H∞ Robust LMI-Based Nonlinear State Feedback Controller of Uncertain Nonlinear Systems with External Disturbances

Chatavi, Masoud; Vu, Mai The; Mobayen, Saleh; Fekih, Afef

doi:10.3390/math10193518

Cited by 7 publications

(3 citation statements)

References 58 publications

(90 reference statements)

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“…The system state is realized to attain equilibrium more quickly in a finite amount of time by using robust control techniques, and linear matrix inequality (LMI) determines the control parameters. A state feedback controller is suggested in [19] to maintain system performance and stability in the face of time-varying disturbances and system uncertainty. A method of learning-based control for autonomous cars is presented in this research.…”

Section: Introductionmentioning

confidence: 99%

Path Tracking Control Based on T-S Fuzzy Model for Autonomous Vehicles with Yaw Angle and Heading Angle

He,

Wu,

et al. 2024

Machines

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Existing vehicle-road models used for road tracking do not take into account the side slip angle, which leads to a reduction in road tracking accuracy in scenarios where the vehicle is at a large side slip angle, such as an emergency lane change. Consequently, this study presents a path-tracking control technique based on the T-S fuzzy model of heading angle vehicle autonomy. In this paper, based on the yaw angle-based vehicle tracking model, a heading angle-based tracking model considering the side slip angle is constructed. Second, since the vehicle speed varies with time, this paper selects the membership function of the vehicle speed to establish the T-S fuzzy model of autonomous vehicle based on the yaw angle and heading angle, respectively, and ensures the robustness and stability over the whole parameter space by the linear parameter variation robust H∞ controller. Then, cost functions based on the yaw angle and heading angle augmented error systems are created separately to optimize the system’s overall performance. Ultimately, simulation and experimentation confirm that the algorithm for control, which is based on the fuzzy model of the heading angle vehicle, has superior autonomous trajectory performance.

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Section: Introductionmentioning

confidence: 99%

Path Tracking Control Based on T-S Fuzzy Model for Autonomous Vehicles with Yaw Angle and Heading Angle

He,

Wu,

et al. 2024

Machines

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“…To find a compromise between the conflicting performances of the vehicle suspension system, many approaches have been proposed based on various control techniques, such as sliding mode control [15,16], fuzzy logic and neural network control [1,17], model predictive control [18], adaptive control [15,17], H ∞ control [2,[19][20][21], etc. In particular, the application of robust H ∞ control of the active vehicle suspension system in the context of robustness and damping of road disturbances has been intensively investigated.…”

Section: Introductionmentioning

confidence: 99%

“…In [2], a delay-dependent memory state-feedback H ∞ controller for active quarter-car suspension system with input time-delay in the presence of external disturbance were investigated. In [21], for a class of nonlinear systems under parametric uncertainties and external disturbances, a nonlinear state feedback controller based on linear matrix inequality was presented. Considering all these works, we intend to investigate the active inerterbased suspension system for a quarter-car model by considering all factors, including external disturbance, parametric uncertainty, and input constraint.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Ride Performance of Active Inerter-Based Vehicle Suspension System with Parameter Uncertainties and Input Constraint via Robust H∞ Control

2023

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In this study, we investigate a robust H∞ controller for a quarter-car model of an active inerter-based suspension system under parameter uncertainties and road disturbance. Its main objective is to improve the inherent compromises between ride quality, handling performance, suspension stroke, and energy consumption. Inerters have been extensively used to suppress unwanted vibrations from various kinds of mechanical structures. The advantage of inerter is that the realized ratio of equivalent mass (inertance relative to the mass of the primary structure) is greater than its actual mass ratio, resulting in higher performance for the same effective mass. First, the dynamics and state space of the active inerter-based suspension system were achieved for the quarter-car model with parameter uncertainties. In order to attain the defined objectives, and ensure that the closed-loop system achieves the prescribed disturbance attenuation level, the Lyapunov stability function, and linear matrix inequality (LMI) techniques have been utilized to satisfy the robust H∞ criterion. Furthermore, to limit the gain of the controller, some LMIs have been added. In the case of feasibility, sufficient LMI conditions by solving a convex optimization problem afford the stabilizing gain of the robust state-feedback controller. According to numerical simulations, the active inerter-based suspension system in the presence of parameter uncertainties and external disturbance performs much better than both a passive suspension with inerter and active suspension without inerter.

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Robust State‐Feedback Controller of Uncertain Systems Based on Non‐Monotonic Approach

El Fadili,

Boukili,

N'Diaye

et al. 2024

Adaptive Control & Signal

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In this article, new linear matrix inequality (LMI) conditions are proposed to guarantee robust stability of the closed‐loop of the linear time‐invariant one‐dimensional uncertain system by dealing with both continuous‐time (CT) and discrete‐time (DT) cases. These improved conditions for robust state feedback control combine the non‐monotonic approach and Finsler's technique. The benefit of the non‐monotonic approach returns to the utility of an arbitrary number of quadratic functions by considering the higher order derivatives of the vector field in the CT case (or the higher order differences of the vector field in the DT case). Finsler's technique aims to solve the closed‐loop stability problem in a larger parametric space. The strong points of the suggested LMI conditions are easy to program, eliminate the product between the state matrix and Lyapunov matrices, reduce the constraints by avoiding the decrease monotonically along trajectories for each quadratic Lyapunov function, guarantee the robust stability of the closed‐loop by using a state‐feedback gain. The simulation results show and confirm the effectiveness of these proposed conditions.

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H∞ Robust LMI-Based Nonlinear State Feedback Controller of Uncertain Nonlinear Systems with External Disturbances

Cited by 7 publications

References 58 publications

Path Tracking Control Based on T-S Fuzzy Model for Autonomous Vehicles with Yaw Angle and Heading Angle

Path Tracking Control Based on T-S Fuzzy Model for Autonomous Vehicles with Yaw Angle and Heading Angle

Evaluation of Ride Performance of Active Inerter-Based Vehicle Suspension System with Parameter Uncertainties and Input Constraint via Robust H∞ Control

Robust State‐Feedback Controller of Uncertain Systems Based on Non‐Monotonic Approach

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