Showing papers in "Journal of Process Control in 2003"

TL;DR: In this article, the authors present analytic rules for PID controller tuning that are simple and still result in good closed-loop behavior, including the half-rule for obtaining the effective time delay.

TL;DR: An overview of available results of state and parameter approaches for chemical and biochemical processes is given and the design of online parameter estimation schemes will be introduced.

TL;DR: In this paper, the presence of oscillations in selected frequency ranges is determined using a new method based on the regularity of the zero crossings of filtered autocovariance functions.

TL;DR: In this paper, a modified IMC structure for unstable processes with time delays is proposed, where setpoint tracking and disturbance rejection can be designed separately, and a method is proposed to tune the modified structure with an emphasis on the robustness of the structure.

TL;DR: In this paper, a multi-loop system is decomposed into a number of equivalent single loops for design, and an effective open-loop process (EOP) is formulated without prior knowledge of controller dynamics in other loops, and, hence, controller can be designed directly and independently.

TL;DR: Closest distance to center (CDC) is proposed in this paper as an alternative for outlier detection and better performance was obtained when CDC is incorporated with MVT, compared to using CDC and MVT alone.

TL;DR: A large-scale controller performance assessment system spanning over 14,000 PID controllers in 40 plants at 9 sites worldwide was developed by the Eastman Chemical Company (ECC).

TL;DR: In this paper, the authors describe some broad classes of nonlinear model structures, which may be approximately characterized as mildly nonlinear, strongly nonlinear or of intermediate nonlinearity, depending on the different ways they violate linear intuition.

TL;DR: In this article, a nonlinear model predictive control (NMPC) based on a Wiener model with a piecewise linear gain is presented, which retains all the interested properties of the classical linear model predictive controller (MPC) and keeps computations easy to solve due to the canonical structure of the nonlinear gain.

TL;DR: In this article, the authors examined the potentials of iterative learning control (ILC) as a framework for industrial batch process control and optimization and showed how the concept of ILC can be fused with model predictive control (MPC) to build an integrated end product and transient profile control technique for industrial chemical batch processes.

TL;DR: In this paper, a modified PI-PD Smith predictor is proposed to improve the control of processes with large time constants or an integrator or unstable plant transfer functions plus long dead-time for reference inputs and disturbance rejections.

TL;DR: In this article, a design method for decentralized PI control systems with guaranteed closed-loop stability is presented, where a detuning factor for each loop is specified based on a diagonal dominance index and appropriate controller settings are determined using this index and the stability region.

TL;DR: In this paper, a framework for nonlinear systems analysis based on controllability and observability covariance matrices is presented, which is used for reduction of the nonlinear model.

TL;DR: In this paper, a fuzzy decomposition of the steady state map is proposed to identify and control complex nonlinear plants using multi-model approach, and a novel control scheme that is based on the multi model strategy is proposed.

TL;DR: In this article, the output feedback of a uniformly observable MIMO system with high-gain observers is combined with state feedback to achieve output feedback stabilization, and it is shown that the resulting closed loop is asymptotically stable.

TL;DR: In this article, a novel tuning strategy based on RPN for MIMO MPC is presented, which is applied in the controller design of an air separation plant and a CSTR with the Van de Vusse's reaction.

TL;DR: In this paper, the disturbance model, used by MPC algorithms to achieve offset-free control, is optimally designed to enhance the robustness of single-model predictive controllers.

TL;DR: It is shown how the minimum variance output space can be considered an optimal subspace of the general closed-loop output space and a simple control performance calculation which uses orthogonal projection of filtered output data onto past closed- loop data is proposed.

TL;DR: In this paper, a grey box model of a pilot heating process is used to estimate the thermal diffusivity of the process and a continuous-discrete extended Kalman filter is used for model expansion.

TL;DR: In this paper, a systematic method is proposed for the design of general multivariable controller for complex processes to achieve the goal of fast loop responses with acceptable overshoots and minimum loop interaction while maintaining low complexity of the feedback controller.

TL;DR: In this paper, a systematic approach to derive analytical expressions for relay feed back responses is proposed based on the observation that a relay feedback test consists of a series of step inputs and a stable limit cycle implies a convergent infinite series.

TL;DR: In this article, a simple receding horizon (or model predictive) control for state delayed systems is presented and its solution is given in a closed form by a reduction method, which can be used as a stabilizing control for time-delay systems.

TL;DR: In this paper, the control strategy of a reactive distillation for synthesis of MTBE is investigated, and a linear control is still possible since a controlled and manipulated variable-pairing scheme that exhibits a sufficiently large range of near linear relations can be found, if we operate at constant reflux ratio.

TL;DR: In this article, the authors propose an approach for the supervisory control of fed-batch fermentation during process development, where transitions in the process are explicitly modeled and characterized using multivariate rules and online data is used to identify the occurrence of transitions and thus track the process across different phases.

TL;DR: This review will expound the basic tenets of the cybernetic framework in its current state of evolution, highlight the various developments of this methodology, and foster its future for model-based control of bioreactors towards maintaining a meticulously monitored metabolic activity.

TL;DR: In this article, a pattern-based predictive control (PPC) scheme was proposed to maintain the product purity in reactive distillation (RD) of ETBE through developing a pattern based predictive control scheme.

TL;DR: In this article, a supervisory multiple model control scheme, SMMC, is proposed to handle nonlinear behaviour in industrial processes. But the scheme is not suitable for nonlinear control and it requires the use of multiple model observers (MMOs) for the selection of local controllers.

TL;DR: In this paper, a subspace approach was proposed to identify the optimal residual models for process fault detection and isolation in a multivariate continuous-time system, where the fault gain matrix is always available no matter how the faults vary with time.

TL;DR: A regional-knowledge index is proposed in this study and applied in the analysis of dynamic artificial neural network models in process control to tackle the extrapolation problem and assure stability of the control system.

TL;DR: In this paper, a method of tuning for PI controllers with one-way lead/lag decoupling tuning is demonstrated for 2×2 input-output systems, based on finite frequency response data.