F. Dumortier

A comparative study of self-adaptive long-range predictive control methods

Abstract During the last years a number of interesting control methods were published all having the same common idea: the control action is based on a long-range prediction of the process output. Four of these methods are compared in this paper. At least for three of them industrial applications are known, indicating that long-range predictive control methods are likely to be a useful tool for real-life applications. These adaptive control methods are compared by means of a simulation study. Special attention is paid to their robustness w.r.t. unmodelled dynamics, parameter variations, process noise and changing dead-time. Also dealt with are the number of tuning parameters that remain, as well as their efficiency and interpretation to the user.

SLICOT, a subroutine library in control and systems theory

Abstract Past initiatives with respect to realising control libraries are analyzed. A new collaborative initiative is introduced. The design of a new control library SLICOT is presented and the first release of this library is discussed

A Comparative Study of Self-Adaptive Long-Range Predictive Control Methods

Abstract During the last years a number of interesting control methods were published all having the same common idea : the control action is based on a long-range prediction of the process output. Four of these methods are compared in this paper. At least for three of them industrial applications are known, indicating that long-range predictive control methods are likely to be a useful tool for real-life applications. These adaptive control methods are compared by means of a simulation study. Special attention is paid to their robustness w.r.t. unmodelled dynamics, parameter variations, process noise and changing dead-time. Also the number of tuning parameters that remain, as well as their efficiency and interpretation to the user are dealt with.

Computer aided design of advanced control algorithms for nuclear reactor control

This paper discusses the computer-aided design of advanced control algorithms for a nuclear PWR-reactor. The implementation of the simulation model and the integration of the control methods in a typical CADCS-package are considered. The control problem may well serve as a new benchmark problem for CADCS. To evaluate the control performance of the digital control algorithms a comparison is made between classical analog PID-control and two long-range predictive control (LRPC)-methods.<<ETX>>

Adaptive control for domestic floor heating

This article from the University of Ghent, Belgium, is an interim report on the self‐tuning and adaptive start/stop and disturbance‐rejection control of multizone low‐temperature floor heating for a house which, in common with such heating arrangements, involved large time constants and difficulties with start/stop decisions. The problem was tackled by using predictive control techniques based on self‐tuning and adaptive prediction models, as described here.

Parallelization of long-range predictive control methods

The use of parallel processing techniques offers interesting perspectives for the application of advanced control algorithms in time-critical situations. In this paper the parallelization of some long-range predictive control (LRPC) algorithms is examined. A study is made of the speed-up that can be obtained through proper parallelization of the underlying mathematical matrix routines. Two LRPC-methods are applied to the position control of a DC-servomotor.<<ETX>>

CADCS and Parallel Computing

In modern control engineering the field of Computer Aided Design in Control Systems has become a major area of research, which involves many topics: simulation, analysis and design of control systems, linear and nonlinear control, multivariable control, frequency-domain and time-domain analysis, state-space systems, continuous-time and discrete-time systems, etc.. Current CADCS software packages cover the whole spectrum of classical and modern control theory. As in many areas of science the arrival of performant microcomputers and minicomputers has boosted the level of fundamental and applied research. In CADCS new advanced and complex numerical control algorithms are continuously being developed and refined. The real-time application of these powerful control methods is however very much limited, especially in time-critical situations, due to the physical speed limits of todays microprocessors. The arrival of new computer architectures, s.a. vector computing and parallel processing, and new technologies, s.a. GaAs chips and optical fibres, can offer a breakthrough to the current computing limitations. It is now generally believed that concurrent processing is the only way to further increase computer performance and to keep the cost/performance ratio within reasonable bounds.

CADCS and Vector Processing

Abstract The field of Computer Aided Design in Control Systems has become a major topic of research in modern control engineering. Current CADCS packages cover the whole spectrum of classical and modern control theory and are being continuously updated with the latest advances in numerical control algorithms. As a result todays control engineers have access to many powerful and advanced control techniques to meet the still increasing demands from the industry. However the actual implementation of these modern techniques is still very much limited, especially in time-critical on-line situations, by the physical limits of todays sequential processors. The arrival of new computer architectures and technologies, such as vector computers and parallel processing, can offer a spectacular breakthrough to the current computing limitations. In this paper it is demonstrated that a considerable speedup is obtained when vector processing is applied to two classical but powerful long-range predictive control techniques; namely Model Algorithmic Control and Dynamic Matrix Control.

CACSD OF MULTIVARIABLE LINEAR CONTROL SYSTEMS ON MICROVAX II

Abstract In this paper two CACSD-packages for the analysis and synthesis of multivariable linear control systems are presented. Their theoretical background and specific implementation are discussed. The main characteristics of these programs are their user-friendliness and robustness. The packages can be applied in an educational environment as well as in an industrial context.

CACSD of Multivariable Linear Control Systems on MicroVAX II

Abstract In this paper two CACSD-packages for the analysis and synthesis of multivariable linear control systems are presented. Their theoretical background and specific implementation are discussed. The main characteristics of these programs are their user-friendliness and robustness. The packages can be applied in an educational environment as well as in an industrial context.