Direct model reference adaptive control of coupled tank liquid level control system

Industries such as petro-chemical industries, paper making industries, waste management and others are the vital industries where liquid level and flow control are essential. Liquids will be processed by chemical or mixing treatment in the tanks, but always the level fluid in the tanks must be controlled, and the flow between tanks must be regulated in the presence of nonlinearity and inexact model description of the plant. This project investigates the usage of Direct Model Reference Adaptive Control (DMRAC) in controlling the liquid level in the second tank of Coupled-Tank plant through variable manipulation of water pump in the first tank. It is to show that DMRAC could produce appropriate control signal to the coupled-tank system in response to the given desired water level with plant nonlinearity and measurement noise present simultaneously. The ability to use only input-output measurement of the plant in adaptation mechanism is the DMRAC’s special characteristics that does not require the explicit identification of the model description nor the solution to linear(or nonlinear) equations of the respective plant dynamics. A dynamic model of the plant is initially developed. Simulation studies are then conducted based on the developed model using Matlab and Simulink. A series of tracking performance tests, disturbance rejection and plant parameter changes are conducted to evaluate the controller performance in comparison to PID controller. The outcome of the project reveals that DMRAC is more robust than PID controller when there is a change in system parameters despite of its sensitivity to measurement noise. The framework of this project is generic enough to have an overview of the possible outcome before implementing the DMRAC controller in real-time system in the future

Robust Adaptive Cooperative Control for Formation-Tracking Problem in a Network of Non-Affine Nonlinear Agents

In this chapter, a decentralized cooperative control protocol is proposed with application to any network of agents with non-affine nonlinear multi-input-multi-output (MIMO) dynamics. Here, the main purpose of cooperative control protocol is to track a time-variant reference trajectory while maintaining a desired formation. The reference trajectory is defined to a leader, which has at least one information connection with one of the agents in the network. The design procedure includes a robust adaptive law for estimating the unknown nonlinear terms of each agent’s dynamics in a model-free format, that is, without the use of any regressors. Moreover, an observer is designed to have an approximation on the values of control parameters for the leader at the agents without connection to the leader. The entire design procedure is analysed successfully for the stability using Lyapunov stability theorem. Finally, the simulation results for the application of the proposed method on a network of nonholonomic wheeled mobile robots (WMR) are presented. Desirable leader-following tracking and geometric formation control performance have been successfully demonstrated through simulated group of wheeled mobile robots

An enhanced time synchronization protocol in automated surface vehicles

1056-1069Mobility of an autonomous surface vehicle (ASV) has caused the wireless sensor and actuator networks (WSANs) onboard to be mobile as well. However, the time synchronization of a WSAN on ASV is more challenging due to the environmental harshness and node mobility. In this paper, an enhanced control-theoretic distributed time synchronization protocol called Time Synchronization using Distributed Observer algorithm with Sliding mode control element (TSDOS) is presented to solve the time synchronization issue in ASV. This TSDOS protocol feeds a sliding mode control element on the relative comparative error to estimate the skew rate and relative skew rate. Through the theoretical analysis and simulations, TSDOS has showed the advantages of totally distributed, robust to node failure and time-varying clock frequencies, which are the situations usually faced by an ASV. In addition, TSDOS also has better or comparable performance over existing protocols in terms of rate of convergence, consensus error spike, and steady-state error

Classes Of Control Architectures For AUV: A Brief Survey.

This paper provides a brief survey on the control architectures used in the underwater system and robotics research for AUV application

Simulation of Direct Model Reference Adaptive Control on a Coupled-Tank System using Nonlinear Plant Model.

This paper presents the application of direct model reference adaptive control (DMRAC) on a nonlinear model of coupled-tank liquid level control system through simulation

Neuro-Fuzzy Algorithm Implemented In Altera’s FPGA For Mobile Robot’s Obstacle Avoidance Mission.

This paper presents the designed obstacle avoidance program for mobile robot that incorporates a neuro-fuzzy algorithm using Altera™ Field Programmable Gate Array (FPGA) development DE2 board

A SURVEY ON CONTROL TECHNIQUES OF A BENCHMARKED CONTINUOUS STIRRED TANK REACTOR

The study carried out in this paper unveils a survey on issues related to modelling problems control strategies of a Continuous Stirred Tank Reactor (CSTR), a highly nonlinear plant containing numbers of stable and unstable operating points is considered. The issues discussed are categorised into regulation, feedback linearization, flatness, observation and estimation as well as challenges related to equilibrium points concerning CSTR. In this study, the limited capability of a conventional PID controller is discussed based on preliminary description and a dynamic modelling of the nonlinear plant. Moreover, the limitations of the conventional PID is illustrated through a simulation using nonlinear model of CSTR carried out under input constraint and the presence of bounded disturbances. The result shows that a fixed PID will not guarantee consistent performance throughout operating set points. The feedback linearization formalism is presented to prove that only regulation in the neighbourhood of operating point is possible. Non-minimum phase property exhibited by a CSTR is investigated as well. Flatness control is demonstrated as one of the possible linearization control technique achieving the objective of the trajectory trackin

An adaptive observer-based parameter estimation algorithm with application to road gradient and vehicle's mass estimation

A novel observer-based parameter estimation algorithm with sliding mode term has been developed to estimate the road gradient and vehicle weight using only the vehicle's velocity and the driving torque from the engine. The estimation algorithm exploits all known terms in the system dynamics and a low pass filtered representation to derive an explicit expression of the parameter estimation error without measuring the acceleration. The proposed algorithm which features a sliding-mode term to ensure the fast and robust convergence of the estimation in the presence of persistent excitation is augmented to an adaptive observer and analyzed using Lyapunov Theory. The analytical results show that the algorithm is stable and ensures finite-time error convergence to a bounded error even in the presence of disturbances. A simple practical method for validating persistent excitation is provided using the new theoretical approach to estimation. This is validated by the practical implementation of the algorithm on a small-scaled vehicle, emulating a car system. The slope gradient as well as the vehicle's mass/weight are estimated online. The algorithm shows a significant improvement over a previous result