Adaptive fuzzy sliding mode control for coordinated longitudinal and lateral motions of multiple autonomous vehicles in a platoon

In this paper, the platoon control problem of autonomous vehicles in highway is studied. Since the autonomous vehicles have the characteristics of nonlinearities, external disturbances and strong coupling, a novel adaptive fuzzy sliding coordinated control system is constructed to supervise the longitudinal and lateral motions of autonomous vehicles, in which the fuzzy system is employed to approximate the unknown nonlinear functions. Due to the low sensitivity to disturbances and plant parameter variations, the proposed control approach is an efficient way to handle with the complex dynamic plants operating under un-certainty conditions. The asymptotic stability of adaptive coordinated platoon close-loop control system is verified based on the Lyapunov stability theory. The results indicate that the presented adaptive coordinated platoon control approach can accurately achieve the tracking performance and ensures the stability and riding comfort of autonomous vehicles in a platoon. Finally,simulation test is exploited to demonstrate the effectiveness of the proposed control approach.

Adaptive Fuzzy Sliding Mode Control of Under-actuated Nonlinear Systems

A new extension of the conventional adaptive fuzzy sliding mode control（AFSMC） scheme, for the case of under-actuated and uncertain affine multiple-input multiple-output（MIMO） systems, is presented. In particular, the assumption for non-zero diagonal entries of the input gain matrix of the plant is relaxed. In other words, the control effect of one actuator can propagate from a subgroup of canonical state equations to the rest of equations in an indirect sense. The asymptotic stability of the proposed AFSM control method is proved using a Lyapunov-based methodology. The effectiveness of the proposed method for the case of under-actuated systems is investigated in the presence of plant uncertainties and disturbances, through simulation studies.

Adaptive fuzzy integral sliding mode pressure control for cutter feeding system of trench cutter

A nonlinear pressure controller was presented to track desired feeding pressure for the cutter feeding system(CFS) of trench cutter(TC) in the presence of unknown external disturbances.The feeding pressure control of CFS is subjected to unknown load characteristics of rock or soil; in addition,the geological condition is time-varying.Due to the complex load characteristics of rock or soil,the feeding velocity of TC is related to geological conditions.What is worse,its dynamic model is subjected to uncertainties and its function is unknown.To deal with the particular characteristics of CFS,a novel adaptive fuzzy integral sliding mode control(AFISMC) was designed for feeding pressure control of CFS,which combines the robust characteristics of an integral sliding mode controller and the adaptive adjusting characteristics of an adaptive fuzzy controller.The AFISMC feeding pressure controller is synthesized using the backstepping technique.The stability of the overall closed-loop system consisting of the adaptive fuzzy inference system,integral sliding mode controller and the cutter feeding system is proved using Lyapunov theory.Experiments are conducted on a TC test bench with the AFISMC under different operating conditions.The experimental results demonstrate that the proposed AFISMC feeding pressure controller for CFS gives a superior and robust pressure tracking performance with maximum pressure tracking error within ?0.3 MPa.

Variable speed wind turbine for maximum power capture using adaptive fuzzy integral sliding mode control

This paper presents a nonlinear control approach to variable speed wind turbine(VSWT)with a wind speed estimator.The dynamics of the wind turbine(WT)is derived from single mass model.In this work,a modified Newton Raphson estimator has been considered for exact estimation of effective wind speed.The main objective of this work is to extract maximum energy from the wind at below rated wind speed while reducing drive train oscillation.In order to achieve the above objectives,VSWT should operate close to the optimal power coefficient.The generator torque is considered as the control input to achieve maximum energy capture.From the literature,it is clear that existing linear and nonlinear control techniques suffer from poor tracking of WT dynamics,increased power loss and complex control law.In addition,they are not robust with respect to input disturbances.In order to overcome the above drawbacks,adaptive fuzzy integral sliding mode control(AFISMC)is proposed for VSWT control.The proposed controller is tested with different types of disturbances and compared with other nonlinear controllers such as sliding mode control and integral sliding mode control.The result shows the better performance of AFISMC and its robustness to input disturbances.In this paper,the discontinuity in integral sliding mode controller is smoothed by using hyperbolic tangent function,and the sliding gain is adapted using a fuzzy technique which makes the controller more robust.

Fuzzy adaptive sliding mode controller for electrically driven wheeled mobile robot for trajectory tracking task

This paper presents a fuzzy adaptive sliding mode controller(FASMC)for electrically driven wheeled mobile robot for trajectory tracking task in the presence of uncertainties and disturbances.First,a finite-time kinematic controller is developed to compute the auxiliary velocity vector.Second,the FASMC,based on the nonlinear dynamic model of the robot and its actuators,is used to guarantee the stability and the convergence of the closed-loop system.Moreover,by employing the advantages of the fuzzy logic systems,the developed controller ensures the robustness of the system against dynamic disturbances and uncertainties,the smoothness of the computing voltage against the chattering phenomenon,and the optimal convergence of the velocity and posture errors.The Lyapunov theory is used to analyse the stability of this algorithm.In order to evaluate the effectiveness of the developed method,numerical simulations are done in the Mahlab/Simulink environment.