Синтез системы управления полетом с нечеткими регуляторами на основе линейных матричных неравенств

Розглядається задача синтезу статичного регулятора за виходом у ланцюзі зворотного зв’язку для системи управління польотом малого безпілотного апарата, яка складається із двох контурів: внутрішнього “чіткого” та зовнішнього нечіткого. Задача синтезу статичного зворотного зв’язку за виходом розглядається в термінах лінійних матричних нерівностей (ЛМН). Особливість цієї статті полягає в тому, що ЛМН, які використовуються для синтезу “чіткого” зворотного зв’язку, використовуються у процедурі синтезу статичного зворотного зв’язку за виходом зовнішнього контуру управління для нечіткої моделі Такагі – Сугено (Т-С). Ефективність запропонованого методу ілюструється на прикладі синтезу системи управління бічним рухом безпілотного літального апарату (БПЛА).This paper presents the problem of static output feedback controller design for small UAV with combined structure of Flight Control System (FCS). The architecture of FCS includes the inner “crisp” and outer fuzzy loops. The proposed design method is based on Linear Matrix Inequality approach (LMI). The main feature of this paper constitutes that the LMI approach used for inner loop controller design is extended to the outer loop static output feedback (SOF) construction for Takagi-Sugeno (T-S) Fuzzy System. The efficiency of the proposed design method is demonstrated by an example of lateral channel of the Unmanned Aerial Vehicle flight control system.В статье рассматривается задача синтеза статического регулятора по выходу в цепи обратной связи для системы управления полетом малого беспилотного аппарата, состоящей из двух контуров: внутреннего “четкого” и внешнего нечеткого. Задача синтеза статической обратной связи по выходу рассматривается в терминах линейных матричных неравенствах (ЛМН). Особенность данной статьи является то, что ЛМН, используемые для синтеза четкой обратной связи, распространяются на синтез статической обратной связи по выходу внешнего контура управления для нечеткой модели Такаги – Сугено. Эффективность предложенного метода иллюстрируется на примере синтеза системы управления полетом боковым движением беспилотного летательного аппарата (БПЛА)

Constrained Nonlinear Model Predictive Control of an MMA Polymerization Process via Evolutionary Optimization

In this work, a nonlinear model predictive controller is developed for a batch polymerization process. The physical model of the process is parameterized along a desired trajectory resulting in a trajectory linearized piecewise model (a multiple linear model bank) and the parameters are identified for an experimental polymerization reactor. Then, a multiple model adaptive predictive controller is designed for thermal trajectory tracking of the MMA polymerization. The input control signal to the process is constrained by the maximum thermal power provided by the heaters. The constrained optimization in the model predictive controller is solved via genetic algorithms to minimize a DMC cost function in each sampling interval.Comment: 12 pages, 9 figures, 28 reference

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

Hierarchically Clustered Adaptive Quantization CMAC and Its Learning Convergence

No abstract availabl

CAutoCSD-evolutionary search and optimisation enabled computer automated control system design

This paper attempts to set a unified scene for various linear time-invariant (LTI) control system design schemes, by transforming the existing concept of 'Computer-Aided Control System Design' (CACSD) to the novel 'Computer-Automated Control System Design' (CAutoCSD). The first step towards this goal is to accommodate, under practical constraints, various design objectives that are desirable in both time and frequency-domains. Such performance-prioritised unification is aimed to relieve practising engineers from having to select a particular control scheme and from sacrificing certain performance goals resulting from pre-committing to the adopted scheme. With the recent progress in evolutionary computing based extra-numeric, multi-criterion search and optimisation techniques, such unification of LTI control schemes becomes feasible, analytically and practically, and the resultant designs can be creative. The techniques developed are applied to, and illustrated by, three design problems. The unified approach automatically provides an integrator for zero-steady state error in velocity control of a DC motor, meets multiple objectives in designing an LTI controller for a non-minimum phase plant and offers a high-performing LTI controller network for a nonlinear chemical process

Integrated fault estimation and accommodation design for discrete-time Takagi-Sugeno fuzzy systems with actuator faults

This paper addresses the problem of integrated robust fault estimation (FE) and accommodation for discrete-time Takagi–Sugeno (T–S) fuzzy systems. First, a multiconstrained reduced-order FE observer (RFEO) is proposed to achieve FE for discrete-time T–S fuzzy models with actuator faults. Based on the RFEO, a new fault estimator is constructed. Then, using the information of online FE, a new approach for fault accommodation based on fuzzy-dynamic output feedback is designed to compensate for the effect of faults by stabilizing the closed-loop systems. Moreover, the RFEO and the dynamic output feedback fault-tolerant controller are designed separately, such that their design parameters can be calculated readily. Simulation results are presented to illustrate our contributions

Nonlinear static output feedback controller design for uncertain polynomial systems: An iterative sums of squares approach

This paper examines the problem of designing a nonlinear static output feedback controller for uncertain polynomial systems via an iterative sums of squares approach. The derivation of the static output feedback controller is given in terms of the solvability conditions of state dependent bilinear matrix inequalities (BMIs). An iterative algorithm based on the sum of squares (SOS) decomposition is proposed to solve these state-dependent BMIs. Finally, numerical examples are provided at the end of the paper as to demonstrate the validity of the proposed design techniqu