Abstract
This paper proposes an improved neuroendocrine–proportional–integral–derivative controller for nonlinear multi-input–multi-output crane systems using a sigmoid-based secretion rate of the hormone regulation. The main advantage of the sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative is that the hormone secretion rate of neuroendocrine–proportional–integral–derivative can be varied according to the change of error. As a result, it can provide high accuracy control performance, especially in nonlinear multi-input–multi-output crane systems. In particular, the hormone secretion rate is designed to adapt with the changes of error using a sigmoid function, thus contributing to enhanced control accuracy. The parameters of the sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative controller are tuned using the safe experimentation dynamics algorithm. The performance of the proposed sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative controller-based safe experimentation dynamics algorithm is evaluated by tracking the error and the control input. In addition, the performances of proportional–integral–derivative and neuroendocrine–proportional–integral–derivative controllers are compared with the proposed sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative performance. From the simulation work, it is discovered that the sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative design provides better control performances in terms of the objective function, the total norm of error and the total norm of input compared to proportional–integral–derivative and neuroendocrine–proportional–integral–derivative controllers. In particular, it is shown the proposed sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative controller contributes 5.12% of control accuracy improvement by changing the fixed hormone secretion rate into a variable hormone secretion rate based on the change of error.
Highlights
Nowadays, nonlinear multi-input–multi-output (MIMO) crane systems are widely used in the container logistics industry for loading and unloading containers from and to container ships in the harbour
Model-based control methods potentially suffer from problems of un-modelled dynamics, which lead to model inaccuracy and poor control performance
Underpinning this novel technique, the contribution of this work is to verify that the SbSR–NEPID provides better control performance accuracy than the standard NEPID and the standard PID controller by modifying the fixed secretion rate into variable secretion rate based on a sigmoid function
Summary
Nonlinear multi-input–multi-output (MIMO) crane systems are widely used in the container logistics industry for loading and unloading containers from and to container ships in the harbour. Designing the variable hormone secretion rate of neuroendocrine–PID control could offer a great potential in improving the control accuracy of the standard NEPID controller in controlling nonlinear MIMO crane systems. This paper presents a sigmoid-based secretion rate neuroendocrine–PID (SbSR–NEPID) control mechanism for controlling nonlinear MIMO crane systems. The performance of the proposed control approach is validated through application to a nonlinear MIMO crane system in terms of tracking error and control input energy. Underpinning this novel technique, the contribution of this work is to verify that the SbSR–NEPID provides better control performance accuracy than the standard NEPID and the standard PID controller by modifying the fixed secretion rate into variable secretion rate based on a sigmoid function.
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