riccati equations. In the present paper these results are extended to guarantee robust H₂ and H_∞ performance in the presence of structured real-valued parameter variiations (ΔA, ΔB, ΔC) in the state space model. For design flexibility the paper considers two distinct types of uncertainty bounds for both full- and reduced-order dynamic compensation. An important special case of these results generates H₂/H_∞ controller designs with guaranteed gain margins.     

Cross-directional control of sheet and film processes

Sheet and film processes include polymer film extrusion, coating processes of many types, paper manufacturing, sheet metal rolling, and plate glass manufacture. Identification, estimation, monitoring, and control of sheet and film processes are of substantial industrial interest since effective control means reduced usage of raw materials, increased production rates, improved product quality, elimination of product rejects, and reduced energy consumption. This paper reviews recent developments in sheet and film process control with particular attention to the effectiveness of existing techniques at addressing the critical aspects of sheet and film processes.     

Process analytical technologies and real time process control a review of some spectroscopic issues and challenges

Process analytical technologies (PAT) are increasingly being explored and adopted by pharmaceutical and industrial biotechnology companies for enhanced process understanding, Quality by Design (QbD) and Real Time Release (RTR). To achieve these aspirations there is a critical need to extract the most information, and hence understanding, from complex and often ‘messy’ spectroscopic data. This contribution reviews a number of new approaches that have been shown to overcome the limitations of existing calibration/modelling methodologies and describes a practical system which would enhance robustness of the closed loop process control system and overall ‘control strategy’. Application studies are described of the use of on-line spectroscopy for the monitoring and control of a downstream solvent recovery column, batch cooling crystallization and pharmaceutical fermentation.     

A mid-ranging control strategy for non-stationary processes and its application to dissolved oxygen control in a bioprocess

In this study a modified mid-ranging strategy is proposed where the controller for the secondary manipulated variable uses its own output as its setpoint, possibly with an offset and/or re-scaling. This modification allows the manipulated variables to increase in unison so that the mid-ranging advantage of utilizing the fast dynamics of the primary controller to regulate the process can be achieved also in non-stationary processes, while not adding complexity to the controller. The proposed control strategy has been implemented in pilot-scale (500 l) industrial bioprocesses where it is used to control the dissolved oxygen level by manipulating agitator speed and aeration rate. The controller is demonstrated to perform well in these, outperforming a reference controller which has previously been shown to give satisfactory control performance. It is also shown in similar experiments that the strategy can easily be adapted to control dissolved oxygen in bioprocesses where the feed rate is controlled using an extremum-seeking controller. The proposed strategy is generally applicable to non-stationary processes where a mid-ranging approach is suitable.     

A delta transform approach to loop gain-phase shaping design of robust digital control systems

This paper addresses the existence of loop gain-phase shaping (LGPS) solutions for the design of robust digital control systems for SISO, minimum-phase, continuous-time processes with parametric uncertainty. We develop the frequency response properties of LGPS for discrete-time systems using the Δ-transform, a transform method that applies to both continuous-time and discrete-time systems. A theorem is presented which demonstrates that for reasonable specifications there always exists a sampling period such that the robust digital control problem has a solution. Finally, we offer a procedure for estimating the maximum feasible sampling period for LGPS solutions to robust digital control problems.     

A comparison of adaptive control strategies for hot steel strip rolling mills

Many modeling situations occur in which the plant has uncertain dynamics, nonlinearities, time varying characteristics and noise corrupted input and output measurements. These processes generally require a human operator whose function is to provide intelligent modeling and control. This exact situation occurs in the modeling and control of roll force in a hot steel rolling mill. It is the purpose of this paper to investigate and compare various adaptive control strategies for this problem.The first strategy uses a parameter identification technique to track the parameters in the roll force setup model from one steel run to the next. The next algorithm provides feedback control from run to run by an adaptive controller which uses a linear reinforcement learning scheme to adjust its parameters. The third method accounts for the above complexities by approaching the problem from a behavioral and structural point of view. The behavior of the model is assessed through a performance evaluator and the model is modified structurally and parametrically to improve the performance of the system as the process evolves. The derivation is based on correlation techniques and linear reinforcement learning theory, the latter of which provides memory and intelligence to the algorithm to model the decision process of the human operator. The results of this work serve to reinforce the opinion that the nonlinear mathematical structure of the model should be able to change from one steel run to the next in order to compensate for changes in mill characteristics and in the mill environment. Modeling results are presented from actual mill data and comparisons are made with time invariant models. In addition, the algorithms are general enough so that they may be easily applied to other processes that seem to defy traditional modeling techniques. They are not case dependent.     

Robust control of delay systems: a sliding mode control design via LMI

This paper considers the sliding mode control of uncertain systems with single or multiple, constant or time-varying state-delays, submitted to additive perturbations. The sliding surface is designed so to maximize the calculable set of admissible delays. The conditions for the existence of the sliding regime are studied by using Lyapunov–Krasovskii functionals and Lyapunov-Razumikhin functions. LMIs are used for the optimization procedure. Two examples illustrate the proposed method.     

An experimental study on the information design of CRT display in process control systems

A task analysis was first initiated in this study for the supervisor in process control systems. An experiment was then conducted by simulating a Reactor Water Cleanup System and the effects of some variables were focused upon, e.g. format types (graphical vs. digital), volumes of data (number of figures) and layout methods of data (process, function, importance) on the human-machine interface design. The main effects of format types, volumes, and layout methods of data and the two-way interaction effects, between format types and volumes of data and between volumes of data and layout methods of data, were observed from the results of the experiment to be significant for the searching tasks. Some main effects and the interaction effects were also observed to be significant for the detection and prediction tasks. The importance of the layout method was then suggested here to be preferred for supervisory tasks. Additionally, the optimal volumes of data were roughly eight figures per screen and the graphical formats were better than digital formats for either searching or detection /prediction tasks. Finally, some further researches are recommended.     

Further results on sampled-data design for robust control of a single qubit

This paper presents further results on the robust control method for qubit systems in Dong et al. (2013) Dong, D., Petersen, I.R., &; Rabitz, H. (2013). Sampled-data design for robust control of a single qubit. IEEE Transactions on Automatic Control, 58, 2654–2659.[Crossref], [Web of Science ®] , [Google Scholar]. Based on the properties of an antisymmetric system, an alternative method is presented to analyse and exclude singularity intervals in the proof of partial original results. For the case of amplitude damping decoherence, a larger sampling period is presented when the upper bound of the probability of failure is small enough. For the case of phase damping decoherence, a larger sampling period is given when the lower bound of the target coherence is large enough. Furthermore, we provide improved sampling periods for amplitude damping decoherence and phase damping decoherence without the above prior constraints.