scholarly journals Reactive control scheme based on fuzzy behaviors for mobile robot

2020 ◽  
Vol 16 (31) ◽  
pp. 9-18
Author(s):  
Orlando Zapata-Cortés ◽  
Gustavo Alonso Acosta-Amaya ◽  
Jovani Alberto Jiménez-Builes
Keyword(s):  
Behavioral Inhibition ◽  
Reactive Control ◽  
Robotic Platform ◽  
Subsumption Architecture ◽  
Scheme Design ◽  
Design And Implementation ◽  
Control Actions ◽  
Control Scheme ◽  
Behavior Based Control ◽  
Left And Right

This paper presents the design and implementation of a behavior-based control scheme. The construction of the set of behaviors is based on the use of fuzzy logic as a means for materializing the designer’s knowledge into the behaviors. The behavior set was established by left and right wall following and obstacle avoidance. These three behaviors were programmed and coordinated by a subsumption architecture or behavioral inhibition. Behavior simulations and coordination scheme design were tested by means of real experiments using a mobile robotic platform. Finally, the results are presented, where the control actions are executed by the robotic system achieving a secure navigation.

scholarly journals A Novel Control Scheme Design and Implementation of Cane feeding System in Sugar Plant

2018 ◽  
Vol 51 (1) ◽  
pp. 389-394 ◽  
Author(s):  
Abhir Raj Metkar ◽  
S. Rominus Valsalam ◽  
N. Sivakumaran
Keyword(s):  
Feeding System ◽  
Scheme Design ◽  
Design And Implementation ◽  
Control Scheme ◽  
Sugar Plant

Optimal Model Reference Control Scheme Design for Nonlinear Strict-Feedback Systems

2020 ◽  
Vol 38 (9A) ◽  
pp. 1342-1351
Author(s):  
Musadaq A. Hadi ◽  
Hazem I. Ali
Keyword(s):  
Reference Model ◽  
Feedback System ◽  
Optimization Method ◽  
Feedback Systems ◽  
Model Reference ◽  
Scheme Design ◽  
Model Reference Control ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Strict Feedback

In this paper, a new design of the model reference control scheme is proposed in a class of nonlinear strict-feedback system. First, the system is analyzed using Lyapunov stability analysis. Next, a model reference is used to improve system performance. Then, the Integral Square Error (ISE) is considered as a cost function to drive the error between the reference model and the system to zero. After that, a powerful metaheuristic optimization method is used to optimize the parameters of the proposed controller. Finally, the results show that the proposed controller can effectively compensate for the strictly-feedback nonlinear system with more desirable performance.

Signal Synthesis Model Reference Adaptive Controller with Artificial Intelligent Technique for a Control of Continuous Stirred Tank Reactor

2018 ◽  
Vol 17 (2) ◽  
Author(s):  
Harsh Goud ◽  
Pankaj Swarnkar
Keyword(s):  
Steady State ◽  
Stirred Tank ◽  
Continuous Stirred Tank Reactor ◽  
Stirred Tank Reactor ◽  
Tank Reactor ◽  
Design And Implementation ◽  
Control Scheme ◽  
Signal Synthesis ◽  
Continuous Stirred Tank ◽  
The Given

AbstractModelling and controlling of Continuous stirred tank reactor (CSTR) is one of the major problems in the process industry. The nonlinear characteristic of CSTR may change the variation of temperature in either direction from the given set value. Chemical reactions within the CSTR depends on the given reference temperature. Such variation from reference values may result in degrading the variety of biomass. Design and implementation of the precise control device in such system are difficult for researchers. This paper proposes the MIT based control scheme as a solution to control problem of CSTR. An improvement of signal synthesis MIT system has been proposed in this study to enhance the steady-state and transient performance of CSTR. Artificial Bee Colony (ABC) based controller parameter tuning technique is applied to get the optimal performance of the controller. This paper shows the design and implementation of conventional PID tuned with the Z-N method, adaptive PID tune with ABC, MIT and ABC-MIT for CSTR. Detailed comparison based on simulation studies is presented which shows that ABC-MIT based control scheme improves the transient and steady state response.

Statistical Process Control Scheme Design

1995 ◽  
Vol 27 (3) ◽  
pp. 214-225 ◽  
Author(s):  
J. Bert Keats ◽  
John D. Miskulin ◽  
George C. Runger
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Statistical Process ◽  
Scheme Design ◽  
Control Scheme
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