Robust Anti-Swing Adaptive Fuzzy Tracking Control for Tower Crane Systems With Both Dead-Zone Band and Time-Delays Uncertainties

2015 ◽  
Author(s):  
Tzu Sung Wu ◽  
Mansour Karkoub
Keyword(s):  
Time Delays ◽  
Closed Loop ◽  
Dead Zone ◽  
Mechanical Systems ◽  
Control Technique ◽  
External Disturbances ◽  
Adaptive Fuzzy ◽  
Tower Crane ◽  
Control Scheme ◽  
Actuator Nonlinearities

Complex mechanical systems, such as tower cranes, are known to be highly nonlinear, under-actuated, and non-colocated, which makes their closed-loop control very challenging. The interconnected components of these systems undergo complex dynamic phenomena, such as friction, which lead to energy or momentum transmission delays. The complexity of such systems is further complicated by external disturbances and nonlinearities resulting from using hydraulic and/or electrical actuators, mechanical joints, gears, etc., which result in the formation of dead-zones, backlash, and hysteresis. A dead-zone, which constitutes a significant non-smooth nonlinearity, severely limits the performance of many mechanical systems such as the tower crane. Previous works on the control of tower cranes were based on accurate determination of their actuated states. In this work, a robust control technique based on adaptive fuzzy theory is investigated for anti-swing and trajectory tracking of tower crane systems. The system is subject to uncertainties in parameter parameters, time delays, external disturbances, and unknown actuator nonlinearities. The unknown actuator nonlinearities, from the jib and tower motors, are characterized by dead-zone bands (as opposed to the typical crisp dead-zone functions). First, fuzzy logic systems with on-line adaptations are utilized to evaluate the unknown nonlinear functions. The proposed control scheme uses the H∞ control technique to develop compensators to overcome the effects of parameter variations, time delays, external disturbances, and unknown actuator dead-zone band nonlinearities. The proposed control scheme ensures the stability of the closed-loop system and achieves desired tracking precision such that the states of the tower crane system are ultimately uniformly bounded (UUB) and guarantees an H∞ norm bound constraint on disturbance attenuation for all admissible uncertainties based on the Lyapunov criterion. Simulation results show the validity of this approach for the tower crane system.

H ∞ Based Adaptive Fuzzy Control of a Tower Crane System

2012 ◽  
Author(s):  
Mansour Karkoub ◽  
Tzu Sung Wu ◽  
Chien Ting Chen
Keyword(s):  
Fuzzy Control ◽  
Time Delays ◽  
Adaptive Fuzzy Control ◽  
Tracking Performance ◽  
Control Technique ◽  
Control Law ◽  
External Disturbances ◽  
Adaptive Fuzzy ◽  
Tower Crane ◽  
Highly Nonlinear

Tower cranes are very complex mechanical systems and have been the subject of research investigations for several decades. Research on tower cranes has focused on the development of dynamical models (linear and nonlinear) as well as control techniques to reduce the swaying of the payload. Inherently, the dynamical model of the tower crane is highly nonlinear and classified as under-actuated. The crane system has potentially six degrees of freedom but only three actuators. Also, the actuators are far from the payload which makes the system non-colocated. The dynamic model describing the motion of the payload from point to point is affected by uncertainties, time delays and external disturbances which may lead to inaccurate positioning, reduce safety and efficacy of the overall system. It is proposed here to use an H∞ based adaptive fuzzy control technique to control the swaying motion of a tower crane. This technique will overcome modeling inaccuracies, such as drag and friction losses, effect of time delayed disturbances, as well as parameter uncertainties. The proposed control law for payload positioning is based on indirect adaptive fuzzy control. A fuzzy model is used to approximate the dynamics of the tower crane; then, an indirect adaptive fuzzy scheme is developed for overriding the nonlinearities and time delays. The advantage of employing an adaptive fuzzy system is the use of linear analytical results instead of estimating nonlinear system functions with an online update law. The adaptive fuzzy scheme fuses a Variable Structure (VS) scheme to resolve the system uncertainties, and the external disturbances such that H∞ tracking performance is achieved. A control law is derived based on a Lyapunov criterion and the Riccati-inequality to compensate for the effect of the external disturbances on tracking error so that all states of the system are uniformly ultimately bounded (UUB). Therefore, the effect can be reduced to any prescribed level to achieve H∞ tracking performance. Simulations are presented here to illustrate the performance of the proposed control design.

Asymptotic tracking control scheme for mechanical systems with external disturbances and friction

2010 ◽  
Vol 73 (7-9) ◽  
pp. 1293-1302 ◽  
Author(s):  
Lili Cui ◽  
Huaguang Zhang ◽  
Bing Chen ◽  
Qingling Zhang
Keyword(s):  
Tracking Control ◽  
Mechanical Systems ◽  
External Disturbances ◽  
Control Scheme ◽  
Asymptotic Tracking

ADAPTIVE FUZZY CONTROL WITH OUTPUT FEEDBACK FOR H∞ TRACKING OF SISO NONLINEAR SYSTEMS

2008 ◽  
Vol 18 (04) ◽  
pp. 305-320 ◽  
Author(s):  
GERASIMOS G. RIGATOS
Keyword(s):  
Nonlinear Systems ◽  
Output Feedback ◽  
State Vector ◽  
Adaptive Fuzzy Control ◽  
External Disturbances ◽  
Adaptive Fuzzy ◽  
Neuro Fuzzy ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Motor Model

Observer-based adaptive fuzzy H∞ control is proposed to achieve H∞ tracking performance for a class of nonlinear systems, which are subject to model uncertainty and external disturbances and in which only a measurement of the output is available. The key ideas in the design of the proposed controller are (i) to transform the nonlinear control problem into a regulation problem through suitable output feedback, (ii) to design a state observer for the estimation of the non-measurable elements of the system's state vector, (iii) to design neuro-fuzzy approximators that receive as inputs the parameters of the reconstructed state vector and give as output an estimation of the system's unknown dynamics, (iv) to use an H∞ control term for the compensation of external disturbances and modelling errors, (v) to use Lyapunov stability analysis in order to find the learning law for the neuro-fuzzy approximators, and a supervisory control term for disturbance and modelling error rejection. The control scheme is tested in the cart-pole balancing problem and in a DC-motor model.

scholarly journals Robust Adaptive Fuzzy Control via State-Dependent Function for Nonlinear Stochastic Large-Scale Systems Subject to Dead Zones

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Chang-Qi Zhu ◽  
Lei Liu
Keyword(s):  
Fuzzy Control ◽  
Large Scale ◽  
Dead Zone ◽  
Adaptive Fuzzy Control ◽  
Closed Loop System ◽  
Large Scale Systems ◽  
Adaptive Fuzzy ◽  
State Dependent ◽  
Control Scheme ◽  
Robust Adaptive

This paper concentrates on the adaptive fuzzy control problem for stochastic nonlinear large-scale systems with constraints and unknown dead zones. By introducing the state-dependent function, the constrained closed-loop system is transformed into a brand-new system without constraints, which can realize the same control objective. Then, fuzzy logic systems (FLSs) are used to identify the unknown nonlinear functions, the dead zone inverse technique is utilized to compensate for the dead zone effect, and a robust adaptive fuzzy control scheme is developed under the backstepping frame. Based on the Lyapunov stability theory, it is proved ultimately that all signals in the closed-loop system are bounded and the tracking errors converge to a small neighborhood of the origin. Finally, an example based on an actual system is given to verify the effectiveness of the proposed control scheme.

scholarly journals An Adaptive Hierarchical Sliding Mode Controller for Autonomous Underwater Vehicles

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2316
Author(s):  
Quang Van Vu ◽  
Tuan Anh Dinh ◽  
Thien Van Nguyen ◽  
Hoang Viet Tran ◽  
Hai Xuan Le ◽  
...  
Keyword(s):  
Adaptive Learning ◽  
Autonomous Underwater Vehicle ◽  
Sliding Mode ◽  
Autonomous Underwater Vehicles ◽  
Lyapunov Theory ◽  
Control Technique ◽  
External Disturbances ◽  
Control Scheme ◽  
Hierarchical Sliding Mode ◽  
Over Time

The paper addresses a problem of efficiently controlling an autonomous underwater vehicle (AUV), where its typical underactuated model is considered. Due to critical uncertainties and nonlinearities in the system caused by unavoidable external disturbances such as ocean currents when it operates, it is paramount to robustly maintain motions of the vehicle over time as expected. Therefore, it is proposed to employ the hierarchical sliding mode control technique to design the closed-loop control scheme for the device. However, exactly determining parameters of the AUV control system is impractical since its nonlinearities and external disturbances can vary those parameters over time. Thus, it is proposed to exploit neural networks to develop an adaptive learning mechanism that allows the system to learn its parameters adaptively. More importantly, stability of the AUV system controlled by the proposed approach is theoretically proved to be guaranteed by the use of the Lyapunov theory. Effectiveness of the proposed control scheme was verified by the experiments implemented in a synthetic environment, where the obtained results are highly promising.

Robust adaptive fault tolerant attitude control for post-capture non-cooperative targets with actuator nonlinearities

2017 ◽  
Vol 40 (7) ◽  
pp. 2116-2128 ◽  
Author(s):  
Zheng Wang ◽  
Jianping Yuan ◽  
Yong Shi ◽  
Dejia Che
Keyword(s):  
Attitude Control ◽  
Control Structure ◽  
Control Method ◽  
Fault Tolerant ◽  
Dead Zone ◽  
Measurement Information ◽  
Attitude Stabilization ◽  
Control Scheme ◽  
Actuator Nonlinearities ◽  
Robust Adaptive

This paper develops an attitude takeover control structure for post-capture non-cooperative targets with actuator nonlinearities and faults. In this paper, the contingent actuator gain faults, deviation faults and the undesirable non-symmetric dead-zone nonlinearities of the actuator are all under consideration. An effective robust adaptive fault tolerant attitude control method is synthesized such that the actuator nonlinearities and faults can be well handled. As a result, the accurate attitude stabilization and tracking are maintained. Moreover, an extended fault tolerant attitude control scheme that can work well in the presence of inaccurate measurement information is proposed. Based on a quadratic Lyapunov function, the proof of the convergence is completed. Simulation results demonstrate the effectiveness and advantages of the proposed method.

Distributed finite-time tracking for multiple uncertain mechanical systems with dead-zone input and external disturbances

2019 ◽  
Vol 41 (15) ◽  
pp. 4450-4461 ◽  
Author(s):  
Jihong Jia ◽  
Xia Xie ◽  
Zhikai Zhang ◽  
Guangren Duan
Keyword(s):  
Finite Time ◽  
Dead Zone ◽  
Mechanical Systems ◽  
Small Neighborhood ◽  
Consensus Protocol ◽  
Tracking Errors ◽  
External Disturbances ◽  
Adding A Power Integrator ◽  
Adaptive Laws ◽  
Power Integrator

This paper addresses the distributed finite-time tracking problem for multiple uncertain mechanical systems with dead-zone input and external disturbances. An observer-based adaptive finite-time consensus protocol is designed, which consists of two steps. Firstly, distributed observers are developed such that all the mechanical systems can obtain the leader’s state in finite settling time. Then, based on backstepping method and adding a power integrator technique, the finite-time consensus protocol and appropriate adaptive laws are designed to track the estimated leader’s state. Rigorous proofs show that the tracking errors between each mechanical system and the leader can converge to a small neighborhood of origin in finite time despite the presence of dead-zone nonlinearity and external disturbances. Finally, simulation example is provided to demonstrate the effectiveness of the proposed scheme.

Increasing Robustness of Input Shaping Method to Parametric Uncertainties and Time-Delays

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
M. C. Pai ◽  
A. Sinha
Keyword(s):  
Time Delays ◽  
Closed Loop ◽  
Sliding Mode ◽  
Flexible Structures ◽  
System Stability ◽  
Flexible Structure ◽  
Input Shaping ◽  
Parametric Uncertainties ◽  
Residual Vibration ◽  
External Disturbances

The input shaping technique has proven to be highly effective in reducing or eliminating residual vibration of flexible structures. The exact elimination of the residual vibration via input shaping depends on the amplitudes and instants of utilized impulses. However, systems always have parametric uncertainties, which can lead to performance degradation. Furthermore, input shaping method does not deal with vibration excited by external disturbances and time-delays. In this paper, a closed-loop input shaping control scheme is developed for uncertain flexible structure and uncertain time-delay flexible structure systems. The algorithm is based on the sliding mode control and H∞/μ techniques. This scheme guarantees closed-loop system stability, and yields good performance and robustness in the presence of parametric uncertainties, time-delays and external disturbances as well. Also, it is shown that increasing the robustness to parametric uncertainties and time-delays does not lengthen the duration of the impulse sequence. Numerical examples are presented to verify the theoretical analysis.

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