Fuzzy Sliding Mode Controller Design Using Takagi-Sugeno Modelled Nonlinear Systems
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/734094 Open access Adaptive fuzzy sliding mode controller for a class of uncertain nonlinear systems is proposed in this paper. The unknown system dynamics and upper bounds of the minimum approximation errors are adaptively updated with stabilizing adaptive laws. The closed-loop system driven by the proposed controllers is shown to be stable with all the adaptation parameters being bounded. The performance and stability of the proposed control system are achieved analytically using the Lyapunov stability theory. Simulations show that the …
A structured filter for Markovian switching systems
In this work, a new methodology for the structuring of multiple model estimation schemas is developed. The proposed filter is applied to the estimation and detection of active mode in dynamic systems. The discrete-time Markovian switching systems represented by several linear models, associated with a particular operating mode, are studied. Therefore, the main idea of this work is the subdivision of the models set to some subsets in order to improve the detection and estimation performances. Each subset is associated with sub-estimators based on models of the subset. In order to compute the global estimate and subset probabilities, a global estimator is proposed. Theoretical developments ba…
Control of uncertain highly nonlinear biological process based on Takagi–Sugeno fuzzy models
This note deals with the control of uncertain highly nonlinear biological processes. Indeed, an adaptive fuzzy control (AFC) scheme is developed for the pre-treatment of wastewater represented by a Takagi-Sugeno (TS) fuzzy model. The proposed approach uses a fuzzy system to approximate the unknown substrate consumption rate in designing the adaptive controller, and then an observer is designed to estimate the concentration in substrate at the outlet bioreactor. The observer is employed to generate an error signal for the adaptive control law which permits to minimize the influence of the measurement noise on the estimation of the substrate concentration. An update of the fuzzy models parame…
On the robust design of unknown inputs Takagi-Sugeno observer
This paper deals with the observer design for Takagi-Sugeno (T-S) fuzzy models subject to unknown inputs and disturbance affecting both states and outputs of the system. Sufficient conditions to design an unknown input T-S observer are given in Linear Matrix Inequalities (LMIs) terms. Relaxations are introduced by using intermediate variables. Numerical example is given to illustrate the effectiveness of the given result.
Fuzzy predictive controller design using ant colony optimization algorithm
In this paper, an approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the Ant Colony Optimization (ACO) is studied. On-line adaptive fuzzy identification is used to identify the system parameters. These parameters are used to calculate the objective function based on predictive approach and structure of RST control. The optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to calculate a sequence of future RST control actions. The obtained simulation results show that proposed approach provides better results compared with Proportional Integral-Ant Colony Optimization (PI-ACO) controller and adaptive fuzzy model pr…
Notice of Violation of IEEE Publication Principles: Robust Observer Design for Unknown Inputs Takagi–Sugeno Models
This paper deals with the observer design for Takagi-Sugeno (T-S) fuzzy models subject to unknown inputs and disturbance affecting both states and outputs of the system. Sufficient conditions to design an unknown input T-S observer are given in linear matrix inequality (LMI) terms. Both continuous-time and discrete-time cases are studied. Relaxations are introduced by using intermediate variables. Extension to the case of unmeasured decision variables is also given. A numerical example is given to illustrate the effectiveness of the given results.
Modeling, Planning, and Control of Complex Logistic Processes
1Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway 2College of Engineering, University of Wisconsin System, Madison, WI, USA 3ArcelorMittal Bremen GmbH, Bremen, Germany 4BIBA-Bremer Institut fur Produktion und Logistik GmbH, Planning and Control of Production Systems (PSPS), University of Bremen, Hochschulring 20, 28359 Bremen, Germany 5University of Picardie Jules Verne, MIS-UPJV, 7 Moulin Neuf, 80000 Amiens, France
Robust Predictive Control of a variable speed wind turbine using the LMI formalism
This paper proposes a Robust Fuzzy Multivariable Model Predictive Controller (RFMMPC) using Linear Matrix Inequalities (LMIs) formulation. The main idea is to solve at each time instant, an LMI optimization problem that incorporates input, output and Constrained Receding Horizon Predictive Control (CRHPC) constraints, and plant uncertainties, and guarantees certain robustness properties. The RFMMPC is easily designed by solving a convex optimization problem subject to LMI conditions. Then, the derived RFMMPC applied to a variable wind turbine with blade pitch and generator torque as two control inputs. The effectiveness of the proposed design is shown by simulation results.
Robust Output-Feedback Based Fault-Tolerant Control of Active Suspension with Finite-Frequency Constraint ★ ★This work is partly supported by National Natural Science Foundation of China(Grant nos. 51205058, 51375086, 61403252), and Jiangsu Province Science Foundation for Youths, China(Grant no. BK20140634),the Foundation of Education Office of Guangxi Province of China (Grant no. KY2015YB101), the Fundamental Research Funds for the Central Universities and Jiangsu Postgraduate Innovation Programm (Grant no. KYLX-0102).
Abstract In this paper, the H∞ fault-tolerant control (FTC) problem of active suspensions with finite-frequency constraints is investigated. A full-car model is employed in the controller design such that the heave, pitch and roll motions can be simultaneously controlled. Both the actuator faults and external disturbance are considered in the controller design. As the human body is more sensitive to the vertical vibration in 4-8Hz, robust H∞ control with finite frequency constraints is designed. From the practical perspective, a robust dynamic output-feedback controller with fault tolerant ability is proposed, while other performances such as suspension deflection and actuator saturation ar…
Composite nonlinear feedback control for path following of four-wheel independently actuated autonomous ground vehicles
This paper studies the path following control problem for four-wheel independently actuated (FWIA) autonomous ground vehicles (AGVs) through integrated control of active front-wheel steering (AFS) and direct yaw-moment control (DYC). A modified composite nonlinear feedback (CNF) strategy is proposed to improve the transient performance and eliminate the steady-state errors in the path following control considering the tire force saturations, in the presence of the time-varying road curvature for the desired path. The path following is achieved through vehicle lateral and yaw control, i.e., the lateral velocity and yaw rate are simultaneously controlled to track their respective desired valu…
Robust fault tolerant tracking controller design for vehicle dynamics: A descriptor approach
Abstract In this paper, an active Fault Tolerant Tracking Controller (FTTC) scheme dedicated to vehicle dynamics system is proposed. To address the challenging problem, an uncertain dynamic model of the vehicle is firstly developed, by considering the lateral forces nonlinearities as a Takagi–Sugeno (TS) representation, the sideslip angle as unmeasurable premise variables and the road bank angle as an unknown input. Subsequently, the vehicle dynamic states with the sensor faults are jointly estimated by a descriptor observer on the basis of the roll rate and the steering angle measures. Then a fault tolerant tracking controller is synthesized and solutions are proposed in terms of Linear Ma…
Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2013/670878 Open Access This paper presents an unknown input Proportional Multiple-Integral Observer (PIO) for synchronization of chaotic systems based on Takagi-Sugeno (TS) fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory…
Finite-time stability and stabilisation for a class of nonlinear systems with time-varying delay
This paper is concerned with the problems of finite-time stability FTS and finite-time stabilisation for a class of nonlinear systems with time-varying delay, which can be represented by Takagi–Sugeno fuzzy system. Some new delay-dependent FTS conditions are provided and applied to the design problem of finite-time fuzzy controllers. First, based on an integral inequality and a fuzzy Lyapunov–Krasovskii functional, a delay-dependent FTS criterion is proposed for open-loop fuzzy system by introducing some free fuzzy weighting matrices, which are less conservative than other existing ones. Then, the parallel distributed compensation controller is designed to ensure FTS of the time-delay fuzzy…
Recent Advances on Mathematical Modeling and Control Methods for Complex Vehicle Systems
1 Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway 2 College of Automation, Harbin Engineering University, Nantong Street #145, Nangang District, Harbin, China 3 School of Astronautics, Harbin Institute of Technology, P.O. Box 3015, Yikuang Street #2, Nangang District, Harbin, China 4 Laboratory of Modeling, Information & Systems, University of Picardie Jules Verne, Amiens, France
Discrete-timeH − ∕ H ∞ sensor fault detection observer design for nonlinear systems with parameter uncertainty
SUMMARY This work concerns robust sensor fault detection observer (SFDO) design for uncertain and disturbed discrete-time Takagi–Sugeno (T–S) systems using H − ∕ H ∞ criterion. The principle of the proposed approach is based on simultaneously minimizing the perturbation effect and maximizing the fault effect on the residual vector. Furthermore, by introducing slack decision matrices and taking advantage of the descriptor formulation, less conservative sufficient conditions are proposed leading to easier linear matrix inequalities (LMIs). Moreover, the proposed (SFDO) design conditions allow dealing with unmeasurable premise variables. Finally, a numerical example and a truck–trailer system…
Fuzzy control for Electric Power Steering System with assist motor current input constraints
Abstract Friction and disturbances of the road are the main sources of nonlinearity in the Electric Power Steering (EPS) System. Consequently, conventional linear controllers design based on a simplified linear model of the EPS system will result in poor dynamic performance or system instability. On the other hand, a brush-type DC motor is more used in EPS control with an input current that is limited in practice. The control laws designed without taking into account the saturation effect may have undesirable consequences on the system stability. In this paper, a Takagi–Sugeno (T−S) fuzzy is used to represent the nonlinear behavior of an EPS system, and stabilization conditions for nonlinea…
Robust Observer Design for Takagi-Sugeno Fuzzy Systems with Mixed Neutral and Discrete Delays and Unknown Inputs
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/635709 A robust observer design is proposed for Takagi-Sugeno fuzzy neutral models with unknown inputs. The model consists of a mixed neutral and discrete delay, and the disturbances are imposed on both state and output signals. Delay-dependent sufficient conditions for the design of an unknown input T-S observer with time delays are given in terms of linear matrix inequalities. Some relaxations are introduced by using intermediate variables. A numerical example is given to illustrate the effectiveness of the given results.
Robust fault tolerant tracking controller design for a VTOL aircraft
This paper deals with the fault tolerant control (FTC) design for a Vertical Takeoff and Landing (VTOL) aircraft subject to external disturbances and actuator faults. The aim is to synthesize a fault tolerant controller ensuring trajectory tracking for the nonlinear uncertain system represented by a Takagi-Sugeno (T-S) model. In order to design the FTC law, a proportional integral observer (PIO) is adopted which estimate both of the faults and the faulty system states. Based on the Lyapunov theory and ℓ2 optimization, the trajectory tracking performance and the stability of the closed loop system are analyzed. Sufficient conditions are obtained in terms of linear matrix inequalities (LMI). …
An ant colony optimization-based fuzzy predictive control approach for nonlinear processes
In this paper, a new approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the ant colony optimization (ACO) is proposed. On-line adaptive fuzzy identification is introduced to identify the system parameters. These parameters are used to calculate the objective function based on a predictive approach and structure of RST control. Then the optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to determine optimal controller parameters of RST control. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, where the proposed approach provides better performances compared with p…
H∞ fuzzy control of DC-DC converters with input constraint
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2012/973082 Open access This paper proposes a method for designing H∞ fuzzy control of DC-DC converters under actuator saturation. Because linear control design methods do not take into account the nonlinearity of the system, a T-S fuzzy model and a controller design approach is used. The designed control not only handles the external disturbance but also the saturation of duty cycle. The input constraint is first transformed into a symmetric saturation which is represented by a polytopic model. Stabilization conditions for the H∞ state feedba…
On stability and stabilization of singular uncertain Takagi-Sugeno fuzzy systems
This paper deals with the problem of robust stability and robust stabilization for a class of continuous-time singular Takagi-Sugeno fuzzy systems. Sufficient conditions on stability and stabilization are proposed in terms of strict LMI (Linear Matrix Inequality) for uncertain T-S fuzzy models. In order to reduce the conservatism of results developed using quadratic method, an approach based on non-quadratic Lyapunov functions and S-procedure is proposed. Illustrative examples are given to show the effectiveness of the given results Refereed/Peer-reviewed
Control and Estimation of Electrified Vehicles
Fault Detection, Isolation, andTolerant Control of Vehicles using Soft Computing Methods
Faults diagnosis based on proportional integral observer for TS fuzzy model with unmeasurable premise variable
In this work, we focus on the synthesis of a Proportional Integral (PI) observer for the actuators and sensors faults diagnosis based on Takagi-Sugeno (TS) fuzzy model with unmeasurable premise variables. The faults estimation method is based on the assumption that these faults act as unknown inputs under polynomials form whose their kth derivatives are bounded. The convergence conditions of the observer as well as the faults reconstruction are established on the basis of the Lyapunov stability theory and the L 2 optimization technique, expressed as Linear Matrix Inequalities (LMI) constraints. In order to validate the proposed approach, a hydraulic system with two tanks is proposed.
Design of robust observer for T-S fuzzy time-delayed systems subject to unknown inputs
In this paper, a novel approach is proposed to design a robust observer for a class of Takagi-Sugeno (T-S) fuzzy models with unknown inputs and delays. The main contribution of this paper is to consider unknown inputs and a mixed neutral and discrete delay in the model. Also, the system is subject to disturbances, which are imposed on both state and output signals. Delay-dependent sufficient conditions for the design of an unknown input T-S observer with time delays are given in terms of linear matrix inequalities (LMIs). Some relaxations are introduced by using intermediate variables. A numerical example is given to illustrate the effectiveness of the given results.
Design of unknown inputs proportional integral observers for TS fuzzy models
In this paper the design of unknown inputs proportional integral observers for Takagi-Sugeno (TS) fuzzy models subject to unmeasurable decision variables is proposed. These unknown inputs affect both state and output of the system. The synthesis of these observers is based on two hypotheses that the unknown inputs are under the polynomials form with their kth derivatives zero for the first one and bounded norm for the second one, hence two approaches. The Lyapunov theory and L"2-gain technique are used to develop the stability conditions of such observers in LMIs (linear matrix inequality) formulation. A simulation example is given to validate and compare the proposed design conditions for …