This paper investigates the spring stiffness control of air suspension systems working under different operating conditions of road profile frequencies and amplitudes. Usually changing the stiffness of the air spring ...
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ISBN:
(纸本)9789897583803
This paper investigates the spring stiffness control of air suspension systems working under different operating conditions of road profile frequencies and amplitudes. Usually changing the stiffness of the air spring involves variations of the enclosed air pressure by pumping air into or out of the air chamber, or by changing its volume. Since, changing spring stiffness through controlling its pressure consumes power and is not instantaneous, controlling the stiffness through finite volume control is merged with a PI-like Fuzzy Logic control (PI-FLC) in this paper. This is achieved by connecting the air spring volume to two additional unequal volumes. By controlling the total spring volumes through ON-OFF switching valves, four different stiffness settings are available, and one can achieve an improved performance of air suspension system. A nonlinear quarter-car model is used to evaluate the proposed approach while a Genetic Algorithm (GA) optimization is applied to estimate the PI-FLC optimal gains and the finite levels for switching the spring volumes. Numerical simulations results demonstrate the performance of the proposed control under different road profile. The vehicle body acceleration decreases by a value that reaches 4 cm/s2 which means improving the passenger ride comfort as well as maintaining the passenger safety. This in turns encourages the implementation of the proposed approach on an actual vehicle air suspension in the near future to further verify the system performance.
The proceedings contain 4 papers. The topics discussed include: community driven artificial intelligence development for robotics;multi-objective optimization for control and process operation;augmented reality interf...
The proceedings contain 4 papers. The topics discussed include: community driven artificial intelligence development for robotics;multi-objective optimization for control and process operation;augmented reality interface design for autonomous driving;and design of robust control strategy for non-linear multivariable systems with delay, parametric uncertainty and external disturbances.
The paper proposes three Gain-Scheduling (GS) control design approaches dedicated to the position control of electromagnetic actuated clutch systems. The initial nonlinear mathematical model of the plant is simplified...
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We study the controllability of the multidimensional wave equation in a bounded domain with Dirichlet boundary condition, in which the support of the control is allowed to change over time. The exact controllability i...
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This paper presents an improved robust adaptive control design for longitudinal dynamics of a large transport aircraft with flexible structure. The proposed adaptive control technique is consist of a baseline Linear Q...
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This paper proposes to address the problem of fixed-structure gain-scheduled LPV/LFT controllers for plants with time-varying measurable and time invariant unmeasurable uncertainties. Due to the complexity of merging ...
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Path planning in a complex dynamic environment is one of the key subsystems in an autonomous vehicle. This paper presents an extension of Model Predictive Path Integral (MPPI) control method which is able to take movi...
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We propose a method in which multiple nozzles are arranged consecutively along a conveying line and an object can be relayed one after another. In this paper, as a most essential technology for such a conveyor, we foc...
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