Adaptive Hybrid Intelligent Tracking Control for Uncertain Fractional Order Chaotic Systems

2012 ◽  
Vol 1 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Tsung-Chih Lin ◽  
Chia-Hao Kuo
Keyword(s):  
Fractional Order ◽  
Chaotic Systems ◽  
Fuzzy Controller ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Weighting Factor ◽  
Control Effort ◽  
Plant Knowledge ◽  
Control Knowledge ◽  
And Control

This paper presents an adaptive hybrid fuzzy controller to achieve prescribed tracking performance of fractional order chaotic systems. Depending on plant knowledge and control knowledge, a weighting factor can be adjusted by combining the indirect adaptive fuzzy control effort and the direct fuzzy adaptive control effort. Nonlinear fractional order chaotic response system is fully demonstrated to track the trajectory generated from fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control scheme is more flexible during the design process.

scholarly journals Uncertain Fractional Order Chaotic Systems Tracking Design via Adaptive Hybrid Fuzzy Sliding Mode Control

2011 ◽  
Vol 6 (3) ◽  
pp. 418 ◽  
Author(s):  
Tsung-Chih Lin ◽  
Chia-Hao Kuo ◽  
Valentina E. Balas
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Chaotic Systems ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy ◽  
Mode Control ◽  
And Control

In this paper, in order to achieve tracking performance of uncertain fractional order chaotic systems an adaptive hybrid fuzzy controller is proposed. During the design procedure, a hybrid learning algorithm combining sliding mode control and Lyapunov stability criterion is adopted to tune the free parameters on line by output feedback control law and adaptive law. A weighting factor, which can be adjusted by the trade-off between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive fuzzy controller and direct adaptive fuzzy controller. To confirm effectiveness of the proposed control scheme, the fractional order chaotic response system is fully illustrated to track the trajectory generated from the fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control structure is more flexible during the design process.

DIRECT ADAPTIVE TYPE-2 FUZZY CONTROL FOR NONLINEAR SYSTEMS

2006 ◽  
Vol 06 (03) ◽  
pp. 389-411 ◽  
Author(s):  
KHEIREDDINE CHAFAA ◽  
LAMIR SAIDI ◽  
MOUNA GHANAI ◽  
KHIER BENMAHAMMED
Keyword(s):  
Fuzzy Controller ◽  
Tracking Error ◽  
Nonlinear Dynamical System ◽  
Reference Trajectory ◽  
Oscillation System ◽  
Control Effort ◽  
Nonlinear Dynamical ◽  
Supervisory Controller ◽  
And Control

A new direct adaptive type-2 fuzzy controller for a nonlinear dynamical system is developed in this paper. The parameters of the membership functions characterizing the linguistic terms in the type-2 fuzzy IF–THEN rules change according to some adaptive law for the purpose of controlling a plant to track a reference trajectory. A supervisory controller is appended to the type-2 fuzzy controller to force the state to be within the constraint set. Stability of this adaptive scheme is established using Lyapunov stability tools, where we guarantee the global stability of the resulting closed-loop system, in the sense that all signals involved are uniformly bounded. The simulation results for a Duffing forced-oscillation system show better performances, i.e. tracking error and control effort can be made smaller.

scholarly journals Fractional-Order PII1/2DD1/2 Control: Theoretical Aspects and Application to a Mechatronic Axis

2021 ◽  
Vol 11 (8) ◽  
pp. 3631
Author(s):  
Luca Bruzzone ◽  
Mario Baggetta ◽  
Pietro Fanghella
Keyword(s):  
Fractional Order ◽  
Position Control ◽  
Tracking Error ◽  
Experimental Tests ◽  
Maximum Torque ◽  
Control Effort ◽  
Tuning Method ◽  
Alternative Approach ◽  
Remarkable Reduction ◽  
Distributed Order

Fractional Calculus is usually applied to control systems by means of the well-known PIlDm scheme, which adopts integral and derivative components of non-integer orders λ and µ. An alternative approach is to add equally distributed fractional-order terms to the PID scheme instead of replacing the integer-order terms (Distributed Order PID, DOPID). This work analyzes the properties of the DOPID scheme with five terms, that is the PII1/2DD1/2 (the half-integral and the half-derivative components are added to the classical PID). The frequency domain responses of the PID, PIlDm and PII1/2DD1/2 controllers are compared, then stability features of the PII1/2DD1/2 controller are discussed. A Bode plot-based tuning method for the PII1/2DD1/2 controller is proposed and then applied to the position control of a mechatronic axis. The closed-loop behaviours of PID and PII1/2DD1/2 are compared by simulation and by experimental tests. The results show that the PII1/2DD1/2 scheme with the proposed tuning criterium allows remarkable reduction in the position error with respect to the PID, with a similar control effort and maximum torque. For the considered mechatronic axis and trapezoidal speed law, the reduction in maximum tracking error is −71% and the reduction in mean tracking error is −77%, in correspondence to a limited increase in maximum torque (+5%) and in control effort (+4%).

scholarly journals SECURE COMMUNICATION USING THE SYNCHRONIZATION OF TWO FRACTIONAL-ORDER CHAOTIC SYSTEMS WITH ORDER CHANGES USING THE FINITE-TIME OPTIMAL CONTROL APPROACH

2021 ◽  
Vol 16 (10) ◽  
Author(s):  
Ali Soleimanizadeh
Keyword(s):  
Fractional Order ◽  
Secure Communication ◽  
Chaotic Systems ◽  
Control Approach ◽  
Synchronization Problem ◽  
Control Signals ◽  
Two Factors ◽  
Time Optimal ◽  
And Control ◽  
Optimal Control Approach

In this paper synchronization problem for two different fractional-order chaotic systems has been investigated. Based on fractional calculus, optimality conditions for this synchronization have been achieved. Synchronization Time and control signals are two factors that are optimized. After that, the synchronization method is applied in secure communication. Finally using the simulation example, the performance of the proposed method for synchronization and chaotic masking is shown.

Adaptive Fuzzy Control for a SISO Nonlinear System

2003 ◽  
Vol 7 (2) ◽  
pp. 86-91
Author(s):  
Hugang Han ◽  
◽  
Shuta Murakami ◽  
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Systems ◽  
Fuzzy Controller ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Switching Function ◽  
Adaptive Fuzzy ◽  
Synthesis Approach ◽  
Unknown Case

When using the Lyapunov synthesis approach to construct an adaptive fuzzy control system, one important way is to regard the fuzzy systems as approximators to approximate the unknown functions in the system to be controlled. Concerning the unknownness, generally there are two cases: a completely unknown case, and a partly unknown case. However, most of the schemes presented so far have only focused on the former. Clearly, if an unknown function belongs to the latter, the knowledge available about the function should be utilized as much as possible in the development of the control system. In this paper, our goal is to design an adaptive fuzzy controller for a class of nonlinear systems with uncertainty, which can correspond to the either case. Also, we propose a unique way to deal with the uncertainty, i.e., adopt a switching function with an alterable coefficient, which is tuned by adaptive law based on the tracking error.

Path tracking control of electromechanical micro-positioner by considering control effort of the system

2020 ◽  
pp. 095965182095327
Author(s):  
Mohammad Reza Gharib ◽  
Ali Koochi ◽  
Mojtaba Ghorbani
Keyword(s):  
Tracking Control ◽  
Tracking Error ◽  
Path Tracking ◽  
Lumped Parameter Model ◽  
Proportional Integral Derivative ◽  
Control Effort ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Micro Actuators ◽  
And Control

Position controlling with less overshoot and control effort is a fundamental issue in the design and application of micro-actuators such as micro-positioner. Also, tracking a considered path is very crucial for some particular applications of micro-actuators such as surgeon robots. Herein, a proportional–integral–derivative controller is designed using a feedback linearization technique for path tracking control of a cantilever electromechanical micro-positioner. The micro-positioner is simulated based on a 1-degree-of-freedom lumped-parameter model. Three different paths are considered, and the capability of the designed controller on the path tracking with lower error and control effort is investigated. The obtained results demonstrate the efficiency of the designed proportional–integral–derivative controller not only for reducing the tracking error but also for decreasing the control effort.

Design of Adaptive Fuzzy Control for a Class of Networked Nonlinear Systems

2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Mohamed Hamdy ◽  
Sameh Abd-Elhaleem ◽  
M. A. Fkirin
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
External Disturbance ◽  
Tracking Error ◽  
Adaptive Fuzzy Control ◽  
Time Varying ◽  
Fuzzy Logic Systems ◽  
Packet Losses ◽  
Adaptive Fuzzy Controller ◽  
Adaptive Fuzzy

This paper presents an adaptive fuzzy controller for a class of unknown nonlinear systems over network. The network-induced delays can degrade the performance of the networked control systems (NCSs) and also can destabilize the system. Moreover, the seriousness of the delay problem is aggravated when packet losses occur during a transmission of data. The proposed controller uses a filtered tracking error to cope the time-varying network-induced delays. It is also robust enough to cope some packet losses in the system. Fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear functions that appear in the tracking controller. Based on Lyapunov stability theory, the constructed controller is proved to be asymptotically stable. Stability of the adaptive fuzzy controller is guaranteed in the presence of bounded external disturbance, time-varying delays, and data packet dropouts. Simulated application of the inverted pendulum tracking illustrates the effectiveness of the proposed technique with comparative results.

Design of Fractional Order Fuzzy Controller Based on Sliding Mode Control for Robotic Flexible Joint Manipulators

2011 ◽  
Vol 109 ◽  
pp. 323-332 ◽  
Author(s):  
Ali Fayazi ◽  
Amir Hossein Hadjahmadi
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Tracking Error ◽  
Robotic Manipulators ◽  
Sliding Mode Controller ◽  
Level Control ◽  
Mode Control ◽  
Fractional Control

In this paper, a new design approach that combines the advantages in terms of robustness of the fractional control, the fuzzy scheme and the Sliding Mode Control (SMC) is proposed for robotic manipulators. A fractional order fuzzy sliding-mode controller (FOFSMC) can drive system tracking error to converge to zero in finite time. The FOFSMC is applied to a level control in robotic manipulators. Performance of the proposed controller evaluated to compare the performance with respect the conventional sliding mode controller. The simulation results demonstrate that the FOFSMC can provide a reasonable tracking performance.

Fuzzy Multivariable Control Strategy Applied to a Refrigeration System

2016 ◽  
Vol 12 (2) ◽  
Author(s):  
Saulo Fernando dos Santos Vidal ◽  
Jones Erni Schmitz ◽  
Ivan Carlos Franco ◽  
Ana Maria Frattini Fileti ◽  
Flavio Vasconcelos Da Silva
Keyword(s):  
Energy Consumption ◽  
Fuzzy Controller ◽  
Fine Tuning ◽  
Refrigeration System ◽  
Process Variables ◽  
Pump Frequency ◽  
Comparative Performance ◽  
Control Effort ◽  
Squared Error ◽  
And Control

Abstract The refrigeration process involves complex systems exhibiting nonlinearities and coupled behavior, so this paper aims to evaluate the comparative performance of a multivariable fuzzy logic-based control system and a classic multi loop PID. The process variables were the temperature of the secondary fluid (propylene glycol) outlet and the evaporating temperature. The manipulated variables were the compressor frequency speed and the pump frequency speed. Aspen Plus and Aspen Dynamics simulators were used to simulate the experimental prototype. The model was previously validated and linked with MATLAB software, where the controllers were implemented. Tuning of the fuzzy controller was performed through the membership functions and gains adjustments. The tuning of the multi loop PID controller was performed using the Ziegler-Nichols method and then a fine tuning was carried out. In order to fairly compare energy consumption and control effort, the tune of PID-based strategy was finished when similar values of Integral of Squared Error were achieved. Thus, very similar behavior for the process variables in both controllers. On the other hand, a great improvement in the control effort and energy saving was observed when the multivariable fuzzy controller was used in comparison to classic PID. The energy consumption was reduced by 25 % and the control effort by 96 % when the proposed strategy was used.

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