Linear Parameter-Varying Control of a Floating Piston Electro-Pneumatic Actuator

Szabo, Adam; Bécsi, Tamás; Aradi, Szilárd

doi:10.1109/ines49302.2020.9147127

Cited by 3 publications

(2 citation statements)

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“…Automatized manual transmission (AMT) has been used in heavy-duty vehicles due to its great transmission torque, high transmission efficiency, and low manufacturing and maintenance costs [13,14]. AMT employs the dog clutch as a shifting element, but as it is only a clutch and not a synchronizer, the problems of synchronization shall be studied, and many authors studied the gearshift process in AMT [15][16][17]. Bóka [16] described an external synchronization strategy for a dog clutch in automatized mechanical transmission (AMT) for heavy-duty commercial vehicles.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Modeling of the Dog Clutch Engagement Process Using Hybrid Automata

2023

jjmie

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A detailed system dynamics model is essential for the design and calibration of the system controller. This paper introduces a control-oriented full dynamic model for the dog clutch engagement process that can be integrated with other system dynamic models found in ground vehicle transmission systems, such as the shifting mechanism system. This integrated model can be used later to design a position controller of the shifting mechanism's linkages to achieve a successful gearshift process. The engagement process is divided into four main stages, each of which has distinct dynamic behavior. The dynamics of each discrete stage are analyzed and modeled, and then, the discrete stages are integrated into one model using the hybrid automata modeling technique. Hybrid automata enables us to describe the continuous states within the discrete stages, which is better than continuous time techniques. The possible interactions between the sliding sleeve and the gear are analyzed and based on these interactions, the transition paths' conditions between these stages are established. The hybrid automata model comprises four discrete stages and ten guards that govern the transition between these stages. This model was simulated using Simulink State flow. Three cases are considered to verify the model, and the results showed that it could accurately capture the continuous system dynamics despite four discrete states. Furthermore, the transitions between the discrete states match the possible transition paths and guards.

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Section: Introductionmentioning

confidence: 99%

Dynamic Modeling of the Dog Clutch Engagement Process Using Hybrid Automata

2023

jjmie

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“…The initial design of the LPV-based control for the system is presented in [37]; however, the results are only evaluated on simulation with a simplified model. This paper further develops this design, by using a slightly different generalized model, applying different LPV synthesis, and performing order reduction on the system to be implementable.…”

Section: Introductionmentioning

confidence: 99%

LPV-Based Controller Design of a Floating Piston Pneumatic Actuator

et al. 2020

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The paper presents the modeling and control design of a floating piston pneumatic gearbox actuator using a grid-based Linear Parameter Varying approach. First, the nonlinear model of the pneumatic actuator is presented, then it is transformed into a 6th order Linear Parameter Varying representation with endogenous scheduling parameters. The model is simplified based on empirical considerations to solve the controller synthesis and allow fast controller tuning. The developed Linear Parameter Varying controller is tested in simulations. Moreover, using a balanced truncation-model order reduction method, the minimum order of the controller is determined, which can provide acceptable performance. The simplified controller is implemented in an embedded environment and validated against the real target. Then, the validation results are compared with a gain-scheduled PD controller and a Linear Quadratic Regulator. The results show that by taking the time-varying nature of the scheduling parameters into account, the Linear Parameter Varying controller surpasses the Linear Quadratic Regulator, which cannot handle the high-speed transients around Neutral. Furthermore, the PD controller performs slightly better in two of the four test cases, although the Linear Parameter Varying controller has a higher level of fault tolerance.

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