Road Adaptive Suspension Controller Based on Partial-State Feedback Gain Scheduling

A new control algorithm combing Reduced-order observer, LQG and Fuzzy Logic Controller (RLFLC) is proposed to compromise the classical suspension conflict between riding comfort and driving safety. The RLFLC optimizes the weights of the performance indexes on line in accordance with variational suspension deflection and body acceleration to schedule the gain of LQG controller dynamically for achieving multiple control objectives. In particular, a reduced-order observer is introduced to estimate some state variables which are difficult to measure. Compared with the passive suspension and the conventional LQG control system, the simulation results show that RLFLC can be adaptive to vehicle speed and road conditions to improve not only the riding comfort at low speeds, but also driving safety at high speeds without violating the given suspension deflection limit

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Design of reduced-order observer-based variable structure power system stabiliser for unmeasurable state variables

IEE Proceedings - Generation Transmission and Distribution ◽

10.1049/ip-gtd:19982180 ◽

1998 ◽

Vol 145 (5) ◽

pp. 525 ◽

Cited By ~ 17

Author(s):

S.S. Lee ◽

J.K. Park

Keyword(s):

Power System ◽

Variable Structure ◽

State Variables ◽

Reduced Order ◽

Reduced Order Observer

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Loss of Optimal Performance of the Finite-Horizon Continuous-Time Linear-Quadratic Controller Driven by a Reduced-Order Observer

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4038654 ◽

2017 ◽

Vol 140 (6) ◽

Cited By ~ 2

Author(s):

Verica Radisavljevic-Gajic ◽

Milos Milanovic

Keyword(s):

Continuous Time ◽

Initial Conditions ◽

Proton Exchange ◽

Optimal Performance ◽

Finite Horizon ◽

Least Square ◽

State Variables ◽

Linear Quadratic ◽

Reduced Order ◽

Reduced Order Observer

In this paper, we derive an expression for the loss of optimal performance (compared to the corresponding linear-quadratic optimal performance with the instantaneous full-state feedback) when the continuous-time finite-horizon linear-quadratic optimal controller uses the estimates of the state variables obtained via a reduced-order observer. It was shown that the loss of optimal performance value can be found by solving the differential Lyapunov equation whose dimensions are equal to dimensions of the reduced-order observer. A proton exchange membrane fuel cell example is included to demonstrate the loss of optimal performance as a function of the final time. It can be seen from the simulation results that the loss of optimal performance value can be very large. The loss of optimal performance value can be drastically reduced by using the proposed least-square formulas for the choice of the reduced-order observer initial conditions.

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Leader-Following Consensus Stability of Discrete-Time Linear Multiagent Systems with Observer-Based Protocols

Abstract and Applied Analysis ◽

10.1155/2013/357971 ◽

2013 ◽

Vol 2013 ◽

pp. 1-10 ◽

Cited By ~ 4

Author(s):

Bingbing Xu ◽

Lixin Gao ◽

Yan Zhang ◽

Xiaole Xu

Keyword(s):

Multiagent Systems ◽

Discrete Time ◽

Matrix Theory ◽

Algebraic Riccati Equation ◽

State Variables ◽

Reduced Order ◽

Communication Topology ◽

Reduced Order Observer ◽

Leader Following ◽

Time Linear

We consider the leader-following consensus problem of discrete-time multiagent systems on a directed communication topology. Two types of distributed observer-based consensus protocols are considered to solve such a problem. The observers involved in the proposed protocols include full-order observer and reduced-order observer, which are used to reconstruct the state variables. Two algorithms are provided to construct the consensus protocols, which are based on the modified discrete-time algebraic Riccati equation and Sylvester equation. In light of graph and matrix theory, some consensus conditions are established. Finally, a numerical example is provided to illustrate the obtained result.

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Nonlinear Reduced-Order Observer-Based Predictive Control for Diving of an Autonomous Underwater Vehicle

Discrete Dynamics in Nature and Society ◽

10.1155/2017/4394571 ◽

2017 ◽

Vol 2017 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Xuliang Yao ◽

Guangyi Yang ◽

Yu Peng

Keyword(s):

Predictive Control ◽

Attitude Control ◽

Autonomous Underwater Vehicle ◽

Underwater Vehicle ◽

Accurate Estimation ◽

State Variables ◽

Time Model ◽

Near Surface ◽

Reduced Order ◽

Reduced Order Observer

The attitude control and depth tracking issue of autonomous underwater vehicle (AUV) are addressed in this paper. By introducing a nonsingular coordinate transformation, a novel nonlinear reduced-order observer (NROO) is presented to achieve an accurate estimation of AUV’s state variables. A discrete-time model predictive control with nonlinear model online linearization (MPC-NMOL) is applied to enhance the attitude control and depth tracking performance of AUV considering the wave disturbance near surface. In AUV longitudinal control simulation, the comparisons have been presented between NROO and full-order observer (FOO) and also between MPC-NMOL and traditional NMPC. Simulation results show the effectiveness of the proposed method.

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