Payload Pendulation Reduction Using a Variable-Geometry-Truss Architecture with LQR and Fuzzy Controls

2003 ◽  
Vol 9 (7) ◽  
pp. 805-837 ◽  
Author(s):  
Paolo Dadone ◽  
Walter Lacarbonara ◽  
Ali H. Nayfeh ◽  
Hugh F. Vanlandingham
Keyword(s):  
Control Point ◽  
Broad Band ◽  
Ship Motions ◽  
Control Input ◽  
Variable Geometry ◽  
Linear Quadratic ◽  
Control Laws ◽  
Band Frequency ◽  
Input Acceleration ◽  
Variable Geometry Truss

We investigate the feasibility of a variable-geometry truss (VGT) based architecture for suppressing payload pendulations in ship-mounted cranes. The VGT assembly is conceived to be retrofitted onto the boom tip of ship-mounted cranes. A simplified planar model is developed. A control point along the cable hoisting the payload is constrained to move along a straight path with a given control input (acceleration) imparted via the actuators embedded in the VGT assembly. Control laws based on either linear quadratic or fuzzy control methodologies are developed in order to minimize an assigned cost functional. Their effectiveness is compared through extensive numerical simulations. The performance of the VGT architecture and associated control laws is analyzed when the crane is subject to the most severe combination of resonant excitations: a primary resonant roll excitation at the natural frequency of the controlled system, and a principal-parametric resonant heave excitation, both corresponding to sea state three and higher. The proposed strategy exhibits enough control authority over the system dynamics, greatly reducing the severe and undesirable resonant pendulations caused by the ship motions in a broad-band frequency range. Moreover, its disturbance-rejection capabilities are exerted with feasible control efforts, which are localized in the segment of the crane where they are needed.

Active control of transonic buffet flow

2017 ◽  
Vol 824 ◽  
pp. 312-351 ◽  
Author(s):  
Chuanqiang Gao ◽  
Weiwei Zhang ◽  
Jiaqing Kou ◽  
Yilang Liu ◽  
Zhengyin Ye
Keyword(s):  
Feedback Control ◽  
Design Flow ◽  
Complex Conjugate ◽  
Control Input ◽  
Input Output ◽  
Linear Quadratic ◽  
Unstable Flow ◽  
Control Laws ◽  
Loop Control ◽  
Transonic Buffet

Transonic buffet is a phenomenon of aerodynamic instability with shock wave motions which occurs at certain combinations of Mach number and mean angle of attack, and which limits the aircraft flight envelope. The objective of this study is to develop a modelling method for unstable flow with oscillating shock waves and moving boundaries, and to perform model-based feedback control of the two-dimensional buffet flow by means of trailing-edge flap oscillations. System identification based on the ARX algorithm is first used to derive a linear model of the input–output dynamics between the flap rotation (the control input) and the lift and pitching moment coefficients (system outputs). The model features a pair of unstable complex-conjugate poles at the characteristic buffet frequency. An appropriate reduced-order model (ROM) with a lower dimension is further obtained by a balanced truncation method that keeps the pair of unstable poles in the unstable subspace but truncates the dynamics in the stable subspace. Based on this balanced ROM, two kinds of feedback control are designed by pole assignment and linear quadratic methods respectively. These independent designs, however, result in similar suboptimal static output feedback control laws. When introduced in numerical simulations, they are both able to completely suppress the buffet instability. Furthermore, the resulting controllers are even able to stabilize buffet flows with nonlinear disturbances and in off-design flow conditions, thus implying their robustness. The analysis of the feedback control laws indicates that parameters (frequency and phase) corresponding to the ‘anti-resonance’ of the linear input–output model are vital for optimal control. The best performance is obtained when the control operates close to the ‘anti-resonance’, which is supported by the optimal frequency and the phase of the open-loop control as well as by the optimal phase of the closed-loop control.

Design of Finite Time Settling Regulators for Linear Systems

1994 ◽  
Vol 116 (4) ◽  
pp. 602-609 ◽  
Author(s):  
Slim Choura
Keyword(s):  
Finite Time ◽  
Feedforward Control ◽  
Linear Quadratic Regulator ◽  
Control Law ◽  
Control Input ◽  
Linear Quadratic ◽  
Control Laws ◽  
Performance Specifications ◽  
The Time Domain ◽  
State Responses

Earlier development of finite time settling controllers focused on the structure of the control law which consists of feedback and feedforward parts. In this structure, the feedback part is designed separately to satisfy certain performance specifications in the frequency and/or the time domain. The feedforward part is determined from the feedback control law, and therefore, there exists one-way coupling of both parts. In this paper, we propose a modification in the control structure that enables the designer to regulate the bounds of the control input and the state responses. We show that the finite time settling control problem can be transformed into a linear quadratic regulator one. This transformation results in a two-way coupling of the feedback and the feedforward control laws. We verify that the robustness property of the control strategy is preserved despite its structural change. In addition, we give guidelines for the selection of the feedforward control law.

A Unified Approach to the Design of Adaptive and Repetitive Controllers for Robotic Manipulators

1990 ◽  
Vol 112 (4) ◽  
pp. 618-629 ◽  
Author(s):  
Nader Sadegh ◽  
Roberto Horowitz ◽  
Wei-Wen Kao ◽  
Masayoshi Tomizuka
Keyword(s):  
Lyapunov Theory ◽  
Control Input ◽  
Robot Arm ◽  
Unified Approach ◽  
Parameter Adaptation ◽  
Control Laws ◽  
Position Errors ◽  
Adaptive Compensator ◽  
Mechanical Manipulators ◽  
Repetitive Controller

A unified approach, based on Lyapunov theory, for synthesis and stability analysis of adaptive and repetitive controllers for mechanical manipulators is presented. This approach utilizes the passivity properties of the manipulator dynamics to derive control laws which guarantee asymptotic trajectory following, without requiring exact knowledge of the manipulator dynamic parameters. The manipulator overall controller consists of a fixed PD action and an adaptive and/or repetitive action for feed-forward compensations. The nonlinear feedforward compensation is adjusted utilizing a linear combination of the tracking velocity and position errors. The repetitive compensator is recommended for tasks in which the desired trajectory is periodic. The repetitive control input is adjusted periodically without requiring knowledge of the explicit structure of the manipulator model. The adaptive compensator, on the other hand, may be used for more general trajectories. However, explicit information regarding the dynamic model structure is required in the parameter adaptation. For discrete time implementations, a hybrid version of the repetitive controller is derived and its global stability is proven. A simulation study is conducted to evaluate the performance of the repetitive controller, and its hybrid version. The hybrid repetitive controller is also implemented in the Berkeley/NSK SCARA type robot arm.

Model-Independent Control of a Flexible-Joint Robot Manipulator

2009 ◽  
Vol 131 (4) ◽  
Author(s):  
Withit Chatlatanagulchai ◽  
Peter H. Meckl
Keyword(s):  
Neural Networks ◽  
Open Problem ◽  
High Performance ◽  
Robot Manipulator ◽  
Intrinsic Property ◽  
Variable Structure ◽  
System Model ◽  
Control Input ◽  
Control Laws ◽  
Flexible Joint

Flexibility at the joint of a manipulator is an intrinsic property. Even “rigid-joint” robots, in fact, possess a certain amount of flexibility. Previous experiments confirmed that joint flexibility should be explicitly included in the model when designing a high-performance controller for a manipulator because the flexibility, if not dealt with, can excite system natural frequencies and cause severe damage. However, control design for a flexible-joint robot manipulator is still an open problem. Besides being described by a complicated system model for which the passivity property does not hold, the manipulator is also underactuated, that is, the control input does not drive the link directly, but through the flexible dynamics. Our work offers another possible solution to this open problem. We use three-layer neural networks to represent the system model. Their weights are adapted in real time and from scratch, which means we do not need the mathematical model of the robot in our control algorithm. All uncertainties are handled by variable-structure control. Backstepping structure allows input efforts to be applied to each subsystem where they are needed. Control laws to adjust all adjustable parameters are devised using Lyapunov’s second method to ensure that error trajectories are globally uniformly ultimately bounded. We present two state-feedback schemes: first, when neural networks are used to represent the unknown plant, and second, when neural networks are used to represent the unknown parts of the control laws. In the former case, we also design an observer to enable us to design a control law using only output signals—the link positions. We use simulations to compare our algorithms with some other well-known techniques. We use experiments to demonstrate the practicality of our algorithms.

Analytical Model Method for Dynamics of N-Celled Tetrahedron-Tetrahedron Variable Geometry Truss Manipulators

1998 ◽  
Author(s):  
Li Ju Xu ◽  
Hong Li ◽  
Shou Wen Fan
Keyword(s):  
Analytical Model ◽  
Variable Geometry ◽  
Symbolic Form ◽  
Model Method ◽  
Variable Geometry Truss Manipulator ◽  
Variable Geometry Truss

Abstract In this paper some fundamental formulae are derived for tetrahedron-based variable geometry truss manipulator which is composed of a series of tetrahedrons stacked upon each other such that one link in each cell is made variable on length. Analytical model for dynamics of the manipulator is established, and expressions in numeric-symbolic form of model matrices are derived. An example is given for illustration.

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