Path Following of a Ship Sailing in Restricted Waters Based on an Extended Updated-Gain High-Gain Observer

2018 ◽  
Author(s):  
Jianqin Wang ◽  
Zaojian Zou ◽  
Tao Wang
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
Control Method ◽  
Output Feedback Control ◽  
Path Following ◽  
High Gain ◽  
The State ◽  
State Feedback Control ◽  
Control Law ◽  
High Gain Observer

The paper studies the path following of a ship sailing in restricted waters based on an output feedback control, which consists of a state feedback control law and an extended updated-gain high-gain observer. According to the separation principle, the state feedback control and the extended updated-gain high-gain observer are designed separately. The state feedback control law is designed based on a robust guaranteed cost control method assuming that system states are measurable. Sufficient conditions are given for the control based on a linear uncertain system. The extended updated-gain high-gain observer, whose gains are updated according to the nonlinear functions of available evaluation errors, is used to reconstruct system states. Then the output feedback control is obtained by replacing states value in the state feedback control law with its estimation yielded by the state observer. Numerical simulations confirm the effectiveness of the proposed control method for the path following of a ship sailing in restricted waters.

scholarly journals Robust H∞ stabilisation with definite attenuance of an uncertain impulsive switche system

2005 ◽  
Vol 46 (4) ◽  
pp. 471-484 ◽  
Author(s):  
Honglei Xu ◽  
Xinzhi Liu ◽  
Kok Lay Teo
Keyword(s):  
Feedback Control ◽  
Switched Systems ◽  
State Feedback ◽  
The State ◽  
State Feedback Control ◽  
State Model ◽  
Control Law ◽  
Time Varying ◽  
Impulsive Switched Systems ◽  
Bounded Uncertainty

AbstractIn this paper, we study the problem of robust H∞ stabilisation with definite attenuance for a class of impulsive switched systems with time-varying uncertainty. A norm-bounded uncertainty is assumed to appear in all the matrices of the state model. An LMI-based method for robust· H∞ stabilisation with definite attenuance via a state feedback control law is developed. A simulation example is presented to demonstrate the effectiveness of the proposed method.

Stabilization of Inverted Pendulum on a Cart in the Presence of Uncertainties

2015 ◽  
Author(s):  
Joonho Lee ◽  
Jongeun Choi
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
State Feedback ◽  
Inverted Pendulum ◽  
Output Feedback Control ◽  
Control Design ◽  
High Gain ◽  
State Feedback Control ◽  
Dynamic Inversion ◽  
Pass Through

This paper presents an output feedback control design to stabilize the inverted pendulum at the upright equilibrium as an extension of our previous work [1]. Compared to our previous work, we add one more time scale between a pendulum angle and angular velocity to reduce a traveled distance of the cart. State feedback control is designed to enable the pendulum to pass through input singularity configurations. Extended High-Gain Observers are used to estimate velocity and acceleration terms while dynamic inversion utilizes the estimates to deal with input coefficient uncertainties and singularity configurations. The proposed control is verified through numerical simulations.

Desain Power System Stabilizer Berbasis Fuzzy dan Particle Swarm Optimization

2019 ◽  
Vol 10 (1) ◽  
pp. 1-8
Author(s):  
Tamaji
Keyword(s):  
Particle Swarm Optimization ◽  
Feedback Control ◽  
Power System ◽  
State Feedback ◽  
The State ◽  
State Feedback Control ◽  
Power System Stabilizer ◽  
Feedback Gain ◽  
Swarm Optimization ◽  
System Stabilizer

One important factor to produce  a qualified electricity is the stability of the system.  An unstable system resulted  an undamped oscilation of system, and the stable system can damp the oscilation quickly. Therefore, it is necessary to apply  a stability device to a power system and it is called a Power System Stabilizer (PSS). One of stability design is a feedback control design. Here, in this research, the state feedback control are designed for Single Machine Infinite Bus (SMIB) . The SMIB model is non linear therefore the feedback control can’t be designed directly. Some researchers do linearize the system before design the feedback control.  In this research, a nonlinear model of SMIB is build in a state space form. Subsequently, a fuzzification Takagi-Sugeno is applied. The state feedback controls are applied to design the control of SMIB fuzzy system, a state feedback gain is determined using method Routh Hurwitz. The determining the parameter of state feedback gain influence the performance of SMIB. Therefore, it is important to determine the suitable parameter such that the SMIB has the optimal performance. The Particle Swarm Optimization (PSO) is applied to optimaze the performance of SMIB. In these research, it is compared the performance of SMIB by applying between Routh Hurwitz, fuzzy Routh Hurwitz, PSO fuzzy Routh Hurwitz for state feedback control. The simulation result show that Performance of SMIB using The PSO Fuzzy Routh  Hurwitz state feedback can improve the performance of SMIB, but the performance of Efd become oscillate and this method influence by the chosen parameter.

Maneuvering Support System for an Amphibian Vehicle – Warning Display to Prevent Rough Maneuvers –

2017 ◽  
Vol 29 (3) ◽  
pp. 591-601
Author(s):  
Ryota Hayashi ◽  
◽  
Genki Matsuyama ◽  
Hisanori Amano ◽  
Hitomu Saiki ◽  
...  
Keyword(s):  
Feedback Control ◽  
Support System ◽  
State Feedback ◽  
Trajectory Control ◽  
State Feedback Control ◽  
Control Law ◽  
Reference Trajectory ◽  
Display System ◽  
Additional Reference ◽  
Nonlinear State

[abstFig src='/00290003/14.jpg' width='300' text='Amphibian vehicle maneuvering simulator' ] This study proposes a maneuvering support system for an amphibian vehicle by applying a nonlinear state feedback control law for vehicle trajectory control. We consider that the vehicle should not drift sideways for good driving performance. To derive a nonlinear state feedback control law, we have defined ‘Maneuvering Trajectory’ as an additional reference trajectory that is generated by the driver’s maneuver. We have constructed a Lyapunov-like function for the trajectory control system. In this paper, we construct a vehicle-maneuvering simulator and set a clockwise circular reference trajectory. The efficiency of the proposed maneuvering support system is shown in the maneuvering simulations. We consider the case where the propulsive forces of the vehicle have limited influence on maneuverability. A new warning display system is proposed so that the driver can recognize if his or her maneuver is not suitable. Then, we examine the feasibility of the proposed warning display system through several simulations.

State Feedback and Output Feedback Control of Polynomial Nonlinear Systems Using Fractional Lyapunov Functions

2007 ◽  
Author(s):  
Qian Zheng ◽  
Fen Wu
Keyword(s):  
Feedback Control ◽  
Nonlinear Systems ◽  
Lyapunov Function ◽  
Output Feedback ◽  
Lyapunov Functions ◽  
State Feedback ◽  
The State ◽  
State Feedback Control ◽  
Feedback Gain ◽  
Variation Rate

In this paper, we will study the state feedback control problem of polynomial nonlinear systems using fractional Lyapunov functions. By adding constraints to bound the variation rate of each state, the general difficulty of calculating derivative of nonquadratic Lyapunov function is effectively overcome. As a result, the state feedback conditions are simplified as a set of Linear Matrix Inequalities (LMIs) with polynomial entries. Computationally tractable solution is obtained by Sum-of-Squares (SOS) decomposition. And it turns out that both of the Lyapunov matrix and the state feedback gain are state dependent fractional matrix functions, where the numerator as well as the denominator can be polynomials with flexible forms and higher nonlinearities involved in. Same idea is extended to a class of output dependent nonlinear systems and the stabilizing output feedback controller is specified as polynomial of output. Synthesis conditions are similarly derived as using constant Lyapunov function except that all entries in LMIs are polynomials of output with derivative of output involved in. By bounding the variation rate of output and gridding on the bounded interval, the LMIs are solvable by SOS decomposition. Finally, two examples are used to materialize the design scheme and clarify the various choices on state boundaries.

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