Compact Fuzzy Systems Based on Boolean Relations

This document presents some considerations and procedures to design a compact fuzzy system based on Boolean relations. In the design process, a Boolean codification of two elements is extended to a Kleene’s of three elements to perform simplifications for obtaining a compact fuzzy system. The design methodology employed a set of considerations producing equivalent expressions when using Boole and Kleene algebras establishing cases where simplification can be carried out, thus obtaining compact forms. In addition, the development of two compact fuzzy systems based on Boolean relations is shown, presenting its application for the identification of a nonlinear plant and the control of a hydraulic system where it can be seen that compact structures describes satisfactory performance for both identification and control when using algorithms for optimizing the parameters of the compact fuzzy systems. Finally, the applications where compact fuzzy systems are based on Boolean relationships are discussed allowing the observation of other scenarios where these structures can be used.

REPETITIVE ADAPTIVE CONTROL OF NONLINEAR UNCERTAIN PLANT WITH INPUT SATURATION

The article proposes solution to the problem of synthesizing adaptive control algorithm for dy-namic T-periodic nonlinear plant operating under conditions of structural and parametric uncer-tainty, in the presence of input restrictions and constant bounded disturbances. The hyperstabil-ity criterion, L-dissipativity conditions, fast-acting filter-correctors, and an implicit reference model are used as the methods for synthesis of repetitive adaptive control system.

Comparison of robust optimal QFT controller with TFC and MFC controller in a multi-input multi-output system

This paper suggests a practical approach for the development of a stable robot controller using the Quantitative Feedback Principle (QFT). Robot manipulators have a multivariable nonlinear transfer function, the implementation of the QFT method includes, first the conversion of their nonlinear plant into a group of linear and uncertain plant set, and then an ideal robust controller for each set has been designed. To demonstrate the effectiveness of our algorithm, we show the implementation of the two degrees of freedom manipulator. In the approach provided, the controller has been designed directly by specifying and optimizing the transfer function coefficients using a genetic algorithm. The consistency and limitations of the method are considered to be the restrictions of the problem in the optimization process. System stability and tracking problem are perceived to be the limitations of the system in the optimization process. Non-linear simulations on the tracking problem are carried out and the results illustrate the performance of the controllers. Finally, the controller constructed based on the QFT approach is compared with the TFC and MFC (Fuzzy) controllers and it is shown that the QFT methodology indicates a controller that has increased control efficiency.

Discrete Time-Coupled State-Dependent Riccati Equation Control of Nonlinear Mechatronic Systems

A discrete-time-coupled state-dependent Riccati equation (CSDRE) control strategy is structured in this paper for synthesizing state feedback controllers satisfying the combined nonlinear quadratic regulator (NLQR) and H∞ robust control performance objectives. Under smoothness assumptions, the nonlinear plant dynamics can be formulated into state-dependent coefficient form through direct parameterization. By solving a pair of coupled state-dependent Riccati equations, the optimal stabilizing solutions can achieve inherent stability, nonlinear quadratic optimality, and H∞ disturbance attenuation performance. The established two-player Nash's game theory is utilized for developing both of the finite and infinite time optimal control laws. Furuta swing-up pendulum, a representative nonholonomic underactuated nonlinear system, is stabilized in real-time for validating the robustness and potential of proposed approach in mechatronics applications.

Modeling, design, and control of low-cost Remotely Operated Vehicle for shallow water survey

Shallow water zones, including lakes, ponds, creeks, and rivers, play a prominent role in the spiritual culture and economy of Vietnamese people throughout history. Therefore, numerous researches have been conducted in regard to this topic for many purposes, most of which focus on elevating the quality of life and safety. With the aid of new technology, modern platforms gradually replace conventional methods and reach a higher level of efficiency and convenience. This paper presents the research on design and control of Remotely Operated Vehicle (ROV) belonging to National key Laboratory of Digital Control and System Engineering. Basically, it is controlled by human pilots to move underwater and perform specifically pre-assigned tasks. The power supply and communication channel for the vehicle are connected from an onshore station via cable systems. There are several stages of the pipeline in implementing a full-scale ROV platform that must be studied carefully. Prior to the experiments in practical conditions, the proposed 3D model designed by SOLIDWORKS® and MATLAB Simulink® mathematical model analysis firstly provide a nonlinear plant in order to apply classical PID controllers and evaluate their feasibility through simulation process. The outer frame protects other components from being damaged or unattached, while the thruster allocation strategy from the simulated model enables flexibility in motion. A system of sensors and cameras collects data from an underwater environment for on-the-spot monitoring, or they can be captured for further post-analysis processes. After assembling all parts into a whole model, we launched the vehicle at the maximum depth of a pool as the condition of a shallow water survey. Optimistic experimental results have proved the ability of controllers even in case of the presence of external disturbances.