Approach to robust multivariable combustion control design

Two robust controller structures are presented. These two structures affect the process in different ways, and so both could be joined together to give more robust control than each controller separately. The structure was used for combustion control which represents multivariable and nonlinear problems with time delay. Simulation results for a closed-loop control system are presented and discussed. The procedure for designing robust multivariable control was supported with computer-aided control system design tools.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A robust delay-dependent guaranteed cost PID multivariable output feedback controller design for time-varying delayed systems: An LMI optimization approach

With cost efficiency a technological imperative today, the future impact of control technology does not depend on new algorithms and theories alone. Such developments need to be employed rapidly, reducing the time involved in deploying controllers for new applications. Furthermore, the insertion of advanced control on a large scale cannot require significant numbers of highly skilled (e.g., Ph.D.-degreed) staff. Thus control technology must be packaged in a form that allows small teams of control engineers to efficiently exploit new research developments and to minimize the cycle time from specification to product. It is a sign of the maturity of control that this packaging is now being accomplished through the development of computer-aided control system design (CACSD) tools. In industries where customized control applications are a frequent demand, CACSD tools that automate several of the steps involved in the practice of control design are now regularly used. At the same time, research continues toward the goal of end-to-end (specification to deployment-ready software) control design automation. No practicing control engineer today can afford to be ignorant of CACSD; it must be considered as much a part of one's professional education as, say, the first course in nonlinear control. This chapter provides an introduction to CACSD, with specific emphasis on control design automation. System modeling, performance specifications by way of mathematical criteria, and iterative algorithms for realizing an ultimately satisfactory controller are among the topics covered. In other chapters in this volume, the state of the art and current research trends in CACSD are discussed in depth from the perspective of two control application domains???-???automotive powertrain control (Chapter 12) and flight control (Chapter 13). The latter application is also used to illustrate the general observations in this chapter.

This paper presents two different robust controllers for boost converters with two stages in a cascade. The first robust controller is monovariable; that is, the duty-cycle is the same for the two switches. The monovariable controller ensures that some prescribed constraints on pole placement and control effort are met, and optimizes the load disturbance rejection, while takes into account the uncertainty in certain parameters. The first controller is then compared with a multivariable robust controller; that is, with independent duty cycles in each switch. The multivariable controller takes into account the same uncertainty, constraints and optimization function. The comparison shows that the multivariable controller performs better at the expense of a slightly more complex implementation; that is, the multivariable controller provides a better rejection of the load disturbance. The paper also describes simulations and experimental results that are in perfect agreement with theoretical derivations.

Mission of Unmanned Aerial Vehicle (UAV) “Elang Avionik” is surveillance and aerial photographs. Therefore the flight of UAV must be stable and controlable, and first step activity is dynamic modelling and stability analisys. The problems of UAV system is disturbance, noise of sensor, MIMO and uncertainty dynamic model. For good result using the multivariable robust control, with some step research that is: (1)modeling and stability analysis, (2) design and implementation of PID control system, (3) flight dynamic parameter identification, (4) design and implementation of hardware in the loop simulation, (5) design and implementation of multivariable robust control, (6) test and evaluation of system. Simulation result show that the eigen value in longitudinal is: phugoid mode = –0,061293±0,40526i and non-oscillation mode = –6,1121±4,9253. In lateral directional is:dutch roll mode = –0,91089±5,7994i, spiral mode= –0,036563, and roll subsidence mode = –12,7181. Location of poles system on the left of imaginary axis, the means that the character of system is dynamic stable. But settling time to steady state condition is very long and improved by control system design.&#x0D; Key word: State space, Longitudinal, Lateral, Stable static, Stable dynamic

Robust Multivariable Control of Nuclear Power Plant

Control design for nonlinear process models using linear robust control methods: An FCCU example

In this paper, we overview the design and development of robust multivariable control design to highlight some of the pragmatic automotive engineering control issues with an emphasis on a non-trivial application of Hybrid Electric Vehicle (HEV) Torque Management. We shall outline that most existing torque management approaches are not model-based dynamical systems, or do not address key concepts of robust stability and performance. We shall also discuss some advantages that robust control systems could offer to a wider automotive control applications. In part II, we show representative simulation results verifying that robust control systems design could be a breakthrough to the production of hybrid electric vehicles by yielding significant improvements on the emission, fuel consumption, calibration time and cost. Our contribution is aimed at the fact that cutting-edge robust controllers could be broadly adopted to tackle increasingly challenging problems of the automotive industry.

Design and implementation of multi-variable [formula omitted] robust control for the underground coal gasification project Thar

Robust velocity and height control problem is dealt with for hypersonic vehicles subject to highly nonlinearity and uncertainties. The linear robust controller design for nonlinear systems suffers from the conservation problem, because the nonlinear dynamics are considered as uncertainties. In this paper, a feedback linearization controller is firstly applied to achieve the dynamic decoupling of the velocity and height channels. Then, robust controllers are designed for each channel to restrain the effects of the parametric uncertainties, external disturbances, and nonlinear dynamics, which cannot be counteracted accurately by the feedback linearization technique. This method can guarantee the robust stability and robust tracking properties of the closed-loop control system, while the conservation of the robust controller design can be reduced because the nonlinear information of dynamic system is used. Simulation comparisons are given to show the advantages of the proposed robust nonlinear control method.

Since the computed torque or inverse dynamics control techniques are based on a good understanding of the controlled system dynamics and even its environment; the objection for the real-time application is unrealizable for the unknown systems. To tackle this problem, this study developed a robust adaptive fuzzy sliding-mode control system based on the H/sup /spl infin// tracking design technique. The developed control system is comprised of a fuzzy controller and a robust controller. The fuzzy controller is utilized to approximate an ideal controller by the tuning algorithms based on the Lyapunov sense, and the robust controller is designed to achieve H/sup /spl infin// robust tracking performance. To investigate the effectiveness of the developed control system, it is applied to a wing rock motion control system. Simulation results demonstrate that the proposed control system can achieve favorable tracking performances with unknown system dynamics.

International audience

This paper reviews robust feedback control applications in power system. Robust control concept in power system control area evolves by the way of uncertainty modeling. Uncertainties can be caused by variation of loading, load parameters, network topology and machine parameters. One direct way to take into consideration of uncertainties is to enumerate various system operating conditions and use a set of linear time invariant systems to model the power systems. Enumeration method is used in robust control signal selection and robust controller design. Another way is to model uncertainties as structured or unstructured uncertainties. Controllers are designed based on nominal system condition to tolerate uncertainty as much as possible. The controller synthesis problem is solved by either Algebraic Ricatti Equation (ARE) or Linear Matrix Inequality (LMI). LMI is shown to be more flexible in controller design since it provides a way to specify system dynamic performance. Most recently, linear parameter varying (LPV) concept expands the use of enumeration method to express a set of linear time invariant (LTI) systems with state space dependent on linear parameters. LPV based control methods extend gain scheduling to design linear control for each operating conditions and overall a nonlinear controller for the varying parameter system.

Background: The conventional method using one-degree-of-freedom (1DOF) controller for Permanent Magnet Synchronous Motor (PMSM) servo system has the trade-off problem between the dynamic performance and the robustness. Methods: In this paper, by using H∞ control theory, a novel robust two-degree-of-freedom (2DOF) controller has been proposed to improve the position control performance of PMSM servo system. Using robust control theory and 2DOF control theory, a H∞ robust position controller has been designed and discussed in detail. Results: The trade-off problem between the dynamic performance and robustness which exists in one-degree-of-freedom (1DOF) control can be dealt with by the application of 2DOF control theory. Then, through H∞ control theory, the design of robust position controller can be translated to H∞ robust standard design problem. Moreover, the control system with robust controller has been proved to be stable. Conclusion: Further simulation results demonstrate that compared with the conventional PID control, the designed control system has better robustness and attenuation to the disturbance of load impact.

The problem of robust velocity and height control is dealt with for hypersonic vehicles subject to high nonlinearity and uncertainties. Robust linear controller design for nonlinear systems suffers from the problem of conservation because the nonlinear dynamics are considered as uncertainties. In this paper, a feedback linearization controller is firstly applied to achieve dynamic decoupling of the velocity and height channels. Robust controllers are then designed for each channel to achieve the desired tracking and restrain the effects of parametric uncertainties, external disturbances, and nonlinear dynamics, which cannot be accurately counteracted by the feedback linearization technique. This method can guarantee the robust stability and robust tracking properties of the closed-loop control system. Moreover, the conservation of the robust controller design can be reduced because the nonlinear information of the dynamic system is used. Simulation results are given to show the advantages of the proposed robust nonlinear control method compared with its linear counterpart.