Adaptive Control

Abstract— This paper presents an adaptive control scheme for suppressing jitter in laser beams. The variable-order adaptive controller is based on an adaptive lattice filter that implicitly identifies the disturbance statistics from real-time sensor data. The multi-channel adaptive ...

Introduction The purpose of this paper is to serve as an introduction to neural networks and to sug-gest that neural network architecture can be used for design and application of intelligent control systems [ 11. The neural network ap-proach is introduced by defining the problem ...

Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain competitive researchers attempt to design an adaptive control system which optimizes the process, but also able to adapt to rapidly evolving demands at a fixed cost. In this paper, we present a multi-agent approach for the dynamic task scheduling in petroleum industry production system. Agents simultaneously insure effective production scheduling and the continuous improvement of the solution quality by means of reinforcement learning, using the SARSA algorithm. Reinforcement learning allows the agents to adapt, learning the best behaviors for their various roles without reducing the performance or reactivity. To demonstrate the innovation of our approach, we include a computer simulation of our model and the results of experimentation applying our model to an Algerian petroleum refinery.

This paper presents a control strategy for the coordination of multiple mobile robots. A combination of the virtual structure and path following approaches is used to derive the formation architecture. A formation controller is proposed for the kinematic model of two-degree-of-freedom unicycle-type mobile robots. The approach is then extended to consider the formation controller by taking into account the physical

This paper presents an adaptive position control scheme for DC motors based on an on-line closed loop continuous-time identiflcation method. A fast, non-asymptotic, algebraic identiflcation method is used to estimate simultaneously the unknown sys- tem parameters and the unmeasured states to update an adaptive position control scheme.

With the increasing number of vehicles on the road, it has become difficult to properly control the flow of traffic especially in large cities like Lahore. The proposed system uses a digital camera mounted on a stepper motor to sense the traffic on the road. The decision to open the lane is done after monitoring the traffic load. The heavily loaded side is turned on for a longer time. Thus the system is intelligent because it is not using the fixed time frame. The system is also integrated with GSM, thus the signals can also be ...

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The present study deals with the analysis of a Lotka-Volterra model describing competition between tumor and immune cells. The model consists of differential equations with piecewise constant arguments and based on metamodel constructed by Stepanova. Using the method of reduction to discrete equations, it is obtained a system of difference equations from the system of differential equations. In order to get local and global stability conditions of the positive equilibrium point of the system, we use Schur-Cohn criterion and Lyapunov function that is constructed. Moreover, it is shown that periodic solutions occur as a consequence of Neimark-Sacker bifurcation.

This paper proposes a novel optimal adaptive event-triggered
control algorithm for nonlinear continuous-time systems. The goal
is to reduce the controller updates, by sampling the state only
when an event is triggered to maintain stability and optimality.
The online algorithm is implemented based on an actor/critic
neural network structure. A critic neural network is used to
approximate the cost and an actor neural network is used to
approximate the optimal {event-triggered controller}. Since in the
algorithm proposed there are dynamics that exhibit continuous
evolutions described by ordinary differential equations and
instantaneous jumps or impulses, we will use an impulsive system
approach. A Lyapunov stability proof ensures that the closed-loop
system is asymptotically stable. Finally, we illustrate the effectiveness of the proposed solution compared to a time-triggered controller.

Citation: Kyriakos G. Vamvoudakis. Event-triggered optimal adaptive control algorithm for continuous-time nonlinear systems.  IEEE/CAA Journal of Automatica Sinica, 2014, 1(3): 282-293

The International Journal of Chaos, Control, Modelling and Simulation is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Chaos Theory, Control Systems, Scientific Modelling and Computer Simulation. In the last few decades, chaos theory has found important applications in secure communication devices and secure data encryption. Control methods are very useful in several applied areas like Chaos, Automation, Communication, Robotics, Power Systems, and Biomedical Instrumentation. The journal focuses on all technical and practical aspects of Chaos, Control, Modelling and Simulation. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on chaotic systems and applications, control theory, process control, automation, modelling concepts, computational methods, computer simulation and establishing new collaborations in these areas.

Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Chaos Theory, Control Systems, Modelling and Simulation Techniques.

5th International Conference on Applied Mathematics and Sciences (AMA 2021)will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications impacts and challenges of Mathematics and Sciences. The conference documents practical and theoretical results which make a fundamental contribution for the development of Mathematics and Sciences. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. The goal of this Conference is to bring together researchers and practitioners from academia and industry to focus on Mathematics and Sciences advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Mathematics.

This paper has implemented an adaptive control technique for Continuous Stirred Tank Reactor (CSTR) process. The transfer function representing the dynamics of a CSTR process was obtained. The system was modeled in Simulink and simulated without being compensated. The output response in terms of concentration to unit step input revealed that a compensator was needed to improve the transient characteristics performance. A Model Reference Adaptive Controller (MRAC) was designed based on the MIT rule and integrated with CSTR process. The Simulink model of the MRAC control for CSTR process is developed. The performance of the MRAC controller was analyzed in terms of Integral Square Error (ISE), Integral Absolute Error (IAE) and Integral Time Absolute Error (ITAE). The simulation results obtained showed that the controller provided robust and improved tracking error for the range of gain selected, with gain adjusted to 25 providing the most effective and robust tracking error performance with ISE of 0.3324, IAE of 0.4408, and ITAE of 0.3945.

—Adaptive traffic control system is the latest generation of traffic control systems that operates, manages and control the signalized intersections with/without coordination. ATAK is one of the adaptive traffic control system that is developed by ISBAK Inc., in Turkey. It uses the genetic and fuzzy-logic algorithm as an optimization tool. The genetic algorithm is used for optimizing signal timings and fuzzy logic is used for controlling the exceptional cases during the operation of traffic control devices. This study defines the ATAK system as an traffic management tool at signalized intersections. The performance of the system is outlined. Application of the ATAK system at isolated and coordinated intersection showed that the performance improvement is about 10% in terms of cycle time and travel time improvement is about 15%.

In this paper we present a method for adaptive feedback linearization contorl of CSTR. Because of the nature of CSTR, the parameters of the system, like feed flowrate, feed temperature, concentration of components in the feed and inlet temperature of coolant, may change with time. So for detecting these changes, online system identification is performed and the NARMA-L2 model of

The problem of balancing an inverted pendulum has been a benchmark problem in demonstrating various control design techniques. The principal reasons for it's popularity are its nonlinear and unstable characteristics. In this paper a single link inverted pendulum system has been chosen and adaptive control algorithm has been implemented for stabilization of the system so that pendulum is always maintained erected in its upright (inverted) position. Model Reference Adaptive Control (MRAC) method is implemented using MIT rule. Minimization of cost function is performed and system response has been observed for different adaption gain. After system modeling the whole process is done in MATLAB Simulink.