This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

This paper reviews available tuning guidelines for model-predictive control (MPC) from theoretical and practical perspectives. Its primary focus is on the guidelines introduced since the publication of our previous review of MPC tuning guidelines in this same journal in 2010. Since then, new guidelines based on approaches such as pole placement and multiobjective optimization have been proposed, and more autotuning methods have been introduced. This review covers different implementations of MPC such as dynamic matrix control, generalized predictive control, and state-space-model predictive control that requires Kalman filter tuning. The closed-loop performances of a distillation column and the Shell fractionator under model-predictive controllers tuned using four different tuning guidelines are compared through numerical simulations.

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Tuning Guidelines for Model-Predictive Control

Control-oriented modelling and investigation on quick load change control of subcritical circulating fluidized bed unit

For the efficient control of industrial heat sources, adaptation to significant changes in operating conditions and in heat demand variations are the critical issues. This article presents the concept of the adaptive dynamic matrix controller dedicated to control of heat sources operated as a part of heat distribution systems. The adaptation is based on interpolation of the process nonlinearities. The implementation in programmable logic controller in the form of a general purpose function block is presented and practical issues of the minimization of the memory load and computational complexity are addressed. The suggested concept is experimentally validated by both virtual and real commissioning in the industrial conditions. The aspect of energy efficiency of the heat source control systems is also discussed and for assessment of the energy supply performance, the energy error index is proposed. In terms of this index, the results show superiority of the suggested controller over the conventional approaches.

Practical PLC-Based Implementation of Adaptive Dynamic Matrix Controller for Energy-Efficient Control of Heat Sources

Economic justification of Virtual Commissioning in automation industry

In Dynamic Matrix Control (DMC) algorithm, the control signal is computed optimally based on the process model. In effect, the DMC algorithm allows for obtaining a better quality of control than conventional controllers, especially for plants with large time delays. However, in spite of these advantages, there are still some difficulties that can appear in the implementation of DMC in local control loops. This is due to limitations of the computational resources in industrial devices (e.g., Programmable Logic Controllers). To overcome these difficulties, we propose a tuning strategy for the DMC algorithm with reduced horizons. It is shown that a reduction in the length of prediction and dynamic horizons can reduce the required memory in industrial controllers without degrading the quality of control.

Tuning strategy for dynamic matrix control with reduced horizons

In this article, increment count method (ICM) is proposed as a novel approach for simultaneous steady-state detection and transportation time delay estimation for industrial processes. The concept of ICM is presented, and its implementation issues are discussed. Especially, the simplicity and very low computational complexity of ICM are addressed, which support its practical implementation. Then, as a practical example, ICM is used as a part of the autotuning algorithm dedicated for reduced-order active disturbance rejection controller with Smith predictor (RADRC+SP). Jointly with dedicated optimization algorithm, it allows for identification between the first or second order of process dynamics. The results of this identification allow for effective tuning of RADRC+SP based on the novel tuning rules. The practical aspect includes programmable logic controllers (PLC) based implementation of both autotuning and RADRC+SP controller in the form of the general-purpose function blocks. The experimental validation shows the practical applicability and superiority of the proposed methods.

Increment Count Method and Its PLC-Based Implementation for Autotuning of Reduced-Order ADRC With Smith Predictor

In this paper, the possibility of using the virtual commissioning for developing the advanced controllers for example of electric flow heater is presented. First, based on the process measurement data, the virtual environment is prepared. Then, for selected advanced control algorithms, both virtual and real commissioning was carried out. The results are discussed in the paper and they demonstrate the impact of the applied commissioning method on the control performance provided by each of considered control algorithms.

Practical Verification of the Advanced Control Algorithms Based on the Virtual Commissioning Methodology - A Case Study

In this paper, the comparison between conventional and data-driven control performance assessment (CPA) indices in application to the heating process is presented. Based on the realistic simulation results for differently tuned single-loop PI/PID based control systems, the chosen CPA measures are computed and compared in terms of ability to load disturbance rejection. Then, the correlation between conventional CPA indices (maximum overshoot, settling time and integral indices) and data-driven methods (minimum variance (MV) and general minimum variance (GMV) indices) is presented. The results show that in some cases, data-driven CPA methods can be replaced by less complex conventional CPA indices.

Patryk Grelewicz

Papers

Tuning strategy for dynamic matrix control with reduced horizons

Practical PLC-Based Implementation of Adaptive Dynamic Matrix Controller for Energy-Efficient Control of Heat Sources

Increment Count Method and Its PLC-Based Implementation for Autotuning of Reduced-Order ADRC With Smith Predictor

Practical Verification of the Advanced Control Algorithms Based on the Virtual Commissioning Methodology - A Case Study

Corelation between Conventional and Data-Driven Control Performance Assessment Indices for Heating Process