A Modified Internal Model Control for an Unstable Plant with an Integrator in Continuous-Time System

Shibasaki, Hiroki; Endo, Junichi; Hikichi, Y.; Tanaka, Ryo

doi:10.7763/ijiee.2013.v3.334

Cited by 6 publications

(2 citation statements)

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“…The direct feedback path of the process, characterized by the gain K f , is used only for integral and some unstable processes, in order to convert the original process P into a stable proportional process P0 (with the gain K P 0 bounded and nonzero), called compensated process. The process compensation technique has been firstly used in [22,23] for unstable processes, and in [24] for stable integral processes. For stable proportional processes, the feedback gain K f is fixed to zero, so that the compensated process and the original process are one and the same, and the control variables C and U are identical.…”

Section: Introductionmentioning

confidence: 99%

A Practical Unified Algorithm of P-IMC Type

Cirtoaje

2020

Processes

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The paper presents a practical algorithm of the proportional-internal model control (P-IMC) type that can be applied to control a wide class of processes: Stable proportional processes, integral processes and some unstable processes. The P-IMC algorithm is a suitable combination between the P0-IMC algorithm and the P1-IMC algorithm, which are characterized by a too weak and a too strong impact of the tuning gain on the control action, respectively. The overall controller has five parameters: A tuning parameter K, three model parameters (steady-state gain, settling time, and time delay) and a process feedback gain used only for integral or unstable processes, to turn them into a compensated process (stable and of proportional type). For a step setpoint, the initial value of the compensated process input is approximately K times its final value. Furthermore, for K = 1 , the compensated process input is close to a step shape (step control principle). These properties enable a human operator to check and adjust online the model parameters. Due to its control performance, robustness to modeling error, and capability to be easily tuned and applied for all industrial processes, the P-IMC algorithm could be a viable alternative to the known PID algorithm. Numerical simulations are given to highlight the performance and the flexibility of the algorithm.

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Section: Introductionmentioning

confidence: 99%

A Practical Unified Algorithm of P-IMC Type

Cirtoaje

2020

Processes

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“…This is possible because the model addresses the compensated process, which is always stable and of proportional type (with the steady-state gain finite and nonzero or, equivalently, with no pole and zero at the origin). Such a control technique based on process compensation has been introduced in [17] for unstable processes (under the name of "modified IMC"), in [18] for integral-type processes, and in [19] for unstable integral processes.…”

Section: Introductionmentioning

confidence: 99%

A quasi-universal practical IMC algorithm

Cirtoaje

2017

Automatika

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The control algorithm incorporates a process feedback path of pure proportional type (only for integral-type or unstable processes), a process model of second order plus time delay and a realizable second-order internal controller which has not a tuning filter time constant as usual in the classical IMC design, but a tuning gain with standard value 1, that can be used by the human operator to get a strong or weak control action. The model parameters (steady-state gain, time delay and transient time) can be easily experimentally determined and can be online verified and corrected. The algorithm is practical and quasi-universal because it is easily tunable, has a unique form and can be applied to almost all process types: stable proportional processes (with or without time delay, with or without overshoot, of minimum or nonminimum phase), integral processes and even some unstable processes. The proposed algorithm is better than the proportional-integral-derivative (PID) algorithm (which is also quasi-universal and practical) due to its robustness, high control performance (especially for processes with time delay) and simple experimental procedure for determining the controller parameters. Some applications are presented to highlight the main features of the algorithm and the tuning procedure for all process types.

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