Integrating Structure and Controller Design to Mechanical Systems via Decentralized Control Techniques

2015 ◽  
Author(s):  
Yilun Liu ◽  
Lei Zuo
Keyword(s):  
Mechanical System ◽  
Decentralized Control ◽  
Output Feedback ◽  
Optimization Problem ◽  
Passive Control ◽  
Design Method ◽  
Lagrange Function ◽  
Integrated Design ◽  
Feedback Controller ◽  
Control Techniques

The overall performance of the mechanical system can be significantly improved by concurrently optimizing the plant and the controller. This paper proposes a new integrated design method via decentralized control techniques to concurrently optimize the structure and the controller, which aims at minimizing the system H2 norm from the disturbance to the system cost. The integrated design problems have been formulated in the cases of a full state feedback controller and a full order output feedback controller respectively. Inspired by noticing that the control techniques are capable of optimizing both the parameters of passive springs and dampers and the controller for the mechanical system, we extend the current LTI control system to a more general framework suitable for the integrated design needs, where the structure design is treated as the passive control optimization tackled by decentralized control techniques with static output feedback, while the active controller is optimized by solving the modified Riccati equations. With the extended system framework, we transfer the original non-convex integrated optimization problem to an unconstrained optimization problem by introducing Lagrange multipliers and a Lagrange function. The gradient-based optimization method is employed to effectively find the optimality solution of the integrated design. Two design examples including an active-passive vehicle suspension system and an active-passive Tuned Mass Damper (TMD) system are designed by the proposed integrated design method. The improvement of the overall system performance due to the integrated design is also presented in comparison with the conventional design methods.

A Computation-Efficient Framework for the Integrated Design of Structural and Control Systems

2016 ◽  
Vol 138 (9) ◽  
Author(s):  
Yilun Liu ◽  
Lei Zuo
Keyword(s):  
Control System ◽  
Decentralized Control ◽  
Output Feedback ◽  
Structural Design ◽  
Design Problem ◽  
Design Method ◽  
Integrated Design ◽  
Design Parameters ◽  
Feedback Controllers ◽  
Control Techniques

This paper proposes a new integrated design method to simultaneously optimize the coupled structural parameters and controllers of mechanical systems by combining decentralized control techniques and Riccati-based control theories. The proposed integrated design method aims at minimizing the closed-loop H2 norm from the disturbance to the system cost. In this paper, the integrated design problems have been formulated in the cases of full state-feedback controllers and full order output-feedback controllers. We extend the current linear time invariant (LTI) control system to a more general framework suitable for the needs of integrated design, where the structural design is treated as a passive control optimization tackled by decentralized control techniques with static output feedback, while the active controller is optimized by solving modified Riccati equations. By using this dual-loop control system framework, the original integrated design problem is transferred to a constrained structural design problem with some additional Riccati-equation based constraints simultaneously integrating the controller synthesis. This reduces the independent design variables from the structural design parameters and the parameters of the controller to the structural design parameters only. As a result, the optimization efficiency is significantly improved. Then the constrained structural design problem is reformed as an unconstrained optimization problem by introducing Lagrange multipliers and a Lagrange function. The corresponding optimal conditions for the integrated design are also derived, which can be efficiently solved by gradient-based optimization algorithms. Later, two design examples, an active–passive vehicle suspension system and an active–passive tuned mass damper (TMD) system, are presented. The improvement of the overall system performance is also presented in comparison with conventional design methods.

Dynamic output feedback control for nonlinear large-scale interconnected systems

2020 ◽  
Vol 39 (4) ◽  
pp. 801-821
Author(s):  
Ezzeddine Touti ◽  
Ali Sghaier Tlili ◽  
Muhannad Almutiry
Keyword(s):  
Decentralized Control ◽  
Output Feedback ◽  
Large Scale ◽  
Optimization Problem ◽  
Lyapunov Theory ◽  
Interconnected Systems ◽  
Dynamic Output Feedback ◽  
Content Type ◽  
Dynamic Output ◽  
Control Scheme

Purpose This paper aims to focus on the design of a decentralized observation and control method for a class of large-scale systems characterized by nonlinear interconnected functions that are assumed to be uncertain but quadratically bounded. Design/methodology/approach Sufficient conditions, under which the designed control scheme can achieve the asymptotic stabilization of the augmented system, are developed within the Lyapunov theory in the framework of linear matrix inequalities (LMIs). Findings The derived LMIs are formulated under the form of an optimization problem whose resolution allows the concurrent computation of the decentralized control and observation gains and the maximization of the nonlinearity coverage tolerated by the system without becoming unstable. The reliable performances of the designed control scheme, compared to a distinguished decentralized guaranteed cost control strategy issued from the literature, are demonstrated by numerical simulations on an extensive application of a three-generator infinite bus power system. Originality/value The developed optimization problem subject to LMI constraints is efficiently solved by a one-step procedure to analyze the asymptotic stability and to synthesize all the control and observation parameters. Therefore, such a procedure enables to cope with the conservatism and suboptimal solutions procreated by optimization problems based on iterative algorithms with multi-step procedures usually used in the problem of dynamic output feedback decentralized control of nonlinear interconnected systems.

scholarly journals Output feedback controller design for polynomial linear parameter varying system via parameter-dependent Lyapunov functions

2017 ◽  
Vol 9 (2) ◽  
pp. 168781401769032 ◽  
Author(s):  
Xiaobao Han ◽  
Zhenbao Liu ◽  
Huacong Li ◽  
Xianwei Liu
Keyword(s):  
Output Feedback ◽  
Optimization Problem ◽  
Controller Design ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Output Feedback Controller ◽  
Parameter Varying ◽  
Parameter Dependent

This article presents a new output feedback controller design method for polynomial linear parameter varying model with bounded parameter variation rate. Based on parameter-dependent Lyapunov function, the polynomial linear parameter varying system controller design is formulated into an optimization problem constrained by parameterized linear matrix inequalities. To solve this problem, first, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameter-dependent Lyapunov function, controller, and object coefficient matrices. Then, the control solving problem was reduced to a normal convex optimization problem with linear matrix inequalities constraint on a newly constructed convex polyhedron. Moreover, a parameter scheduling output feedback controller was achieved on the operating condition, which satisfies robust performance and dynamic performances. Finally, the feasibility and validity of the controller analysis and synthesis method are verified by the numerical simulation.

scholarly journals Stability of a Class of Stochastic Nonlinear Systems with Markovian Switching

2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Xiaohua Liu ◽  
Wuquan Li
Keyword(s):  
Nonlinear Systems ◽  
Output Feedback ◽  
Closed Loop ◽  
Design Method ◽  
Feedback Controller ◽  
Markovian Switching ◽  
Stochastic Nonlinear Systems ◽  
Closed Loop System ◽  
Output Feedback Controller ◽  
The Stability

This paper investigates the stability of a class of stochastic nonlinear systems with Markovian switching via output-feedback. Based on the backstepping design method and homogeneous domination technique, an output-feedback controller is constructed to guarantee that the closed-loop system has a unique solution and is almost surely asymptotically stable. The efficiency of the output-feedback controller is demonstrated by a simulation example.

scholarly journals Dynamic Output Feedback Robust MPC with Input Saturation Based on Zonotopic Set-Membership Estimation

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Xubin Ping ◽  
Bo Qian ◽  
Ning Sun
Keyword(s):  
Output Feedback ◽  
Optimization Problem ◽  
Input Saturation ◽  
Feedback Controller ◽  
Dynamic Output Feedback ◽  
Output Feedback Controller ◽  
Dynamic Output ◽  
Set Membership ◽  
Dynamic Output Feedback Controller ◽  
Bounded Disturbance

For quasi-linear parameter varying (quasi-LPV) systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC) with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The consideration of input saturation in the main optimization problem reduces the conservatism of dynamic output feedback controller design. The estimation error set and bounded disturbance are represented by zonotopes and refreshed by zonotopic set-membership estimation. Compared with the previous results, the proposed algorithm can not only guarantee the recursive feasibility of the optimization problem, but also improve the control performance at the cost of higher computational burden. A nonlinear continuous stirred tank reactor (CSTR) example is given to illustrate the effectiveness of the approach.

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