Faculty of Engineering and Built Environment
Permanent URI for this communityhttp://ir-dev.dut.ac.za/handle/10321/9
Browse
2 results
Search Results
Item Model based real time controller performance assessment for non-linear systems(Central University of Technology, 2016-12) Pillay, N.; Govender, P.The aim of this paper is to present a novel methodology for the performance assessment of proportional-integral-derivative (PID) controllers operating in the presence of process nonlinearities. The principle objective is to assess the quality of controller performance in real time when subjected to setpoint changes. Using prescribed operating regions, optimal PID controller settings are synthesized off-line by numerical optimisation from a trained artificial neural network (ANN) of the process. To demonstrate the effectiveness of the proposed controller benchmarking scheme, the procedure is applied to a simulation example, plus a real process control loop operating in a full scale pH neutralization pilot plant. Results obtained from the experiments indicate that the method is suitable for servo tracking in nonlinear control loops such as those found in the pulp and paper, and water purification industries.Item Controller performance assessment of servomechanisms for nonlinear process control systems(WCECS, 2014-10) Pillay, N.; Govender, P.; Maharaj, O.Abstract—This paper aims at assessing the setpoint tracking performance of proportional-integral-derivative (PID) controllers for nonlinear single-input-single-output (SISO) process loops. A comparison is made between the actual system output and an artificial process output response derived from nonlinear system identification and a user defined closed loop transient specification. Nonlinear system identification is achieved by fitting routine operating closed loop data to nonlinear autoregressive with exogenous input (NARX) models to describe a closed loop process model and the servo model. Once the nonlinear models are established they are linearized to corresponding autoregressive with exogenous input (ARX) models where they are incorporated into a controller performance strategy. The framework will allow for control practitioners to assess the current controller setpoint tracking performance for general nonlinear systems from a transient specification point of view. Simulation studies are given to validate the efficacy of the performance assessment procedure and demonstrate that it is an effective tool when setpoint tracking is of general interest.