Design of a counterbalance forklift based on a predictive anti-tip-over controller

Félez, Jesús; Bermejo, Alvaro

doi:10.3233/ica-180572

Cited by 12 publications

(7 citation statements)

References 22 publications

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“…The variable d s in (12) decides the deceleration distance of AMR while reaching the goal. When the robot is far from the goal (i.e., d > d s ), AMR approaches the target as fast as possible, and begins to slow down while reaching the desired target.…”

Section: Multi-behavior Designmentioning

confidence: 99%

“…Among the many variants of P Systems, Numerical P Systems (NPS) [49] and Enzymatic Numerical P Systems (ENPS) [61] are amongst the most successful due to their high performance in robots' control applications [7,8,41,63,13], especially for modular and complex tasks of autonomous mobile robots (AMR), see also [12,42,65,47,3]. The success of NPS and ENPS in robotics is due to the inherent parallel and distributed nature of these P systems along with their powerful numerical computation power [43].…”

Section: Introductionmentioning

confidence: 99%

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Multi-behaviors coordination controller design with enzymatic numerical P systems for robots

Wang

Zhang

Gou

et al. 2021

ICA

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Membrane computing models are parallel and distributed natural computing models. These models are often referred to as P systems. This paper proposes a novel multi-behaviors co-ordination controller model using enzymatic numerical P systems for autonomous mobile robots navigation in unknown environments. An environment classifier is constructed to identify different environment patterns in the maze-like environment and the multi-behavior co-ordination controller is constructed to coordinate the behaviors of the robots in different environments. Eleven sensory prototypes of local environments are presented to design the environment classifier, which needs to memorize only rough information, for solving the problems of poor obstacle clearance and sensor noise. A switching control strategy and multi-behaviors coordinator are developed without detailed environmental knowledge and heavy computation burden, for avoiding the local minimum traps or oscillation problems and adapt to the unknown environments. Also, a serial behaviors control law is constructed on the basis of Lyapunov stability theory aiming at the specialized environment, for realizing stable navigation and avoiding actuator saturation. Moreover, both environment classifier and multi-behavior coordination controller are amenable to the addition of new environment models or new behaviors due to the modularity of the hierarchical architecture of P systems. The simulation of wheeled mobile robots shows the effectiveness of this approach.

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Section: Multi-behavior Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-behaviors coordination controller design with enzymatic numerical P systems for robots

Wang

Zhang

Gou

et al. 2021

ICA

View full text Add to dashboard Cite

show abstract

“…2 Felez et al analyzed and studied the pitching motion of an automatic guided forklift to analyze the stability conditions of the vehicle and designed an anti-rollover controller based on model predictive control. 3 However, whether it is applicable to the counterbalance forklift remains unknown. Zhang et al 4 used the structural characteristics of the forklift as bases to transform the stable state of gravity center into the stable state of force, which is easy to measure, proposed an anti-rollover early warning scheme, and developed an early warning system integrated with software and hardware to realize the rollover protection scheme.…”

Section: Introductionmentioning

confidence: 99%

Anti-Rollover Control of a Counterbalance Forklift Based on Roll Energy Classification

Xia

Tang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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This study proposes an energy stability index suitable for a counterbalance forklift, aiming to solve the problem that the traditional vehicle stability index load transfer rate is difficult to accurately judge the stability state of such a forklift. The analysis of the structure of the counterbalance forklift and contact relationship between the body and rear axle are used as bases to establish a two-stage dynamic model and derive real-time instability energy of a forklift truck in the rollover process under different conditions. Additionally, this research proposes an anti-rollover control strategy of the counterbalance forklift based on roll energy classification. The corresponding calculation formula of the forklift energy stability index is selected according to different stability conditions to perform roll energy classification. An anti-rollover oil cylinder and active rear wheel steering are used as an anti-rollover control actuator, and an anti-rollover control is implemented based on model predictive control. Last, a simulation based on European standard operating conditions and real vehicle test verification is conducted. Results show that the anti-rollover control strategy based on roll energy classification can effectively reduce the risk of forklift rollover and improve the stability and active safety of a counterbalance forklift.

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“…Ping et al 16 proposed a control strategy of coordinated distribution of driving wheels rotary torque to solving side forklift steering stability problems, based on this control strategy, designed a lateral stability control system, enhance the forklift driving safety. In order to analyse the stability conditions of the forklift, Felez and Bermejo 17 focused on the pitch movement developed an analytical study, based on this analysis, an anti-tip-over control is designed, guaranty the forklift stability without the risk of tip-over. Cheema and Hu 18 analysed the relationship between the principle of lateral stability test and the forklift’s centre of gravity and proposed a method of improving the lateral stability of the forklift.…”

Section: Introductionmentioning

confidence: 99%

Layered control of forklift lateral stability based on Takagi–Sugenofuzzy neural network

Xia

Tang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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An anti-roll hydraulic cylinder is designed as an executive mechanism of the lateral stability control to provide lateral support force on the basis of an analysis of the structure of the forklift and the mechanism of lateral instability. A lateral stability layered control method based on Takagi–Sugeno (T–S) fuzzy neural network is proposed, divides the forklift lateral stability control into the upper identification layer, the middle control layer and the lower executive layer. Simulation and real vehicle test results indicate that the forklift lateral stability control method based on the T–S fuzzy neural network can effectively identify the forklift driving state, reduce the forklift rollover possibility and improve forklift safety under limited working conditions.

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Design of a counterbalance forklift based on a predictive anti-tip-over controller

Cited by 12 publications

References 22 publications

Multi-behaviors coordination controller design with enzymatic numerical P systems for robots

Multi-behaviors coordination controller design with enzymatic numerical P systems for robots

Anti-Rollover Control of a Counterbalance Forklift Based on Roll Energy Classification

Layered control of forklift lateral stability based on Takagi–Sugenofuzzy neural network

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