L2 gain state derivative feedback control of uncertain vehicle suspension systems

2017 ◽  
Vol 24 (16) ◽  
pp. 3779-3794 ◽  
Author(s):  
Hakan Yazici ◽  
Mert Sever
Keyword(s):  
Ride Comfort ◽  
Controller Design ◽  
Parametric Uncertainty ◽  
Feedback Controller ◽  
Vehicle Suspension ◽  
Space Representation ◽  
Linear Matrix ◽  
Feedback Controllers ◽  
State Space Representation ◽  
Tire Stiffness

This paper is concerned with the design of a robust L2 gain state derivative feedback controller for an active suspension system. An uncertain quarter vehicle model is used to analyze vehicle suspension performance. Parametric uncertainty is assumed to exist in sprung mass, tire stiffness and suspension damping coefficients. Polytopic type state space representation is used to enable robust controller design via a linear matrix inequalities (LMIs) framework. Then nominal and robust L2 gain state derivative feedback controllers having bounded controller gains and robust L2 gain state feedback controllers are tested against ISO2631 random road disturbances with different road grades and vehicle horizontal velocities. Simulation results show that the proposed robust L2 gain state derivative feedback controller is very effective in improving ride comfort without deterioration on road holding ability.

Robust state derivative feedback LMI-based designs for discretized systems.

2020 ◽  
Author(s):  
Marco A. C. Leandro ◽  
Renan L. Pereira ◽  
Karl H. Kienitz
Keyword(s):  
Discrete Time ◽  
Cartesian Product ◽  
Stable Region ◽  
Space Representation ◽  
Linear Matrix ◽  
Feedback Controllers ◽  
Time Model ◽  
State Space Representation ◽  
Augmented System ◽  
Discretized Systems

This work addresses novel Linear Matrix Inequality (LMI)-based conditions for thedesign of discrete-time state derivative feedback controllers. The main contribution of this work consists of an augmented discretized model formulated in terms of the state derivative, such that uncertain sampling periods and parametric uncertainties in polytopic form can be propagated from the original continuous-time state space representation. The resulting discrete-time model is composed of homogeneous polynomial matrices with parameters lying in the Cartesian product of simplexes, plus an additive norm-bounded term representing the residual discretization error. Moreover, the referred condition allows for the closed-loop poles allocation of the augmented system in a D-stable region. Finally, numerical simulations illustrate the effectiveness of the proposed method.

Robust H2 Output Feedback Controller Design for Damping Power System Oscillations

2017 ◽  
Vol 6 (10) ◽  
pp. 8
Author(s):  
Kho Hie Kwee ◽  
Hardiansyah .
Keyword(s):  
Power System ◽  
Output Feedback ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Parameter Uncertainties ◽  
Worst Case ◽  
Output Feedback Controller ◽  
Power System Oscillations

This paper addresses the design problem of robust H2 output feedback controller design for damping power system oscillations. Sufficient conditions for the existence of output feedback controllers with norm-bounded parameter uncertainties are given in terms of linear matrix inequalities (LMIs). Furthermore, a convex optimization problem with LMI constraints is formulated to design the output feedback controller which minimizes an upper bound on the worst-case H2 norm for a range of admissible plant perturbations. The technique is illustrated with applications to the design of stabilizer for a single-machine infinite-bus (SMIB) power system. The LMI based control ensures adequate damping for widely varying system operating.

Active Vehicle Suspension Control Using Full State-Feedback Controller

2015 ◽  
Vol 1115 ◽  
pp. 440-445 ◽  
Author(s):  
Musa Mohammed Bello ◽  
Amir Akramin Shafie ◽  
Raisuddin Khan
Keyword(s):  
State Feedback ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
Feedback Controller ◽  
Vehicle Suspension ◽  
Passive Suspension ◽  
Full State ◽  
Full State Feedback ◽  
Passive Suspension System

The main purpose of vehicle suspension system is to isolate the vehicle main body from any road geometrical irregularity in order to improve the passengers ride comfort and to maintain good handling stability. The present work aim at designing a control system for an active suspension system to be applied in today’s automotive industries. The design implementation involves construction of a state space model for quarter car with two degree of freedom and a development of full state-feedback controller. The performance of the active suspension system was assessed by comparing it response with that of the passive suspension system. Simulation using Matlab/Simulink environment shows that, even at resonant frequency the active suspension system produces a good dynamic response and a better ride comfort when compared to the passive suspension system.

Three-Stage Feedback Controller Design With Applications to a Three Time-Scale System

2016 ◽  
Author(s):  
Verica Radisavljevic-Gajic ◽  
Milos Milanovic
Keyword(s):  
Time Scale ◽  
Controller Design ◽  
Feedback Controller ◽  
Linear Feedback ◽  
Feedback Controllers ◽  
Linear Feedback Controller ◽  
Full State ◽  
Full State Feedback ◽  
A New Technique ◽  
Natural Decomposition

A new technique was presented that facilitates design of independent full-state feedback controllers at the subsystem levels. Different types of local controllers, for example, eigenvalue assignment, robust, optimal (in some sense L1, H2, H∞, ...) may be used to control different subsystems. This feature has not been available for any known linear feedback controller design. In the second part of the paper, we specialize the results obtained to the three time-scale linear systems (singularly perturbed control systems) that have natural decomposition into slow, fast, and very fast subsystems. The proposed technique eliminates numerical ill-condition of the original three-time scale problems.

scholarly journals Output feedback controller design for polynomial linear parameter varying system via parameter-dependent Lyapunov functions

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401769032 ◽  
Author(s):  
Xiaobao Han ◽  
Zhenbao Liu ◽  
Huacong Li ◽  
Xianwei Liu
Keyword(s):  
Output Feedback ◽  
Optimization Problem ◽  
Controller Design ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Output Feedback Controller ◽  
Parameter Varying ◽  
Parameter Dependent

This article presents a new output feedback controller design method for polynomial linear parameter varying model with bounded parameter variation rate. Based on parameter-dependent Lyapunov function, the polynomial linear parameter varying system controller design is formulated into an optimization problem constrained by parameterized linear matrix inequalities. To solve this problem, first, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameter-dependent Lyapunov function, controller, and object coefficient matrices. Then, the control solving problem was reduced to a normal convex optimization problem with linear matrix inequalities constraint on a newly constructed convex polyhedron. Moreover, a parameter scheduling output feedback controller was achieved on the operating condition, which satisfies robust performance and dynamic performances. Finally, the feasibility and validity of the controller analysis and synthesis method are verified by the numerical simulation.

scholarly journals Neural-Network-Based Discrete-Time Fuzzy Control of Continuous-Time Nonlinear Systems with Dither

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Zhi-Ren Tsai ◽  
Jiing-Dong Hwang
Keyword(s):  
Neural Network ◽  
Nonlinear System ◽  
Discrete Time ◽  
Continuous Time ◽  
Fuzzy Controller ◽  
Sampling Frequency ◽  
Space Representation ◽  
Linear Matrix ◽  
State Space Representation ◽  
Ct System

This study presents an effective approach to stabilizing a continuous-time (CT) nonlinear system using dithers and a discrete-time (DT) fuzzy controller. A CT nonlinear system is first discretized to a DT nonlinear system. Then, a Neural-Network (NN) system is established to approximate a DT nonlinear system. Next, a Linear Difference Inclusion state-space representation is established for the dynamics of the NN system. Subsequently, a Takagi-Sugeno DT fuzzy controller is designed to stabilize this NN system. If the DT fuzzy controller cannot stabilize the NN system, a dither, as an auxiliary of the controller, is simultaneously introduced to stabilize the closed-loop CT nonlinear system by using the Simplex optimization and the linear matrix inequality method. This dither can be injected into the original CT nonlinear system by the proposed injecting procedure, and this NN system is established to approximate this dithered system. When the discretized frequency or sampling frequency of the CT system is sufficiently high, the DT system can maintain the dynamic of the CT system. We can design the sampling frequency, so the trajectory of the DT system and the relaxed CT system can be made as close as desired.

Furnace Modelling Using State Space Representation

2006 ◽  
Vol 3 (1) ◽  
pp. 37
Author(s):  
Razidah Ismail
Keyword(s):  
State Space ◽  
Power Plants ◽  
Controller Design ◽  
Cost Savings ◽  
Combined Cycle ◽  
The State ◽  
Space Representation ◽  
State Variables ◽  
State Space Representation ◽  
Space Modeling

The state space modeling approach was developed to cope with the demand and performance due to the increase in system complexity, which may have multiple inputs and multiple outputs (MIMO). This approach is based on time-domain analysis and synthesis using state variables. This paper describes the development of a state space representation of a furnace system of a combined cycle power plant. Power plants will need to operate optimally so as to stay competitive, as even a small improvement in energy efficiency would involve substantial cost savings. Both the quantitative and qualitative analyses of the state space representation of the furnace system are discussed. These include the responses of systems excited by certain inputs and the structural properties of the system. The analysis on the furnace system showed that the system is bounded input and bounded output stable, controllable and observable. In practice, the state space formulation is very important for numerical computation and controller design, and can be extended for time-varying systems.

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