Adaptive Neural Network Control for Active Suspension Systems With Time-Varying Vertical Displacement and Speed Constraints

Zeng, Qiang; Tong, Shaocheng; Chen, C. L. Philip; Liu, Lei

doi:10.1109/tie.2019.2893847

Cited by 228 publications

(108 citation statements)

References 55 publications

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“…In addition to the above constant constraints, time-varying constraints are frequently studied in [32], and the main research results are more in line with the requirements of the actual system. For example, the authors in [33,34] applied time-varying constraint control to robot and vehicle active suspension systems, respectively. They combined their approach with NNs to deal with unknown terms, and finally realized the safety control of the actual system.…”

Section: Introductionmentioning

confidence: 99%

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Integral Barrier Lyapunov function-based adaptive control for switched nonlinear systems

Liu

Chen

Tong

et al. 2020

Sci. China Inf. Sci.

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360

147

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This paper presents an adaptive control method for a class of uncertain strict-feedback switched nonlinear systems. First, we consider the constraint characteristics in the switched nonlinear systems to ensure that all states in switched systems do not violate the constraint ranges. Second, we design the controller based on the backstepping technique, while integral Barrier Lyapunov functions (iBLFs) are adopted to solve the full state constraint problems in each step in order to realize the direct constraints on state variables. Furthermore, we introduce the Lyapunov stability theory to demonstrate that the adaptive controller achieves the desired control goals. Finally, we perform a numerical simulation, which further verifies the significance and feasibility of the presented control scheme.

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Section: Introductionmentioning

confidence: 99%

“…though the constraint problems are addressed in lots of existing studies [18,22,28,30,34], only the single mode is investigated in those studies. Although this paper concentrates on the switched systems (multiple mode) for constraint problems, we introduce the iBLFs to constrain all state variables in the switched systems.…”

Section: Introductionmentioning

confidence: 99%

Integral Barrier Lyapunov function-based adaptive control for switched nonlinear systems

Liu

Chen

Tong

et al. 2020

Sci. China Inf. Sci.

Self Cite

360

147

View full text Add to dashboard Cite

show abstract

“…It should be noticed that in practical applications, system states and input and output signals are ubiquitously suffer from amplitude constraints for security reasons or performance requirements. To address the constraint problem, some approaches have been proposed, such as model predictive control (MPC), reference governor (RG), and barrier Lyapunov functions (BLFs) . However, by solving online optimization to guarantee constraints, MPC and RG bring the difficulty of the computational complexity.…”

Section: Introductionmentioning

confidence: 99%

“…To address the constraint problem, some approaches have been proposed, such as model predictive control (MPC), reference governor (RG), and barrier Lyapunov functions (BLFs). [33][34][35] However, by solving online optimization to guarantee constraints, MPC and RG bring the difficulty of the computational complexity. Therefore, BLF-based methods are widely used to avoid this issue for constrained systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive consensus control for stochastic nonlinear multiagent systems with full state constraints

Xiao

Cao

Dong

et al. 2019

Intl J Robust & Nonlinear

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Summary In this paper, the consensus tracking problem is investigated for stochastic nonlinear multiagent systems with full state constraints and time delays. The barrier Lyapunov functions proposed for single‐agent constrained systems are constructively extended to solve the consensus problem for multiagent systems with the full state constraints. Some Lyapunov‐Krasovskii functionals are introduced to compensate for state time delays, which are inherent in the complicated nonlinear systems. Based on the variable separation technique, the difficulty arising from the nonstrict‐feedback structure is overcome. Under a directed communication topology, the distributed neuroadaptive control protocols are proposed to guarantee that all the follower agents follow the trajectory of the leader agent and the full state constraints are not violated. The effectiveness of the proposed distributed adaptive control approach is verified via simulation examples.

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“…Fuzzy logic control strategy has been considered as one of the powerful tools for achieving the control goal of ACC system because it does not rely on an accurate mathematical model, and it represents the human reasoning method in a very effective way and it is suitable for dealing with nonlinear and uncertainty control system. [17][18][19][20] Yu et al have put forward an error compensation mechanism to eliminate the filtering error for uncertain nonlinear system by designed command filtering based on adaptive fuzzy approach. 21,22 Wang et al have put forward an adaptive fuzzy control scheme to overcome the problem on the unknown direction hysteresis for a pure-feedback nonlinear system adopting the backstepping technique.…”

Section: Introductionmentioning

confidence: 99%

A synergetic strategy of automobile intelligent cruise system based on fuzzy control adopting hierarchical structure

Chen

Zhou

Zhang

et al. 2019

International Journal of Advanced Robotic Systems

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To improve automobile travel safety and relieve the intension of driving fatigue, a synergetic strategy on the throttle and brake combined control of automobile cruise system is proposed based on fuzzy control theory. A hierarchical control structure, including the upper fuzzy controller and the lower model match controller, is designed for integrated control function. The upper controller consists of the two input variables, that is, the deviation of the theoretical safe distance and the relative distance and the relative velocity between the host car and the preceding vehicle, and the single output variable, that is, the excepted acceleration of host car. The lower controller has achieved the fast compensation of excepted acceleration by adopting parallel feedforward and feedback compensator to input into the inverse dynamics model of automobile cruise system. Using MATLAB/Simulink, the control function on the proposed synergetic strategy is validated for different working cases. The results show that the synergetic strategy possesses an integrated capability involved automated stop & go control, and following the preceding car to prevent rear-end collision, and the constant velocity cruise whether the driving conditions of the city road or expressway.

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Adaptive Neural Network Control for Active Suspension Systems With Time-Varying Vertical Displacement and Speed Constraints

Cited by 228 publications

References 55 publications

Integral Barrier Lyapunov function-based adaptive control for switched nonlinear systems

Integral Barrier Lyapunov function-based adaptive control for switched nonlinear systems

Adaptive consensus control for stochastic nonlinear multiagent systems with full state constraints

A synergetic strategy of automobile intelligent cruise system based on fuzzy control adopting hierarchical structure

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