A Nonlinear Fuzzy Logic Controller Developed for an Autonomous Surface Boat

2005 ◽  
Author(s):  
Thomas A. Bean ◽  
Akira Okamoto ◽  
John R. Canning ◽  
Dean B. Edwards
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Optimization Method ◽  
Operating Point ◽  
Linear Feedback ◽  
Control Law ◽  
Linear Feedback Control ◽  
Linear Controller ◽  
Optimal Linear ◽  
Optimal Set

This paper presents an optimized nonlinear fuzzy logic controller designed for an autonomous surface craft and describes the process by which it was found. The nonlinear fuzzy logic controller described herein was developed to maintain the linear feedback control of an optimal set of controller gains when the state is near the operating point. The simplex optimization method was utilized to find the optimal fuzzy logic parameters that define the shape of the control law away from the normal operating point. The resultant controller showed approximately a 20% improvement over the optimal linear controller.

Optimization approach to the constrained regulation problem for linear continuous-time fractional-order systems

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Xindong Si ◽  
Hongli Yang
Keyword(s):  
Feedback Control ◽  
Fractional Order ◽  
State Feedback Control ◽  
Invariant Sets ◽  
Linear Feedback ◽  
Control Law ◽  
Optimization Approach ◽  
Fractional Order Systems ◽  
Linear Feedback Control ◽  
Computational Point

AbstractThis paper deals with the Constrained Regulation Problem (CRP) for linear continuous-times fractional-order systems. The aim is to find the existence conditions of linear feedback control law for CRP of fractional-order systems and to provide numerical solving method by means of positively invariant sets. Under two different types of the initial state constraints, the algebraic condition guaranteeing the existence of linear feedback control law for CRP is obtained. Necessary and sufficient conditions for the polyhedral set to be a positive invariant set of linear fractional-order systems are presented, an optimization model and corresponding algorithm for solving linear state feedback control law are proposed based on the positive invariance of polyhedral sets. The proposed model and algorithm transform the fractional-order CRP problem into a linear programming problem which can readily solved from the computational point of view. Numerical examples illustrate the proposed results and show the effectiveness of our approach.

Comparison of a Fuzzy Logic Controller With a P + D Control Law

1989 ◽  
Vol 111 (2) ◽  
pp. 128-137 ◽  
Author(s):  
S. Daley ◽  
K. F. Gill
Keyword(s):  
Fuzzy Logic ◽  
Attitude Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Good Control ◽  
Control Law ◽  
Dynamic Coupling ◽  
Process Knowledge ◽  
Logic Control ◽  
Limited Process

A study is described that compares the performance of a self-organizing fuzzy logic control law (SOC) with that of the more traditional P + D algorithm. The multivariate problem used for the investigation is the attitude control of a flexible satellite that has significant dynamic coupling of the axes. It is demonstrated that the SOC can provide good control, requires limited process knowledge and compares favorably with the P + D algorithm.

Control of Spin-Stabilized Spacecraft With Sloshing Fluid Stores

1992 ◽  
Vol 114 (4) ◽  
pp. 728-731 ◽  
Author(s):  
D. E. Hill ◽  
J. R. Baumgarten
Keyword(s):  
Dynamic Instability ◽  
Fluid Motion ◽  
Nonlinear Dynamic System ◽  
Linear Feedback ◽  
Control Law ◽  
Main Body ◽  
Spherical Pendulum ◽  
Linear Feedback Control ◽  
Highly Nonlinear ◽  
Body Dynamics

Spin-stabilized spacecraft with sloshing fluid stores are known to be a source of dynamic instability for certain spacecraft configurations. A time varying linear feedback control law was developed, using an equivalent spherical pendulum mechanical model of the fluid motion coupled to the main body dynamics, which stabilizes the highly nonlinear dynamic system within a large region of operation. The control law was also demonstrated to perform a pointing maneuver. A control design for a specific spacecraft is outlined and implemented by sensing only the main body angular rates and attitude.

An investigation of fuzzy logic control of flexible robots

Robotica ◽  
1993 ◽  
Vol 11 (4) ◽  
pp. 363-372 ◽  
Author(s):  
Yueh-Jaw Lin ◽  
Tian-Soon Lee
Keyword(s):  
Fuzzy Logic ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Robot Manipulator ◽  
Nonlinear Effects ◽  
Control Law ◽  
Flexible Robot ◽  
Control Rules ◽  
Logic Control ◽  
The Mathematical Model

SUMMARYIn this paper a control law, which consists of a fuzzy logic controller plus a nonlinear effects negotiator for a flexible robot manipulator, is presented. The nonlinear effects negotiator is used to enhence the control system's ability in dealing with the uncertainty of the mathematical model. The control algorithm is simple and easy to tune as opposed to conventional control law which requires time consuming gains selections. To obtain fuzzy control rules, an error response plane method is proposed.

The dynamic behavior of a parametrically excited time-periodic MEMS taking into account parametric errors

2016 ◽  
Vol 22 (20) ◽  
pp. 4101-4110 ◽  
Author(s):  
NJ Peruzzi ◽  
FR Chavarette ◽  
JM Balthazar ◽  
AM Tusset ◽  
ALPM Perticarrari ◽  
...  
Keyword(s):  
Feedback Control ◽  
Control Strategies ◽  
Mechanical Energy ◽  
Electrical Energy ◽  
Linear Feedback ◽  
Linear Feedback Control ◽  
Optimal Linear ◽  
Mems Mass Sensor ◽  
The Mathematical Model ◽  
Time Periodic

Micro-electromechanical systems (MEMS) are micro scale devices that are able to convert electrical energy into mechanical energy or vice versa. In this paper, the mathematical model of an electronic circuit of a resonant MEMS mass sensor, with time-periodic parametric excitation, was analyzed and controlled by Chebyshev polynomial expansion of the Picard interaction and Lyapunov-Floquet transformation, and by Optimal Linear Feedback Control (OLFC). Both controls consider the union of feedback and feedforward controls. The feedback control obtained by Picard interaction and Lyapunov-Floquet transformation is the first strategy and the optimal control theory the second strategy. Numerical simulations show the efficiency of the two control methods, as well as the sensitivity of each control strategy to parametric errors. Without parametric errors, both control strategies were effective in maintaining the system in the desired orbit. On the other hand, in the presence of parametric errors, the OLFC technique was more robust.

scholarly journals Robust Longitudinal Aircraft- Control Based on an Adaptive Fuzzy-Logic Algorithm

2002 ◽  
Vol 7 (1) ◽  
pp. 187
Author(s):  
Abdel- Latif Elshafei
Keyword(s):  
Fuzzy Logic ◽  
Feedback Linearization ◽  
Fuzzy Logic Controller ◽  
Control Law ◽  
Adaptive Fuzzy ◽  
Highly Nonlinear ◽  
Short Period ◽  
Wide Range ◽  
Modeling Errors ◽  
Adaptive Fuzzy Logic

To study the aircraft response to a fast pull-up manoeuvre, a short period approximation of the longitudinal model is considered. The model is highly nonlinear and includes parametric uncertainties. To cope with a wide range of command signals, a robust adaptive fuzzy logic controller is proposed. The proposed controller adopts a dynamic inversion approach. Since feedback linearization is practically imperfect, robustifying and adaptive components are included in the control law to compensate for modeling errors and achieve acceptable tracking errors. Two fuzzy systems are implemented. The first system models the nominal values of the system’s nonlinearity. The second system is an adaptive one that compensates for modeling errors. The derivation of the control law based on a dynamic game approach is given in detail. Stability of the closed-loop control system is also verified. Simulation results based on an F16-model illustrate a successful tracking performance of the proposed controller.   

scholarly journals Optimal PID and fuzzy logic based position controller design of an overhead crane using the Bees Algorithm

2021 ◽  
Vol 3 (10) ◽  
Author(s):  
Esmael Adem Esleman ◽  
Gürol Önal ◽  
Mete Kalyoncu
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Optimization Method ◽  
Industrial Applications ◽  
Bees Algorithm ◽  
Membership Functions ◽  
Overhead Crane ◽  
Target Values

AbstractDifferent industrial applications frequently use overhead cranes for moving and lifting huge loads. It applies to civil construction, metallurgical production, rivers, and seaports. The primary purpose of this paper is to control the motion/position of the overhead crane using a PID controller using Genetic Algorithms (GA) and Bee Algorithms (BA) as optimization tools. Moreover, Fuzzy Logic modified PID Controller is applied to obtain better controller parameters. The mathematical model uses an analytical method, and the PID model employs Simulink in MATLAB. The paper presents the PID parameters determination with a different approach. The development of membership functions, fuzzy rules employ the Fuzzy Logic toolbox. Both inputs and outputs use triangular membership functions. The result shows that the optimized value of the PID controller with the Ziegler-Nichols approach is time-consuming and will provide only the initial parameters. However, PID parameters obtained with the optimization method using GA and BA reached the target values. The results obtained with the fuzzy logic controller (0.227% overshoot) show improvement in overshoot than the conventional PID controller (0.271% overshoot).

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