scholarly journals Nonlinear Ride Height Control of Active Air Suspension System with Output Constraints and Time-Varying Disturbances

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1539
Author(s):  
Rongchen Zhao ◽  
Wei Xie ◽  
Jin Zhao ◽  
Pak Kin Wong ◽  
Carlos Silvestre
Keyword(s):  
Small Neighborhood ◽  
Nonlinear Observer ◽  
Time Varying ◽  
Ride Height ◽  
Performance Simulation ◽  
Output State ◽  
Air Suspension ◽  
Output Constraints ◽  
Uniform Ultimate Boundedness ◽  
Road Excitation

This paper addresses the problem of nonlinear height tracking control of an automobile active air suspension with the output state constraints and time-varying disturbances. The proposed control strategy guarantees that the ride height stays within a predefined range, and converges closely to an arbitrarily small neighborhood of the desired height, ensuring uniform ultimate boundedness. The designed nonlinear observer is able to compensate for the time-varying disturbances caused by external random road excitation and perturbations, achieving robust performance. Simulation results obtained from the co-simulation (AMESim-Matlab/Simulink) are given and analyzed, demonstrating the efficiency of the proposed control methodology.

scholarly journals Disturbance Observer-Based Adaptive Neural Network Control of Marine Vessel Systems with Time-Varying Output Constraints

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Wei Zhao ◽  
Li Tang ◽  
Yan-Jun Liu
Keyword(s):  
Neural Network ◽  
Disturbance Observer ◽  
Continuous Functions ◽  
Network Control ◽  
Time Varying ◽  
Adaptive Neural Network ◽  
External Disturbances ◽  
Adaptive Neural Network Control ◽  
Output Constraints ◽  
Novel Strategy

This article investigates an adaptive neural network (NN) control algorithm for marine surface vessels with time-varying output constraints and unknown external disturbances. The nonlinear state-dependent transformation (NSDT) is introduced to eliminate the feasibility conditions of virtual controller. Moreover, the barrier Lyapunov function (BLF) is used to achieve time-varying output constraints. As an important approximation tool, the NN is employed to approximate uncertain and continuous functions. Subsequently, the disturbance observer is structured to observe time-varying constraints and unknown external disturbances. The novel strategy can guarantee that all signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB). Finally, the simulation results verify the benefit of the proposed method.

scholarly journals Adaptive output feedback control for a class of uncertain non-strict feedback systems with asymmetric time-varying output constraints

2020 ◽  
Vol 12 (9) ◽  
pp. 168781402095882
Author(s):  
Min Wan ◽  
Shanshan Huang
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Tracking Error ◽  
Output Feedback Control ◽  
Time Varying ◽  
Dynamic Surface ◽  
Adaptive Output Feedback Control ◽  
Output Constraints ◽  
Fuzzy State ◽  
Strict Feedback

This study investigated a novel adaptive output feedback control scheme for non-strict feedback nonlinear systems with uncertainties, disturbances, and asymmetric time-varying output constraints. Because that the states of the system are unmeasurable, we used an adaptive fuzzy state observer to obtain the estimated values of the states. To make the output and tracking error satisfy their asymmetric time-varying constraints, an asymmetric time-varying barrier Lyapunov function was adopted. To overcome the “explosion of complexity” problem, we also adopted the dynamic surface control technology. The stability of the closed-loop system was proved by the Lyapunov method, and we give two simulation examples to show the effectiveness of the proposed control method.

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