Thiago V. Costa

Experimental assessment and design of multiple model predictive control based on local model networks for industrial processes

This paper presents the experimental assessment of a class of multiple model predictive controllers based on linear local model networks. The control design is established on a clear and easily understandable structure where local models are used to describe the nonlinear process in several different operating points. Thus, simplifying the model predictive control (MPC) algorithm by eliminating the need of a nonlinear optimization strategy, reducing it to a well-grounded quadratic programming dynamic optimization problem. The investigated methodology was tested in an experimental neutralization pilot plant instrumented with foundation fieldbus devices. The steps of models selection, experimental system identification and proper model validation were addressed. In addition, an open-source system used for control calculation was presented. Results regarding the control problem showed that the MPC based on local relevant models was capable of smooth setpoint tracking despite system nonlinearities and a reduced demand of the final control element was attained. It was shown that the technique is easily implementable and can be used to achieve improvements in the control of nonlinear processes at the cost of little modification to the linear MPC algorithm.

CONTROL RECONFIGURATION OF CHEMICAL PROCESSES SUBJECTED TO ACTUATOR FAULTS: A MOVING HORIZON APPROACH

The use of Fault Tolerant Control (FTC) strategies provides alternatives for control loops in presence of faults by exploring physical and analytical redundancies available in the process. Therefore, the use of FTC techniques is essential to adequate industrial control systems concerning availability and reliability while preserving the closed-loop system performance. In this paper, we propose the extension of the fault-hiding approach for the control reconfiguration to a dynamic optimization problem in order to incorporate system constraints. This method uses the concepts of the virtual actuator and a moving horizon framework extending the original control reconfiguration problem to a quadratic programming problem. A multivariable neutralization process subjected to communication loss between the master controller and the final control elements is used as an example to analyze and demonstrate the performance of the proposed approach.

Exergetic optimization of a refrigeration cycle for natural gas liquefaction

Abstract Natural gas is widely use in many industries as fuel and also as raw material. Although gas pipelines present less transportation losses they become impracticable when distances are too long or when demands are highly variable. The liquefaction of natural gas is then necessary to allow its transportation in great volumes, with little loss of material. This also enables its storage in a more stable way. Natural gas consumption is continuously growing worldwide and consequently, the number of exporter terminals (liquefaction industries) and importer terminals (regasification plants) will increase. The natural gas liquefaction process is based on a sequence of refrigeration cycles, which need to work in an optimized way. The exergetic analysis is a very useful thermodynamic tool to evaluate the efficiency of these cycles. This work aims at an exergetic analysis of a multistage cascade refrigeration cycle applied to a natural gas liquefaction process. Firstly, the process was simulated using commercial software and the results obtained from the simulations were validated with literature data, showing a good agreement. After that, different operational conditions, according to a complete factorial design of experiments, were studied, in order to verify the influence of pressure in six specific points of the cycle. The response variable analyzed is the rate of total exergy destroyed in the cycle. The results showed a new set of operational condition to the refrigeration cycle in which the destroyed exergy rate was reduced by approximately 48% in comparison with literature data.

Scilab/Scicos: An Alternative Tool for Real-Time Monitoring and Advanced Control of Fieldbus Industrial Systems

Abstract The present work deals with real-time data acquisition and advanced control evaluation utilizing the open source scientific platform Scilab. Implementation and visualization of online data with the Scicos toolbox and utilization of OPC technology were discussed. The feasibility and effectiveness of the proposed methodology was shown by means of application of fuzzy controllers to a bromelain enzyme precipitation process instrumented with Foundation Fieldbus devices. Results confirmed Scilab/Scicos suitable for HMI and control systems applied in small industrial applications.

Reconfigurable stabilizing control applied to a neutralization process

Abstract This paper presents the application of reconfigurable control strategy to a multivariable neutralization process under several fault scenarios. The combined control strategy is integrated to a reconfiguration block that uses the available signals from the remaining sensors and actuators to reconstruct a signal useful to the nominal controller leading to a stable closed-loop behavior even in the presence of faults. Simulations results show that, although the overall system performance can be compromised, the reconfigurable control strategy leads to a system that is still able to operate within acceptable performance in the studied fault scenarios.

Fuzzy Model Predictive Control Applied to Piecewise Linear Systems

This paper presents the application of a combined control strategy applied to nonlinear systems and grounded in a MPC structure using a fuzzy model description. The nonlinear models were treated as several sub-models with linear behavior, called Piecewise Linear systems (PWL). The advantages of this methodology were visualized in the temperature control of a continuous tank reactor with output multiplicity behavior. Comparisons with classical control approaches showed that the PWL MPC is an attractive and practical strategy.