Intelligent modified internal model control for speed control of nonlinear uncertain heavy duty vehicles

A simple active carbody roll scheme for hydraulically actuated railway vehicles using internal model control

The paper presents the first classical internal model control (IMC) design in the context of railway carbody roll control. We propose a simple control approach for a recent hydraulically actuated vehicle body roll concept that offers limited carbody roll. The IMC approach addresses both preview- and nulling-type tilt setups, highlighting related benefits and limitations. The design provides a model simplification process that facilitates PI and PID-type control structures without the need for complex optimization. A simple, yet practical, tool for the industrial rail rolling stock engineer in vehicle control design is offered. Vehicle roll performance is rigorously studied on the deterministic (curving acceleration response) and stochastic (ride quality) trade off. Simulations are performed on an in-house multibody dynamics software package employing a realistic nonlinear railway vehicle model and allow to appropriately assess the performance of preview and nulling type tilt performance. The results obtained confirm that preview tilt control offers the better tilt performance as it utilizes a tilt command reference, and highlighted that nulling-type tilt performance remains at a relatively comparable level with the former.

A novel grey decision-DE optimized internal model controller for vibration control of nonlinear uncertain aeroelastic blade system

In this paper, a novel grey decision-differential evolution (GD-DE) optimized internal model controller is proposed for the control of nonlinear aeroelastic blade system (ABS) under time-varying uncertainties and control saturations. Two-port internal model control structure is presented for saturation compensation. The filter parameter of the controller is optimally tuned by proposed GD-DE algorithm, which is designed based on the grey decision incidence theory and differential evolution algorithm. The superiority of GD-DE optimized tuning technique is verified, compared to conventional IMC tuning method and other evolutionary algorithm based techniques. The robustness is analysed by comprehensive simulations from time-invariant uncertainties to large periodic or random time-varying uncertainties. The realistic condition with input/output disturbances is also involved. Simulation results show that the proposed controller outperforms existing adaptive IMC controller and other advanced controllers with greatly improved dynamic performance, stronger robustness and better saturation compensation on various conditions.

Modified fractional order IMC design based drug scheduling for cancer treatment

This paper aims to improve chemotherapy drug(s) scheduling of the drug dose injected into a patient. The existing practice has been established on experiments performed during the drug development process. In general, chemotherapeutic drugs are highly toxic in nature and directly affect the probability of a patient's survival. Therefore, a modified fractional order internal model control (MFOIMC) scheme with a minimal number of design parameters is proposed for effective drug scheduling. The proposed control scheme is a combination of fractional calculus and IMC. The fractional order IMC (FOIMC) is modified by incorporating an extra control loop with a proportional transfer function. Further, IPD and IMC control techniques are also designed for comparative analysis. The dragon fly algorithm (DA) is employed to optimize the parameters of the controller. Results show that the proposed control scheme provides a continuous and precise chemotherapeutic drug dose to the patient on a daily basis. It is also shown that MFOIMC improves IAE by 34% and 32% in comparison to IMC and FOIMC, respectively, which proves its superiority over other controllers.