A Novel Fuzzy Logic Based Adaptive Supertwisting Sliding Mode Control Algorithm for Dynamic Uncertain Systems

This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness of the proposed controller over the first order Sliding Mode Fuzzy Logic controller is illustrated by Matlab based simulations performed on a DC-DC Buck converter. Based on this comparison, the proposed controller is shown to obtain the desired transient response without causing chattering and error under steady-state conditions. The proposed controller is able to give robust performance in terms of rejection to input voltage variations and load variations.Comment: 14 page

Adaptive fuzzy sliding mode control for uncertain nonlinear underactuated mechanical systems

Sliding mode control has been shown to be a robust and effective control approach for stabilization of nonlinear systems. However the dynamic performance of the controller is a complex function of the system parameters, which is often uncertain or partially known. This paper presents an adaptive fuzzy sliding mode control for a class of underactuated nonlinear mechanical systems. An adaptive fuzzy system is used to approximate the uncertain parts of the underactuated system. The adaptive law is designed based on the Lyapunov method. The proof for the stability and the convergence of the system is presented. Robust performance of the adaptive fuzzy sliding mode control is illustrated using a gantry crane system. Simulation results demonstrate that the system output can track the reference signal in the presence of modelling uncertainties, external disturbances and parameter variation. © 2013 IEEE

Design stable robust intelligent nonlinear controller for 6- DOF serial links robot manipulator

In this research parallel Proportional-Derivative (PD) fuzzy logic theory plus Integral part (I) is used to compensate the system dynamic uncertainty controller according to highly nonlinear control theory sliding mode controller. Sliding mode controller (SMC) is an important considerable robust nonlinear controller. In presence of uncertainties, this controller is used to control of highly nonlinear systems especially for multi degrees of freedom (DOF) serial links robot manipulator. In opposition, sliding mode controller is an effective controller but chattering phenomenon and nonlinear equivalent dynamic formulation in uncertain dynamic parameters are two significant drawbacks. To reduce these challenges, new stable intelligent controller is introduce

Type-2 Fuzzy Hybrid Controller Network for Robotic Systems

Dynamic control, including robotic control, faces both the theoretical challenge of obtaining accurate system models and the practical difficulty of defining uncertain system bounds. To facilitate such challenges, this paper proposes a control system consisting of a novel type of fuzzy neural network and a robust compensator controller. The new fuzzy neural network is implemented by integrating a number of key components embedded in a Type-2 fuzzy cerebellar model articulation controller (CMAC) and a brain emotional learning controller (BELC) network, thereby mimicking an ideal sliding mode controller. The system inputs are fed into the neural network through a Type-2 fuzzy inference system (T2FIS), with the results subsequently piped into sensory and emotional channels which jointly produce the final outputs of the network. That is, the proposed network estimates the nonlinear equations representing the ideal sliding mode controllers using a powerful compensator controller with the support of T2FIS and BELC, guaranteeing robust tracking of the dynamics of the controlled systems. The adaptive dynamic tuning laws of the network are developed by exploiting the popular brain emotional learning rule and the Lyapunov function. The proposed system was applied to a robot manipulator and a mobile robot, demonstrating its efficacy and potential; and a comparative study with alternatives indicates a significant improvement by the proposed system in performing the intelligent dynamic control

Design of set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers for quadcopter UAVs

Copyright © 2019 Inderscience Enterprises Ltd. This research is to develop set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers to deal with nonlinear and underactuated coupled systems, and unforeseen circumstances of quadcopter UAVs systems. A comparative assessment through numerical simulations of sliding mode-based nonlinear observer approaches and Kalman filter is presented. These include quasi method, interval type-2 fuzzy logic system, super-twisting algorithm, higher order sliding mode observer, and extended Kalman filter. Chattering, noise rejection, estimation error and time required to track true states are evaluated to demonstrate the performance of each observer. In addition, to assess the proposed controller performance, maximum overshoot, rise time, chattering, and steady-state error are evaluated in relation to the use of each observer

Adaptive fuzzy sliding mode algorithm-based decentralised control for a permanent magnet spherical actuator

<p>The dynamic model of multi-degree-of-freedom permanent magnet (PM) spherical actuators is multivariate and nonlinear due to strong inter-axis couplings, which affects the trajectory tracking performance of the system. In this paper, a decentralised control strategy based on adaptive fuzzy sliding mode (AFSM) algorithm is developed for a PM spherical actuator to enhance its trajectory tracking performance. In this algorithm, the coupling terms are separated as subsystems from the entire system. The AFSM algorithm is applied in such a way that the fuzzy logic systems are used to approximate the subsystem with uncertainties. A sliding mode term is introduced to compensate for the effect of coupling terms and fuzzy approximation error. The stability of the proposed method is guaranteed by choosing the appropriate Lyapunov function. Both simulation and experimental results show that the proposed control algorithm can effectively handle various uncertainties and inter-axis couplings, and improve the trajectory tracking precision of the spherical actuator.</p

Application of modern control techniques in AC speed drive system.

In the past, Direct Current (dc) machines have been commonly favoured in areas where a precise variable speed operation is highly required. This is due to the feasible linear control of flux and torque, which is accomplished by simply varying the field and armature currents. However, they are bulky, expensive and require periodic maintenance due to the existence of commutators and brushes. Alternating Current (ac) machines particularly the squirrel cage induction type have emerged as an alternative to those of dc machines in the application of speed drive systems. In general, however, they do require more complex control schemes than the dc motors, because of their highly non-linear dynamic structure with strong dynamic interactions. This situation has changed dramatically over the last few years with the advent of fast switching power converters along with high performance micro-controllers, which made a significant contribution to performance enhancement of modem speed drive systems. In addition, various control techniques have made possible the application of induction motors in high performance speed drive operations where traditionally only dc motors were previously available. On the other hand, in many speed drive applications which incorporate either scalar or vector control, the prime objective of the speed controller is the capability of achieving a good speed tracking performance and without sensitivity to parameters and operating condition changes. For these reasons, comprehensive investigation of state-of-the-art modem control schemes, which include fuzzy logic and sliding mode control are discussed. The main principles underlying fuzzy logic and sliding mode control schemes along with their basic theory and general mathematical representation are reviewed. In addition, the application of fuzzy logic concepts to reduce the chattering phenomenon typically inherited in the sliding mode control is successfully presented, which results in a new integrated fuzzy sliding mode control algorithms. Through extensive simulation studies, it is found that the fuzzy logic control scheme attained a good transient performance for the speed drive system in comparison to the conventional sliding mode control and the new integrated fuzzy sliding mode control. Furthermore, the design simplicity of the fuzzy logic control system has made it virtually attractive for the ease of practical implementation of the proposed drive system. Extensive practical testes of the proposed variable speed drive system have been carried out to verify the validity of the simulation analysis of the proposed fuzzy logic control system. Several tests are conducted in order to bring out the effectiveness of the designed control system upon step change in speed command and impact load disturbances. The digital implementation of the proposed fuzzy logic control algorithms is realised on a single chip, Intel 80C196KC 16-bit embedded microcontroller, a low cost derivative of the MCS-96 architecture. The main contribution of this thesis is the novel approach to design a sliding mode control system using concepts from fuzzy logic algorithms to alleviate the chattering problems and improve the dynamics of the induction motor drive

Hybrid Control Using Adaptive Fuzzy Sliding Mode for Diagnosis of Stator Fault in PMSM

In nonlinear control systems when we have a non-constant parameters, conventional control laws may be insufficient because they are not robust especially when the requirement on accuracy and other characteristics dynamic systems are strict. We must use control laws insensitive against to parameter variations, disturbance and nonlinearities. For this purpose, several tools are proposed in the literature, which is quoted a hybrid fuzzy logic and variable structure control (Fl_VSC). This per presents an application of the fuzzy logic scheme to control the speed of PMSM by taking account of the presence of interturn short circuit fault. We were interested in the sliding mode control (SMC) of the PMSM using controller’s fuzzy logic controller (FLC) and Adaptive fuzzy logic controller (AFLC). The combination of these two theories has given great performance with fast dynamic response without overshoot. As it has a very robust control, insensitive against to parameters variation and external disturbances. Simulation results confirm the choice of hybrid controllers compared with the conventional controllers and grants a robust performance and precise response to the reference model regardless of load disturbance, stator faults and PMSM parameter uncertainties

Active fault-tolerant control of nonlinear systems with wind turbine application

The thesis concerns the theoretical development of Active Fault-Tolerant Control (AFTC) methods for nonlinear system via T-S multiple-modelling approach. The thesis adopted the estimation and compensation approach to AFTC within a tracking control framework. In this framework, the thesis considers several approaches to robust T-S fuzzy control and T-S fuzzy estimation: T-S fuzzy proportional multiple integral observer (PMIO); T-S fuzzy proportional-proportional integral observer (PPIO); T-S fuzzy virtual sensor (VS) based AFTC; T-S fuzzy Dynamic Output Feedback Control TSDOFC; T-S observer-based feedback control; Sliding Mode Control (SMC). The theoretical concepts have been applied to an offshore wind turbine (OWT) application study. The key developments that present in this thesis are:• The development of three active Fault Tolerant Tracking Control (FTTC) strategies for nonlinear systems described via T-S fuzzy inference modelling. The proposals combine the use of Linear Reference Model Fuzzy Control (LRMFC) with either the estimation and compensation concept or the control reconfiguration concept.• The development of T-S fuzzy observer-based state estimate fuzzy control strategy for nonlinear systems. The developed strategy has the capability to tolerate simultaneous actuator and sensor faults within tracking and regulating control framework. Additionally, a proposal to recover the Separation Principle has also been developed via the use of TSDOFC within the FTTC framework.• The proposals of two FTTC strategies based on the estimation and compensation concept for sustainable OWTs control. The proposals have introduced a significant attribute to the literature of sustainable OWTs control via (1) Obviating the need for Fault Detection and Diagnosis (FDD) unit, (2) Providing useful information to evaluate fault severity via the fault estimation signals.• The development of FTTC architecture for OWTs that combines the use of TSDOFC and a form of cascaded observers (cascaded analytical redundancy). This architecture is proposed in order to ensure the robustness of both the TSDOFC and the EWS estimator against the generator and rotor speed sensor faults.• A sliding mode baseline controller has been proposed within three FTTC strategies for sustainable OWTs control. The proposals utilise the inherent robustness of the SMC to tolerate some matched faults without the need for analytical redundancy. Following this, the combination of SMC and estimation and compensation framework proposed to ensure the close-loop system robustness to various faults.• Within the framework of the developed T-S fuzzy based FTTC strategies, a new perspective to reduce the T-S fuzzy control design conservatism problem has been proposed via the use of different control techniques that demand less design constraints. Moreover, within the SMC based FTTC, an investigation is given to demonstrate the SMC robustness against a wider than usual set of faults is enhanced via designing the sliding surface with minimum dimension of the feedback signals