Performance Enhancement of Semi-active Continuous Skyhook Control
                    Using Chaotic Map Particle Swarm Optimization-Based Stability Augmentation
                    System

Unnithan, Anand Raj Rajasekharan; Subramaniam, Senthilkumar

doi:10.4271/15-16-01-0002

Cited by 1 publication

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“…The vehicle parameters are selected from our previous work. 46 The road input bounce sine sweep is a synthesised chirp signal used to excite the ride dynamics of the vehicle, as shown in Figure 11.…”

Section: Co-simulation Resultsmentioning

confidence: 99%

Improved particle swarm optimisation tuned PID position control of voice coil semi-active electrohydraulic damper

Rajasekharan Unnithan,

Subramaniam,

Gunasekaran

2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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Control on the variable damping coefficients in the semi-active damper enhances ride comfort and vehicle stability. The semi-active electrohydraulic damper (SEH) presented in this study incorporates voice coil-based robust valve control to modify the damping coefficients. However, the position tracking accuracy of the voice coil actuator (VCA) gets negatively influenced by the nonlinearities such as load variations due to external disturbances, back emf, and dynamic damper characteristics. Therefore, to achieve excellent position control, a restart particle swarm optimisation with the Gompertz function (PSO-RG) is presented to obtain optimal tuning control gain for the proportional integral derivative controller. The PSO-RG algorithm applies Gompertz function-based particle coefficients and restarting technique. These techniques allow the PSO-RG to overcome the limitations of standard PSO, such as premature convergence and particle entrapment in local minima. The algorithm is tested in five selected benchmark functions for 10, 30 and 50 dimensions. The test data conveys that PSO-RG outperforms the standard PSO in mean, standard deviation, the best solution, and convergence speed. The transient response on identified and validated model of VCA demonstrated a 75.21% reduction in integral absolute error value than conventional PSO. The obtained maximum sensitivity and total variation values proved the robustness and smoothness of PSO-RG tuned PID control. Furthermore, the experimental analysis on the quarter car model shows that PSO-RG tuned PID precisely tracked the reference position with a 21.66% decrease in root mean square error to conventional PSO tuned PID. The CarSim co-simulation test results in the large van model indicate the need for precise VCA position control in enhancing ride comfort and improving the roll stability of the vehicle.

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Section: Co-simulation Resultsmentioning

confidence: 99%