Tuning Strategies and the Fragility of Fractional-Order PID Controllers

Tuning Strategies and the Fragility of Fractional-Order PID Controllers

This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.

 

Abstract: This paper analyzes the fragility issue of fractional-order proportional-integral-derivative controllers applied to integer first-order plus-dead-time processes. In particular, the effects of the variations of the controller parameters on the achieved control system robustness and performance are investigated. Results show that this kind of controller is more fragile with respect to the standard proportional-integral-derivative controllers and therefore significant attention should be paid by the user in their tuning.

A properly designed control system must provide an effective trade-off between performance and robustness. One of the main reasons to investigate the fragility of fractional-orde PID controllers is to enable an engineer or technician to use alternative strategies for tuning the controller.

 

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2006-2018 Elsevier Science Ltd. All rights reserved.

Low Cost Test Rig for a Standalone Wind Energy Conversion System

Low Cost Test Rig for a Standalone Wind Energy Conversion System

This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.

 

Abstract: In this paper, a contribution to the development of low-cost wind turbine (WT) test rig for stator fault diagnosis of wind turbine generator is proposed. The test rig is developed using a 2.5 kW, 1750 RPM DC motor coupled to a 1.5 kW, 1500 RPM self-excited induction generator interfaced with a WT mathematical model in LabVIEW. The performance of the test rig is benchmarked with already proven wind turbine test rigs. In order to detect the stator faults using non-stationary signals in self-excited induction generator, an online fault diagnostic technique of DWT-based multi-resolution analysis is proposed. It has been experimentally proven that for varying wind conditions wavelet decomposition allows good differentiation between faulty and healthy conditions leading to an effective diagnostic procedure for wind turbine condition monitoring.

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2006-2018 Elsevier Science Ltd. All rights reserved.

Nonlinear Predictive Control of a Boiler-Turbine Unit

Nonlinear Predictive Control of a Boiler-Turbine Unit

This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.

 

Abstract: This paper details development of a model predictive control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearized on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimization problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearization gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimization repeated at each sampling instant.

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2006-2018 Elsevier Science Ltd. All rights reserved.

Tuning the Model Predictive Control of a Crude Distillation Unit

Tuning the Model Predictive Control of a Crude Distillation Unit

This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.

 

Abstract: Tuning the parameters of the model predictive control (MPC) of an industrial crude distillation unit (CDU) is considered here. A realistic scenario is depicted where the inputs of the CDU system have optimizing targets, which are provided by the real-time optimization layer of the control structure. It is considered the nominal case, in which both the CDU model and the MPC model are the same. The process outputs are controlled inside zones instead of at fixed set points. Then, the tuning procedure has to define the weights that penalize the output error with respect to the control zone, the weights that penalize the deviation of the inputs from their targets, as well as the weights that penalize the input moves. A tuning approach based on multi-objective optimization is proposed and applied to the MPC of the CDU system. The performance of the controller tuned with the proposed approach is compared through simulation with the results of an existing approach also based on multi-objective optimization. The simulation results are similar, but the proposed approach has a computational load significantly lower than the existing method. The tuning effort is also much lower than in the conventional practical approaches that are usually based on ad hoc procedures.

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2006-2018 Elsevier Science Ltd. All rights reserved.

Plant-Wide Control Design Based on Steady-State Combined Indexes

Plant-Wide Control Design Based on Steady-State Combined Indexes

This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.

 

Abstract: This work proposes an alternative methodology for designing multi-loop control structures based on steady-state indexes and multi-objective combinatorial optimization problems. Indeed, the simultaneous selection of the controlled variables, manipulated variables, input-output pairing, and controller size and interaction degree is performed by using a combined index which relies on the sum of square deviations and the net load evaluation assessments in conjunction. This unified approach minimizes both the dynamic simulation burden and the heuristic knowledge requirements for deciding about the final optimal control structure. Further, this methodology allows incorporating structural modifications of the optimization problem context (degrees of freedom). The case study selected is the well-known Tennessee Eastman process and a set of simulations are given to compare this approach with early works.

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