Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the Differential Evolution Algorithm

This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

Novel ARC-Fuzzy Coordinated Automatic Tracking Control of Four-Wheeled Mobile Robot

Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure.The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots.However,there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion.As a result,the mobile robot has lim-ited performance,such as chattering during curved movement.In this research work,a three-tiered adaptive robust control with fuzzy parameter estimation,including dynamic modeling,direct torque control and wheel slip control is pro-posed.Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller(ARC)parameters and tracking the trajectories with less tracking error as well as high tracking accuracy.This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique.Our suggested approach outperforms the existing control methods such as Fuzzy,proportional–integral–derivative(PID)and adaptive robust controller with discrete projection(ARC–DP).The experimental results show that the scheduled performance index decreases by 2.77%and 4.76%.All the experimen-tal simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.

Robust adaptive fuzzy tracking control for a class of strict-feedback nonlinear systems based on backstepping technique

In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlinear functions. A design scheme of the robust adaptive fuzzy controller is proposed by use of the backstepping technique. The proposed controller guarantees semi-global uniform ultimate boundedness of all the signals in the derived closed-loop system and achieves the good tracking performance. The possible controller singularity problem which may occur in some existing adaptive control schemes with feedback linearization techniques can be avoided. In addition, the number of the on-line adaptive parameters is not more than the order of the designed system. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed control scheme.

Robust Fuzzy Tracking Control for Nonlinear Networked Control Systems with Integral Quadratic Constraints

This paper investigates the robust tracking control problcm for a class of nonlinear networked control systems （NCSs） using the Takagi-Sugeno （T-S） fuzzy model approach. Based on a time-varying delay system transformed from the NCSs, an augmented Lyapunov function containing more useful information is constructed. A less conservative sufficient condition is established such that the closed-loop systems stability and time-domain integral quadratic constraints （IQCs） are satisfied while both time-varying network- induced delays and packet losses are taken into account. The fuzzy tracking controllers design scheme is derived in terms of linear matrix inequalities （LMIs） and parallel distributed compensation （PDC）. Furthermore, robust stabilization criterion for nonlinear NCSs is given as an extension of the tracking control result. Finally, numerical simulations are provided to illustrate the effectiveness and merits of the proposed method.

Research of robust adaptive trajectory linearization control based on T-S fuzzy system

A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.

Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model

An extended robust model predictive control approach for input constrained discrete uncertain nonlinear systems with time-delay based on a class of uncertain T-S fuzzy models that satisfy sector bound condition is presented. In this approach, the minimization problem of the “worst-case” objective function is converted into the linear objective minimization problem in- volving linear matrix inequalities (LMIs) constraints. The state feedback control law is obtained by solving convex optimization of a set of LMIs. Sufficient condition for stability and a new upper bound on robust performance index are given for these kinds of uncertain fuzzy systems with state time-delay. Simulation results of CSTR process show that the proposed robust predictive control approach is effective and feasible.

Linearization of T-S fuzzy systems and robust H_∞ control

Takagi-Sugeno(T-S) fuzzy model is difficult to be linearized because of membership functions included.So,novel T-S fuzzy state transformation and T-S fuzzy feedback are proposed for the linearization of T-S fuzzy system.The novel T-S fuzzy state transformation is the fuzzy combination of local linear transformation which transforms local linear models in the T-S fuzzy model into the local linear controllable canonical models.The fuzzy combination of local linear controllable canonical model gives controllable canonical T-S fuzzy model and then nonlinear feedback is obtained easily.After the linearization of T-S fuzzy model,a robust H∞ controller with the robustness of sliding model control(SMC) is designed.As a result,controlled T-S fuzzy system shows the performance of H∞ control and the robustness of SMC.

Robust Controller Design of a Class of Uncertain Switched Fuzzy Systems with Delays

The robust control problem for a class of uncertain switched fuzzy systems with delays is investigated. Firstly,the model of the switched fuzzy system is presented and the parallel distributed compensation( PDC) technology is employed to design fuzzy controllers. Then, based on the convex combination method, a sufficient condition for robust stabilization in terms of linear matrix inequalities( LMIs) is obtained and a switching law is presented.Meanwhile,the Lyapunov-Krasovskii functional is taken to deal with time varying delays. Moreover,an algorithm is applied to finding a solution for a group of convex combination coefficient. Finally,a numerical example is given to demonstrate the effectiveness of the proposed method.

Robust H∞ Networked Control for Uncertain Fuzzy Systems with Time-delay

柔韧的 H 联网了控制方法因为有无常和时间的模糊系统推迟的 Takagi-Sugeno (T-S ) 被介绍。一个州的反馈控制器经由联网的控制系统(NCS ) 被设计理论。为有 H 性能的柔韧的稳定性的足够的状况被获得。在网络传播和包退学学生的导致网络的延期被分析。模拟结果显示出这个控制计划的有效性。

Robust H_∞ controller design for a class of nonlinear fuzzy time-delay systems

The problem of fuzzy modeling for state and input time-delays systems with a class of nonlinear uncertainties by fuzzy T-S model is addressed.By using the linear matrix inequality（LMI） method, the problem of fuzzy robust H ∞ controller design for the system is studied.Assuming that the nonlinear uncertain functions in the model considered are gain-bounded, a sufficient condition for the robustly asymptotic stability of the closed-loop system is obtained via Lyapunov stability theory.By solving the LMI, a feedback control law which guarantees the robustly asymptotic stability of the closed-loop system is constructed and the effect of the disturbance input on the controlled output is ruduced to a prescribed level.

Delay-dependent robust H_∞control of convex polyhedral uncertain fuzzy systems

The robust H∞ control problem for a class of uncertain Takagi-Sugeno fuzzy systems with timevarying state delays is studied. The uncertain parameters are supposed to reside in a polytope. Based on the delay-dependent Lyapunov functional method, a new delay-dependent robust H∞ fuzzy controller, which depends on the size of the delays and the derivative of the delays, is presented in term of linear matrix inequalities （LMIs）. For all admissible uncertainties and delays, the controller guarantees not only the asymptotic stability of the system but also the prescribed H∞ attenuation level. In addition, the effectiveness of the proposed design method is demonstrated by a numerical example.

Delay-dependent robust H_∞ control for uncertain discrete time-delay fuzzy systems

The robust H∞ control problem of norm bounded uncertain discrete Takagi-Sugeno （T-S） fuzzy systems with state delay is addressed. First, by constructing an appropriate basis-dependent Lyapunov-Krasovskii function, a new delay-dependent sufficient condition on robust H∞-disturbance attenuation is presented, in which both robust stability and prescribed H∞ performance are guaranteed to be achieved. Then based on the condition, a delay-dependent robust Hoo controller design scheme is developed in term of a convex algorithm. Finally, examples are given to illustrate the effectiveness of the proposed method.

Robust fuzzy control for chaotic dynamics in Lorenz systems with uncertainties

This paper deals with the robust fuzzy control for chaotic systems in the presence of parametric uncertainties. An uncertain Takagi-Sugeno fuzzy model for a Lorenz chaotic system is first constructed. Then a robust fuzzy state feedback control scheme ensures the control for stable operations under bounded parametric uncertainties. For a chaotic system with known uncertainty bounds, a robust fuzzy regulator is designed by choosing the control parameters satisfying the linear matrix inequality. To verify the validity and effectiveness of the proposed controller design method, an analysis technique is suggested and applied to the control of an uncertain Lorenz chaotic system.

Robust State Feedback H_∞Control for Dynamic Biped Robot Based on T-S Fuzzy Model

T-S fuzzy model was applied to describe nonlinear system and global fuzzy model was expressed by the form of uncertain system.Based on robust state feedback H_∞control strategy,designed a global asymptotic steady fuzzy model.This control system can use the experimental input-output data pairs for the biped robot learning and walking with dynamic balance.It is proved by simulation result that robust state feedback H_∞control method based on T-S fuzzy model can effectively restrain the effect of model uncertainties and external disturbance acting on biped robot.From these works,we showed the satisfactory performance of joint tracking without any chattering.

Robust control for a class of uncertain switched fuzzy systems

A model of uncertain switched fuzzy systems whose subsystems are uncertain fuzzy systems is presented. Robust controllers for a class of switched fuzzy systems are designed by using the Lyapunov function method. Stability conditions for global asymptotic stability are developed and a switching strategy is proposed. An example shows the effectiveness of the method.

Robust passive control for discrete-time T-S fuzzy systems with delays

This article deals with the robust stability analysis and passivity of uncertain discrete-time Takagi- Sugeno （T-S） fuzzy systems with time delays. The T-S fuzzy model with parametric uncertainties can approximate nonlinear uncertain systems at any precision. A sufficient condition on the existence of robust passive controller is established based on the Lyapunov stability theory. With the help of linear matrix inequality （LMI） method, robust passive controllers are designed so that the closed-loop system is robust stable and strictly passive. Furthermore, a convex optimization problem with LMI constraints is formulated to design robust passive controllers with the maximum dissipation rate. A numerical example illustrates the validity of the proposed method.

Fuzzy robust attitude controller design for hydrofoil catamaran

A robust attitude controller for hydrofoil catamaran throughout its operating envelope is proposed, based on Tagaki-Sugeno (T-S) fuzzy model. Firstly, T-S fuzzy model and robust attitude control strategy for hydrofoil catamaran is presented by use of linear matrix inequality (LMI) techniques. Secondly, a nonlinear mathematical model of hydrofoil catamaran is established, acting as the platform for further researches. The specialty in interpolation of T-S fuzzy model guarantees that feedback gain can be obtained smoothly, while boat's speed is shifting over the operating envelope. The external disturbances are also attenuated to achieve H ∞ control performance, meanwhile. Finally, based on such a boat, HC200B-A1, simulation researches demonstrate the design procedures and the effectiveness of fuzzy robust attitude controller.

Fuzzy Robust H1 Control for UncertainNonlinear Systems via Output Feedback

This paper is concerned with a fuzzy robust H∞ control problem via output feedbackfor a class of uncertain nonlinear systems. The uncertain nonlinear systemsare represented by fuzzy Takagi-Sugeno （T-S） model, and a fuzzy controller is designedbased on the state observer. A sufficient condition for the existence of fuzzycontroller is given in terms of the linear matrix inequalities （LMIs） and the adaptivelaw. Based on Lyapunov stability theorem, the proposed fuzzy control scheme suchthat the desired H∞performance is achieved in the sense that all the closed-loopsignals are uniformly ultimately bounded （UUB）. Simulation results indicate theeffectiveness of the developed control scheme. In this paper, a less conservativefuzzy tracking controller is proposed, where the matching condition and the upperbound are avoided. Comparing with the existing works, the dimension of the LMIsof this paper is reduced.

Research on Robust Control of Nonlinear Fuzzy VSS for Spacecraft

The nonlinear dynamic system of spacecraft with uncertainty and coupling is analyzed and its general dynamical equation is given.The decoupling-ability and controllability are proved.Aiming at this system,a new nonlinear decoupling controlling method is put forward by synthetically using the variable structure and fuzzy theory.The simulation results show that this method is effective in tracking performances under the existence of uncertainty and outer disturbance.