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Control System Design (control + system_design)
Selected AbstractsEFFECTS OF RANDOM SHIFTS OF TESTING EQUIPMENT ON PROCESS CONTROL SYSTEM DESIGN AND SELECTION OF PROCESS CONTROL POLICIES*PRODUCTION AND OPERATIONS MANAGEMENT, Issue 2 2002JIE DING This paper studies issues associated with designing process control systems when the testing equipment is subjected to random shifts. We consider a production process with two states: in control and out of control. The process may shift randomly to the out-of-control state over time. The process is monitored by periodically sampling finished items from the process. The equipment used to test sampled items also is assumed to have two states and may shift randomly during the testing process. We formulate a cost model for finding the optimal process control policy that minimizes the expected unit time cost. Numerical results show that shifts of the testing equipment may significantly affect the performance of a process control policy. We also studied the effects of the testing equipment's shifts on the selection of process control policies. [source] Adaptive recurrent neural network control of biological wastewater treatmentINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 2 2005Ieroham S. Baruch Three adaptive neural network control structures to regulate a biological wastewater treatment process are introduced: indirect, inverse model, and direct adaptive neural control. The objective is to keep the concentration of the recycled biomass proportional to the influent flow rate in the presence of periodically acting disturbances, process parameter variations, and measurement noise. This is achieved by the so-called Jordan Canonical Recurrent Trainable Neural Network, which is a completely parallel and parametric neural structure, permitting the use of the obtained parameters, during the learning phase, directly for control system design. Comparative simulation results confirmed the applicability of the proposed control schemes. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 173,193, 2005. [source] Stable robust feedback control system design for unstable plants with input constraints using robust right coprime factorizationINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 18 2007Mingcong Deng Abstract A stable robust control system design problem for unstable plants with input constraints is considered using robust right coprime factorization of nonlinear operator. For obtaining strong stability of the closed-loop system of unstable plants with input constraints, a design scheme of robust nonhyphen-linear control system is given based on robust right coprime factorization. Some conditions for the robustness and system output tracking of the unstable plant with input constraints are derived. Numerical examples are given to demonstrate the validity of the theoretical results. Copyright © 2007 John Wiley & Sons, Ltd. [source] Polynomial control: past, present, and futureINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 8 2007Vladimír Ku Abstract Polynomial techniques have made important contributions to systems and control theory. Engineers in industry often find polynomial and frequency domain methods easier to use than state equation-based techniques. Control theorists show that results obtained in isolation using either approach are in fact closely related. Polynomial system description provides input,output models for linear systems with rational transfer functions. These models display two important system properties, namely poles and zeros, in a transparent manner. A performance specification in terms of polynomials is natural in many situations; see pole allocation techniques. A specific control system design technique, called polynomial equation approach, was developed in the 1960s and 1970s. The distinguishing feature of this technique is a reduction of controller synthesis to a solution of linear polynomial equations of a specific (Diophantine or Bézout) type. In most cases, control systems are designed to be stable and meet additional specifications, such as optimality and robustness. It is therefore natural to design the systems step by step: stabilization first, then the additional specifications each at a time. For this it is obviously necessary to have any and all solutions of the current step available before proceeding any further. This motivates the need for a parametrization of all controllers that stabilize a given plant. In fact this result has become a key tool for the sequential design paradigm. The additional specifications are met by selecting an appropriate parameter. This is simple, systematic, and transparent. However, the strategy suffers from an excessive grow of the controller order. This article is a guided tour through the polynomial control system design. The origins of the parametrization of stabilizing controllers, called Youla,Ku,era parametrization, are explained. Standard results on reference tracking, disturbance elimination, pole placement, deadbeat control, H2 control, l1 control and robust stabilization are summarized. New and exciting applications of the Youla,Ku,era parametrization are then discussed: stabilization subject to input constraints, output overshoot reduction, and fixed-order stabilizing controller design. Copyright © 2006 John Wiley & Sons, Ltd. [source] A stability guaranteed active fault-tolerant control system against actuator failuresINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 12 2004Midori Maki Abstract In this paper, a new strategy for fault-tolerant control system design has been proposed using multiple controllers. The design of such controllers is shown to be unique in the sense that the resulting control system neither suffers from the problem of conservativeness of conventional passive fault-tolerant control nor from the risk of instability associated with active fault-tolerant control in case that an incorrect fault detection and isolation decision is made. In other words, the stability of the closed-loop system is always ensured regardless of the decision made by the fault detection and isolation scheme. A correct decision will further lead to optimal performance of the closed-loop system. This paper deals with the conflicting requirements among stability, redundancy, and graceful degradation in performance for fault-tolerant control systems by using robust control techniques. A detailed design procedure has been presented with consideration of parameter uncertainties. Both total and partial actuator failures have been considered. This new control strategy has been demonstrated by controlling a McDonnell F-4C airplane in the lateral-direction through simulation. Copyright © 2004 John Wiley & Sons, Ltd. [source] Adaptive robust stabilization of dynamic nonholonomic chained systemsJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 3 2001S. S. Ge In this article, the stabilization problem is investigated for dynamic nonholonomic systems with unknown inertia parameters and disturbances. First, to facilitate control system design, the nonholonomic kinematic subsystem is transformed into a skew-symmetric form and the properties of the overall systems are discussed. Then, a robust adaptive controller is presented in which adaptive control techniques are used to compensate for the parametric uncertainties and sliding mode control is used to suppress the bounded disturbances. The controller guarantees the outputs of the dynamic subsystem (the inputs to the kinematic subsystem) to track some bounded auxiliary signals which subsequently drive the kinematic subsystem to the origin. In addition, it can also be shown all the signals in the closed loop are bounded. Simulation studies on the control of a unicycle wheeled mobile robot are used to show the effectiveness of the proposed scheme. © 2001 John Wiley & Sons, Inc. [source] Modeling and predictive control using fuzzy logic: Application for a polymerization systemAICHE JOURNAL, Issue 4 2010Nádson M. N. Lima Abstract In this study, a predictive control system based on type Takagi-Sugeno fuzzy models was developed for a polymerization process. Such processes typically have a highly nonlinear dynamic behavior causing the performance of controllers based on conventional internal models to be poor or to require considerable effort in controller tuning. The copolymerization of methyl methacrylate with vinyl acetate was considered for analysis of the performance of the proposed control system. A nonlinear mathematical model which describes the reaction plant was used for data generation and implementation of the controller. The modeling using the fuzzy approach showed an excellent capacity for output prediction as a function of dynamic data input. The performance of the projected control system and dynamic matrix control for regulatory and servo problems were compared and the obtained results showed that the control system design is robust, of simple implementation and provides a better response than conventional predictive control. © 2009 American Institute of Chemical Engineers AIChE J, 2010 [source] Control of a high-purity ethylene glycol reactive distillation column with insights of process dynamicsAICHE JOURNAL, Issue 8 2009Kejin Huang Abstract Inventory control is often regarded as less important than product quality control in the operation of reactive and nonreactive distillation columns (i.e., often detuned considerably in control system design). For the high-purity ethylene glycol reactive distillation column, the inventory control of top condenser is, however, an exception and plays actually a crucial role in the stable and effective process operation, reminding the necessity to thoroughly investigate the intricate dynamic mechanism and its complicated implications on control system synthesis and design. In this article, the dynamics of a high-purity ethylene glycol reactive distillation column is examined, and it is found that the complicated dynamics, for example, the nonminimum phase behavior and process nonlinearity, can be suppressed considerably with the tight inventory control of the top condenser. Moreover, an extremely low controllability is detected, implying the potential difficulties in process operation and thus the need of process design modification. In terms of these insights obtained, two control schemes are devised and studied. It is demonstrated that sharp improvement could be acquired in control system performance when the tight inventory control has been implemented in the top condenser. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source] On the synthesis of time-varying LQG weights and noises along optimal control and state trajectoriesOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 3 2006L. G. Van Willigenburg Abstract A general approach to control non-linear uncertain systems is to apply a pre-computed nominal optimal control, and use a pre-computed LQG compensator to generate control corrections from the on-line measured data. If the non-linear model, on which the optimal control and LQG compensator design is based, is of sufficient quality, and when the LQG compensator is designed appropriately, the closed-loop control system is approximately optimal. This paper contributes to the selection and computation of the time-varying LQG weighting and noise matrices, which determine the LQG compensator design. It is argued that the noise matrices may be taken time-invariant and diagonal. Three very important considerations concerning the selection of the time-varying LQG weighting matrices are turned into a concrete computational scheme. Thereby, the selection of the time-varying LQG weighting matrices is reduced to selecting three scalar design parameters, each one weighting one consideration. Although the three considerations seem straightforward they may oppose one another. Furthermore, they usually result in time-varying weighting matrices that are indefinite, rather than positive (semi) definite as required for the LQG design. The computational scheme presented in this paper addresses and resolves both problems. By two numerical examples the benefits of our optimal closed-loop control system design are demonstrated and evaluated using Monte Carlo simulation. Copyright © 2005 John Wiley & Sons, Ltd. [source] | ||||||||||