Showing papers by "Hamid Reza Karimi published in 2015"
TL;DR: It is shown that the proposed controller guarantees that all signals in the closed-loop system are fourth-moment semiglobally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood of the origin in the sense of mean quartic value.
Abstract: This paper focuses on the problem of approximation-based adaptive fuzzy tracking control for a class of stochastic nonlinear time-delay systems with a nonstrict-feedback structure. A variable separation approach is introduced to overcome the design difficulty from the nonstrict-feedback structure. Mamdani-type fuzzy logic systems are utilized to model the unknown nonlinear functions in the process of controller design, and an adaptive fuzzy tracking controller is systematically designed by using a backstepping technique. It is shown that the proposed controller guarantees that all signals in the closed-loop system are fourth-moment semiglobally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood of the origin in the sense of mean quartic value. Simulation results are provided to demonstrate the effectiveness of our results. Further developments will consider how to generalize the proposed strategy to nonstrict-feedback nonlinear systems with input nonlinearities.
246 citations
TL;DR: A state-estimation-based sliding mode control law is designed to guarantee the reachability of the sliding surface in finite time interval and a stochastic stability criterion is established for all admissible uncertainties, which can guarantee the error system and sliding mode dynamics to be asymptotically stochastically stable with a given disturbance attenuation level.
240 citations
TL;DR: An input–output (IO) approach to the delay-dependent stability analysis and H ∞ controller synthesis for a class of continuous-time Markovian jump linear systems (MJLSs) and conditions for the underlying MJLSs are formulated in terms of linear matrix inequalities.
Abstract: This paper proposes an input–output (IO) approach to the delay-dependent stability analysis and H ∞ controller synthesis for a class of continuous-time Markovian jump linear systems (MJLSs). The concerned systems are with a time-varying delay in the state and deficient mode information in the Markov stochastic process, which simultaneously involves the exactly known, partially unknown and uncertain transition rates. It is first shown that the original system with time-varying delay can be reformulated by a new IO model through a process of two-term approximation and the stability problem of the original system can be transformed into the scaled small gain (SSG) problem of the IO model. Then, based on a Markovian Lyapunov–Krasovskii formulation of SSG condition together with some convexification techniques, the stability analysis and state-feedback H ∞ controller synthesis conditions for the underlying MJLSs are formulated in terms of linear matrix inequalities. Simulation studies are provided to illustrate the effectiveness and superiority of the proposed analysis and design methods.
168 citations
TL;DR: In this paper, the problem of quantized filtering for a class of continuous-time Markovian jump linear systems with deficient mode information is investigated, where the measurement output of the plant is quantized by a mode-dependent logarithmic quantizer, and the defect in the Markov stochastic process simultaneously considers the exactly known, partially unknown, and uncertain transition rates.
Abstract: This paper investigates the problem of quantized filtering for a class of continuous-time Markovian jump linear systems with deficient mode information. The measurement output of the plant is quantized by a mode-dependent logarithmic quantizer, and the deficient mode information in the Markov stochastic process simultaneously considers the exactly known, partially unknown, and uncertain transition rates. By fully exploiting the properties of transition rate matrices, together with the convexification of uncertain domains, a new sufficient condition for quantized performance analysis is first derived, and then two approaches, namely, the convex linearization approach and iterative approach, to the filter synthesis are developed. It is shown that both the full-order and reduced-order filters can be obtained by solving a set of linear matrix inequalities (LMIs) or bilinear matrix inequalities (BMIs). Finally, two illustrative examples are given to show the effectiveness and less conservatism of the proposed design methods.
140 citations
TL;DR: In this article, the robust fault-tolerant H ∞ control problem of active suspension systems with finite-frequency constraint is investigated, and a full-car model is employed in the controller design such that the heave, pitch and roll motions can be simultaneously controlled.
137 citations
TL;DR: In this article, robust sensor fault detection observer (SFDO) design for uncertain and disturbed discrete-time Takagi-Sugeno (T-S) systems using H−−−√H √H√√ H√ √ H √∆∆H∞∆criterion is proposed.
Abstract: 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 model are proposed to illustrate the efficiency of the SFDO design methodology. Copyright © 2013 John Wiley & Sons, Ltd.
131 citations
TL;DR: In this paper, the authors investigated finite-time stability and stabilization problems for a class of switched linear systems with polytopic uncertainties, where stable and unstable subsystems are considered to coexist in the system, and a new concept of extended FT stability was proposed as the first attempt.
Abstract: This paper investigates finite-time (FT) stability and stabilization problems for a class of switched linear systems with polytopic uncertainties. Both stable and unstable subsystems are considered to coexist in the system, and a new concept of extended FT stability is proposed as the first attempt. A stability criterion is first established, where the admissible maximum switching number is obtained while ensuring extended FT stability of switched linear systems with time-varying delays under a given maximum ratio between the running time of unstable subsystems and the running time of stable subsystems. Sufficient conditions on the existence of desired memory state-feedback controllers are then developed. A numerical example and a class of servomechanism systems are given, respectively, to illustrate the effectiveness and validity of the developed techniques with time-varying delays and without time delay.
114 citations
TL;DR: In this article, a gain-scheduling observer is proposed to estimate the sideslip angle with the yaw rate measurements by employing the vehicle dynamics, and the observer gain can be determined with off-line computation and on-line computations.
107 citations
TL;DR: The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, where the proposed approach provides better performances compared with proportional integral-ant colony optimization controller and adaptive fuzzy model predictive controller.
104 citations
TL;DR: This paper presents the adjustable single point under quasi constant pressure strategy of the hydraulic hybrid off-road vehicles which can reduce the fuel consumption clearly without deteriorating the performance.
Abstract: Applying the electric hybrid technique on the off-road vehicle is one popular method to reduce the fuel consumption. However, the high cost, low energy conversion efficiency and disposal of used batteries are still the main problems. This paper is focusing on one alternative choice which is hydraulic hybrid off-road vehicles. Among the most typical off-road vehicles, the excavator is chosen as the prototype to study the control strategy. First, the basic principle of the hydraulic hybrid excavator based on Common Pressure Rail is introduced. Then, the mathematical model of the whole excavator is created. Moreover, the dynamic programming algorithm is used to solve the optimal control variable trajectory under a given circle. Finally, the adjustable single point under quasi constant pressure strategy is presented. The simulation result shows that the proposed strategy can reduce the fuel consumption clearly without deteriorating the performance.
103 citations
TL;DR: Simulation results prove the effectiveness of the proposed finite-frequency H ∞ controller method and show that the human body is much sensitive to vibrations between 4 and 8 Hz.
Abstract: In this paper, the parameter optimization and H ∞ control problem of active suspensions equipped in in-wheel motor driven electric ground vehicles are investigated. In order to better isolate the force transmitted to motor bearing, dynamic vibration absorber (DVA) is installed in the active suspension. Parameters of the vibration isolation modules are also optimized in order to achieve better suspension performances. As the human body is much sensitive to vibrations between 4 and 8 Hz, a finite-frequency state-feedback H ∞ controller is designed to achieve the targeted disturbance attenuation in the concerned frequency range while other performances such as road holding capability and small suspension deflection are also maintained. The performance of the proposed finite-frequency H ∞ controller is compared with that of an entire frequency one, simulation results prove the effectiveness of the proposed control method.
TL;DR: Simulation results show that both the saturated and constrained controls can stabilize the resulting closed-loop EPS system and provide a stable driving in the presence of nonlinear friction, disturbance of the road and actuator saturation.
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 nonlinear EPS system with both constrained and saturated control input cases are proposed in terms of linear matrix inequalities (LMI). Simulation results show that both the saturated and constrained controls can stabilize the resulting closed-loop EPS system and provide a stable driving in the presence of nonlinear friction, disturbance of the road and actuator saturation.
TL;DR: Two approaches, namely, the convex linearisation approach and iterative approach, to the model approximation synthesis are developed, formulated in terms of strict linear matrix inequalities (LMIs) or a sequential minimization problem subject to LMI constraints.
Abstract: This paper is concerned with the problem of $$\mathscr {H}_{\infty }$$H� model approximation for a class of two-dimensional (2-D) discrete-time Markovian jump linear systems with state-delays and imperfect mode information. The 2-D system is described by the well-known Fornasini-Marchesini local state-space model, and the imperfect mode information in the Markov chain simultaneously involves the exactly known, partially unknown and uncertain transition probabilities. By using the characteristics of the transition probability matrices, together with the convexification of uncertain domains, a new $$\mathscr {H}_{\infty }$$H� performance analysis criterion for the underlying system is firstly derived, and then two approaches, namely, the convex linearisation approach and iterative approach, to the $$\mathscr {H}_{\infty }$$H� model approximation synthesis are developed. The solutions to the problem are formulated in terms of strict linear matrix inequalities (LMIs) or a sequential minimization problem subject to LMI constraints. Finally, simulation studies are provided to illustrate the effectiveness of the proposed design methods.
TL;DR: In this article, a sliding mode control law is developed to drive the state trajectory of the closed-loop system to the specified linear switching surface in a finite-time interval in spite of the existing uncertainties, time delays and unknown transition rates.
TL;DR: In this article, a decentralized unscented Kalman filter (UKF) method based on a consensus algorithm for multi-area power system dynamic state estimation is presented, where the overall system is split into a certain number of non-overlapping areas.
TL;DR: A multivariate model is established and improves the accuracy of computation by combing traditional fuzzy time series models and rough set method and using fuzzy c-mean algorithm to make the data into discrete.
TL;DR: In this article, the authors present state-of-the-art methods in the sales forecasting research with a focus on fashion and new product forecasting, and review different strategies to the predictive value of user-generated content and search queries.
Abstract: Sales forecasting is an essential task in retailing. In particular, consumer-oriented markets such as fashion and electronics face uncertain demands, short life cycles and a lack of historical sales data which strengthen the challenges of producing accurate forecasts. This survey paper presents state-of-the-art methods in the sales forecasting research with a focus on fashion and new product forecasting. This study also reviews different strategies to the predictive value of user-generated content and search queries.
TL;DR: This paper investigates the problem of global exponential stability in mean square of delayed Markovian jump fuzzy cellular neural networks (DMJFCNNs) with generally uncertain transition rates (GUTRs), and develops a new uncertain model that is more general than the existing ones.
TL;DR: This paper investigates the filtering problem of discrete-time Takagi-Sugeno (T-S) fuzzy uncertain systems subject to time-varying delays and proposes filter design methods and the filter gain matrices can be obtained by calculating a set of linear matrix inequalities.
Abstract: In this paper, we investigate the filtering problem of discrete-time Takagi–Sugeno (T–S) fuzzy uncertain systems subject to time-varying delays. A reduced-order filter is designed. With the augmentation technique, a filtering error system with delayed states is obtained. In order to deal with time delays in system states, the filtering error system is first transformed into two interconnected subsystems. By using a two-term approximation for the time-varying delay, sufficient delay-dependent conditions of finite-time boundedness and $H_{\infty }$ performance of the filtering error system are derived with the Lyapunov function. Based on these conditions, the filter design methods are proposed and the filter gain matrices can be obtained by calculating a set of linear matrix inequalities. A numerical example is used to illustrate the effectiveness of the proposed approaches.
TL;DR: In this article, a weighted sum approach of the different input matrices is introduced to construct a common sliding surface, and by on-line estimating the loss of effectiveness of the actuators, an adaptive sliding mode controller is designed.
Abstract: The problem of sliding mode control is considered for a class of uncertain switched systems subject to actuator faults. It is assumed that there may happen degradation in each actuator channel. Besides, the authors relax the restrictive assumption that each subsystem shares the same input channel, which is different from some existing works. In this work, a weighted sum approach of the different input matrices is introduced to construct a common sliding surface. Moreover, by on-line estimating the loss of effectiveness of the actuators, an adaptive sliding mode controller is designed. This does not only compensate the effects of the actuator degradation effectively, but can also reduce the conservatism compared with some existing approaches which only utilise the bound of the gain variation. It is shown that the reachability of the specified sliding surface can be ensured, and a sufficient condition on the exponential stability of sliding mode dynamics is obtained via the average dwell time method. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.
TL;DR: An adaptive neural network state-feedback controller for a class of nonlinear systems with mismatched uncertainties is proposed and an observer-based adaptive controller based on RBFNN is designed to stabilize uncertain non linear systems with immeasurable states.
Abstract: In this paper, first, an adaptive neural network (NN) state-feedback controller for a class of nonlinear systems with mismatched uncertainties is proposed. By using a radial basis function NN (RBFNN), a bound of unknown nonlinear functions is approximated so that no information about the upper bound of mismatched uncertainties is required. Then, an observer-based adaptive controller based on RBFNN is designed to stabilize uncertain nonlinear systems with immeasurable states. The state-feedback and observer-based controllers are based on Lyapunov and strictly positive real-Lyapunov stability theory, respectively, and it is shown that the asymptotic convergence of the closed-loop system to zero is achieved while maintaining bounded states at the same time. The presented methods are more general than the previous approaches, handling systems with no restriction on the dimension of the system and the number of inputs. Simulation results confirm the effectiveness of the proposed methods in the stabilization of mismatched nonlinear systems.
TL;DR: The sufficient conditions for asymptotically stochastic stability of sliding mode dynamics with a given disturbance attenuation level are presented in terms of linear matrix inequalities (LMIs).
01 Dec 2015
TL;DR: Results indicate that the proposed CNF controller can effectively improve the transient response performance, inhibit the overshoots and eliminate the steady-state errors in path following within the tire forces saturation limits.
Abstract: 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 values, where the desired yaw rate is generated according to the path following demand. CarSim-Simulink joint simulation results indicate that the proposed CNF controller can effectively improve the transient response performance, inhibit the overshoots and eliminate the steady-state errors in path following within the tire forces saturation limits.
TL;DR: The stability of singular systems based on SVSC scheme is guaranteed by an equivalent characterization theory, and then a soft variable structure controller is designed for achieving rapid regulative rate, and shortening arrival time.
Abstract: A novel soft variable structure control (SVSC) scheme is addressed for a class of singular systems under I-controllable in this paper The structural features of SVSC with differential equations are investigated The stability of singular systems based on SVSC scheme is guaranteed by an equivalent characterization theory, and then a soft variable structure controller is designed The concrete algorithm of SVSC with differential equations is proposed The developed SVSC law for singular systems is carried out for the purpose of achieving rapid regulative rate, and shortening arrival time Moreover, system chattering can be attenuated in the process of approaching to the equilibrium state Finally, a simulation example is provided to verify the feasibility of the proposed scheme
TL;DR: In this article, a sufficient condition for the existence of a state feedback controller is proposed such that the disturbance tolerance capability of the closed-loop system is ensured by solving a convex optimization problem with linear matrix inequality (LMI) constraints.
TL;DR: This article is concerned with the stabilization problem for nonlinear networked control systems which are represented by polynomial fuzzy models, and a novel sampled-data fuzzy controller is designed to guarantee that the closed-loop system is asymptotically stable.
Abstract: This article is concerned with the stabilization problem for nonlinear networked control systems which are represented by polynomial fuzzy models. Two communication features including signal transmission delays and data missing are taken into account in a network environment. To solve the network-induced communication problems, a novel sampled-data fuzzy controller is designed to guarantee that the closed-loop system is asymptotically stable. The stability and stabilization conditions are presented in terms of sum of squares SOS, which can be numerically solved via SOSTOOLS. Finally, a simulation example is provided to demonstrate the feasibility of the proposed method. © 2014 Wiley Periodicals, Inc. Complexity 21: 74-81, 2015
TL;DR: The saturation behavior is described with the help of the convex hull representation, and a sufficient condition for asymptotical stability of the closed-loop system is proposed in terms of linear matrix inequalities via the multiple Lyapunov functional approach.
Abstract: This paper is concerned with the problem of state feedback $$H_\infty $$H? stabilization of discrete two-dimensional switched delay systems with actuator saturation represented by the second Fornasini and Marchesini state-space model. Firstly, the saturation behavior is described with the help of the convex hull representation, and a sufficient condition for asymptotical stability of the closed-loop system is proposed in terms of linear matrix inequalities via the multiple Lyapunov functional approach. Then, a state feedback controller is designed to guarantee the $$H_\infty $$H? disturbance attenuation level of the corresponding closed-loop system. Finally, two examples are provided to validate the proposed results.
TL;DR: In this paper, a series of estimations performed in order to establish the actual cost-effectiveness of three different small wind turbines (SWTs) design solutions were evaluated and based on their power curves and installation costs, using wind data from a numerical weather prediction (WNP) model, a return on investment (ROI) period was calculated.
TL;DR: An adaptive fuzzy control scheme is developed for the pre-treatment of wastewater represented by a Takagi-Sugeno (TS) fuzzy model, which 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.
TL;DR: In this paper, a Lyapunov function is constructed from the sum of nonlinearly-weighted functions of individual subsystems for a feedback interconnection of two discrete-time subsystems, where one subsystem is allowed to be semiglobally practically integral input-to-state stable.