Actuator fault reconstruction based on a robust adaptive observer

This paper presents a sliding mode observer-based fault tolerant controller for a class of active suspension with the parametric uncertainties and sensor faults. First, T-S fuzzy approach is employed to represent the inertial parameters uncertainties and sensor faults, and then an augmented vehicle dynamics model is established. To estimate both system state variables and sensor fault signal simultaneously, a sliding-mode observer is investigated, and the fault tolerant control law is further derived in terms of the estimation of state and state error within Lyapunov theory framework, moreover, the sufficient conditions for the existence of this controller is deduced and solved via a set of linear matrix inequalities. Finally, a complete comparative simulation case is provided to demonstrate the effectiveness and feasibility of the designed control method. INDEX TERMS active suspension system, sliding mode observer, fault tolerant control, T-S fuzzy approach. Nomenclature mc Vehicle body mass [kg] ϕ Pitch angle of vehicle body [rad] Iy Moment of inertia in vehicle body [kg• m² ] cf Damping coefficient of front suspension [N•s•m-1 ] muf Mass of the front suspension wheel [kg] cr Damping coefficient of rear suspension [N•s•m-1 ] mur Mass of the rear suspension wheel [kg] ktf Stiffness of the front tire [N•m-1 ] a Distance from COG to the front axle [m] ktr Stiffness of the rear tire [N•m-1 ] b Distance from COG to the rear axle [m] uf Front actuator force [F] zuf Vertical displacement of the front wheel [m] ur Rear actuator force [F] zur Vertical displacement of the rear wheel [m] ∆yf Front suspension dynamic travel [m] zrf Road excitations at the front wheel [m] ∆yr Rear suspension dynamic travel [m] zrr Road excitations at the rear wheel [m] kf Stiffness coefficient of the front suspension [N•m-1 ] zc Vertical displacement of vehicle body [m] kr Stiffness coefficient of the rear suspension [N•m-1 ]

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“…Besides, the four assumptions are given as [30][31]: The sensor fault fs is satisfied with 0 < fs < 1, where fs > 0 is unknown.…”

Section: C I D E = Ementioning

confidence: 99%

Design of a Sliding Mode Observer-Based Fault Tolerant Controller for Automobile Active Suspensions With Parameter Uncertainties and Sensor Faults

2020

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“…Most of the real systems contain uncertainty including unknown inputs and modelling errors. Although there are a lot of references in the robust FDI of deterministic systems [1][2][3], few research works can be found in robust FDI of stochastic systems with unknown inputs [4]. The generation of the residual signal is one of the most common robust FDI methods in stochastic systems.…”

Section: Introductionmentioning

confidence: 99%

“…27)Proof: The first and second LMIs in (27) are directly obtained from conditions of unknown input effect rejection in system(1). Equality constraints are approximately converged to their values in convex optimisation.…”

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confidence: 99%

LMI‐based robust fault detection and isolation in linear stochastic systems

Jafari

Poshtan

Shamaghdari

2020

IET Science, Measurement & Technology

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“…Literature [17,18] also designed a class of mixed H 2 /H ∞ controllers for ASS, but the model uncertainty issue is not considered. In literature [19], the authors have developed a full-state feedback controller with considering the input delay for a seat suspension system, and this controller achieved better control effects in a certain delay range. These studies inspired our study along this direction.…”

Section: Introductionmentioning

confidence: 99%

“…Synthesizing the above discussions, this paper presents a robust generalized H 2 /H ∞ full state feedback controller for the ASS. Compared with the related studies in [12][13][14][15][16][17][18][19][20][21], the key contribution points lie in the two aspects:…”

Section: Introductionmentioning

confidence: 99%

Robust Mixed H2/H∞ State Feedback Controller Development for Uncertain Automobile Suspensions with Input Delay

2020

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In order to achieve better dynamics performances of a class of automobile active suspensions with the model uncertainties and input delays, this paper proposes a generalized robust linear H2/H∞ state feedback control approach. First, the mathematical model of a half-automobile active suspension is established. In this model, the H∞ norm of body acceleration is determined as the performance index of the designed controller, and the hard constraints of suspension dynamic deflection, tire dynamic load and actuator saturation are selected as the generalized H2 performance output index of the designed controller to satisfy the suspension safety requirements. Second, a generalized H2/H∞ guaranteed cost state-feedback controller is developed in terms of Lyapunov stability theory. In addition, the Cone Complementarity Linearization (CCL) algorithm is employed to convert the generalized H2/H∞ output-feedback control problem into a finite convex optimization problem (COP) in a linear matrix inequality framework. Finally, a numerical simulation case of this half-automobile active suspension is presented to illustrate the effectiveness of the proposed controller in frequency-domain and time-domain.

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Actuator fault reconstruction based on a robust adaptive observer

Cited by 20 publications

References 30 publications

Design of a Sliding Mode Observer-Based Fault Tolerant Controller for Automobile Active Suspensions With Parameter Uncertainties and Sensor Faults

Design of a Sliding Mode Observer-Based Fault Tolerant Controller for Automobile Active Suspensions With Parameter Uncertainties and Sensor Faults

LMI‐based robust fault detection and isolation in linear stochastic systems

Robust Mixed H2/H∞ State Feedback Controller Development for Uncertain Automobile Suspensions with Input Delay

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