Time-optimal control algorithm for two-time-scale discrete system

A linear, shift-invariant discrete system exhibiting two-time-scale (slow and fast) character is addressed. An iterative algorithm based on linear programming for the computation of time-optimal control is presented by decoupling the original system into slow and fast subsystems. It is found that the computation time and storage capacity for the computation of time-optimal control of the slow and fast subsystems is less than that required for the original system. A numerical example is provided to illustrate the proposed algorithm.     

力矩输入有界的柔性关节机器人轨迹跟踪控制

为解决柔性关节机器人在关节驱动力矩输出受限情况下的轨迹跟踪控制问题,提出一种基于奇异摄动理论的有界控制器.首先,利用奇异摄动理论将柔性关节机器人动力学模型解耦成快、慢两个子系统.然后,引入一类平滑饱和函数和径向基函数神经网络非线性逼近手段,依据反步策略设计了针对慢子系统的有界控制器.在快子系统的有界控制器设计中,通过关节弹性力矩跟踪误差的滤波处理加速系统的收敛.同时,在快、慢子系统控制器中均采用模糊逻辑实现控制参数的在线动态自调整.此外,结合李雅普诺夫稳定理论给出了严格的系统稳定性证明.最后,通过仿真对比实验验证了所提出控制方法的有效性和优越性.     

Robust ISS of uncertain discrete-time singularly perturbed systems with disturbances

This paper is concerned with robustly input-to-state stable (ISS) and Robust ISS by feedback of uncertain discrete-time singularly perturbed systems (SPSs) with disturbances. Meanwhile, robust stability and stabilisation of uncertain discrete-time SPSs are also obtained as the particular cases of robust ISS and robust ISS by feedback. We first find a sufficient condition by using the fixed-point principle in terms of linear matrix inequalities (LMIs) to guarantee that the considered system is always standard discrete-time SPSs subject to uncertainty and disturbances. Then, the full systems could decompose into the continuous-time uncertain slow subsystem with disturbance and discrete-time uncertain fast subsystems with disturbance, respectively. Based on the two-time-scale decomposition technique, sufficient condition in terms of LMIs is given such that the full systems are uniformly standard and robust ISS simultaneously. In addition, a state feedback controller is constructed by using the LMI approach such that the resulting closed-loop systems are robust ISS. Finally, a numerical example is provided to illustrate the effectiveness of the proposed approach.     

Adaptive composite suboptimal control for linear singularly perturbed systems with unknown slow dynamics

In this article, using singular perturbation theory and adaptive dynamic programming (ADP) approach, an adaptive composite suboptimal control method is proposed for linear singularly perturbed systems (SPSs) with unknown slow dynamics. First, the system is decomposed into fast‐ and slow‐subsystems and the original optimal control problem is reduced to two subproblems in different time‐scales. Afterward, the fast subproblem is solved based on the known model of the fast‐subsystem and a fast optimal control law is designed by solving the algebraic Riccati equation corresponding to the fast‐subsystem. Then, the slow subproblem is reformulated by introducing a system transformation for the slow‐subsystem. An online learning algorithm is proposed to design a slow optimal control law by using the information of the original system state in the framework of ADP. As a result, the obtained fast and slow optimal control laws constitute the adaptive composite suboptimal control law for the original SPSs. Furthermore, convergence of the learning algorithm, suboptimality of the adaptive composite suboptimal control law and stability of the whole closed‐loop system are analyzed by singular perturbation theory. Finally, a numerical example is given to show the feasibility and effectiveness of the proposed methods.     

单连杆柔性臂负载自适应模糊滑模控制

针对单连杆柔性臂，提出了负载自适应模糊滑模控制与最优控制相结合的混合控制方法。首先，采用奇异摄动将系统分为慢变和快变两个子系统。然后，对慢变子系统采用负载自适应模糊滑模控制，快变子系统采用最优控制。最后，仿真结果表明，该方法不仅能实现柔性臂轨迹的快速、准确跟踪，有效地抑制弹性振动，并且对负载的变化具有强的鲁棒性。     

Design of observer-based controllers for a class of discrete systems

Design of observers and observer-based controllers for linear, discrete control systems with fast and slow modes are considered in this paper. The time separation is expressed in terms of an inequality relating norms of system submatrices. It is shown that reconstruction of fast and slow states can be accomplished by a full-order observer, the gains of which are computed using a two-stage procedure. Then, provided that the fast subsystem is asymptotically stable, it is shown that a low-order observer-based controller can be designed with independent gain matrices to stabilize the original discrete system. The theoretical analysis is illustrated by a ninth-order boiler system model.     

Decentralized MRAC for large-scale interconnected systems with time-varying delays and applications to chemical reactor systems

The model reference adaptive control problem is investigated for a class of large-scale systems with time-varying delays. The considered systems have mismatched delay functions and matched interconnections. Firstly, a state coordinate transformation is employed to convert the original error system into a cascade system. Secondly, a delay-dependent virtual linear state feedback controller is developed to stabilize the first subsystem. Based on the virtual controller, a memoryless state feedback controller is constructed for the second subsystem. By choosing new Lyapunov Krasovskii functional, we show that the designed decentralized continuous adaptive controller renders that the solutions of the closed-loop system converge exponentially to a bounded region. Finally, the theoretic achievements are applied to the control design of a chemical reactor system with two subsystems. The control results show the effectiveness of the proposed method.     

基于模糊神经的柔性臂变负载控制方法

基于奇异摄动将单连杆柔性机械臂动力学模型分解为慢、快变子系统,传统方法分别采用PD控制和最优控制能取得较好控制效果,但负载不确定时,控制效果并不理想.提出对于慢变子系统,采用模糊神经、PD控制相结合的控制方法,对于快变子系统,采用模糊神经、最优控制相结合的控制方法.当负载变化时,采用模糊神经控制器根据实际负载对PD参数及最优控制参数进行调整,达到更优的控制效果.分别采用传统方法及本文提出的改进方法在变负载条件下作了仿真实验,结果表明后者的控制效果明显优于前者.给出了慢、快变子系统模糊神经控制器在变负载条件下训练参数的获取方法.     

基于神经网络与粒子滤波的柔性臂控制方法研究

基于奇异摄动法将单连杆柔性臂系统分解为慢变、快变子系统,采用混合控制方法;设计了基于粒子滤波的神经网络控制器来线性化慢子系统,使其跟踪期望轨迹;采用粒子滤波训练神经网络克服了BP算法收敛速度慢、易陷入局部极小值的缺陷,及扩展卡尔曼滤波方法带来的模型线性化损失;对于快变系统采用最优控制方法;仿真结果表明:在神经网络训练误差收敛速度及精度方面,粒子滤波要比BP及卡尔曼滤波要好;组合控制方法能有效地抑制柔性臂弹性振动,轨迹跟踪迅速准确,精度方面也是前者最优。     

基于奇异摄动的双连杆柔性臂模糊控制

讨论了双连杆柔性臂位置控制问题。应用拉格朗日-假设模态法建立系统的动力学方程，并用奇异摄动法将双连杆柔性臂系统分解为两个降阶的慢变子系统和快变子系统。针对柔性臂强非线性、强耦合性及不确定性等特点，给出一种慢变子系统在反馈线性化后采用模糊控制、快变子系统因呈线性系统而采用简单的最优控制的混合控制方法。其中，模糊控制是二维PD型控制器，其输入为关节角跟踪误差及其导数。最后进行了计算机仿真，结果表明，该方法不仅能实现柔性臂轨迹的快速、准确跟踪，有效的抑制弹性振动，并且对负载的变化具有强的鲁棒性。     

Adaptive Fault Tolerant Control of Multi-time-scale Singularly Perturbed Systems

This paper studies the fault tolerant control, adaptive approach, for linear time-invariant two-time-scale and three-time-scale singularly perturbed systems in presence of actuator faults and external disturbances. First, the full order system will be controlled using ε-dependent control law. The corresponding Lyapunov equation is ill-conditioned due to the presence of slow and fast phenomena. Secondly, a time-scale decomposition of the Lyapunov equation is carried out using singular perturbation method to avoid the numerical stiffness. A composite control law based on local controllers of the slow and fast subsystems is also used to make the control law ε-independent. The designed fault tolerant control guarantees the robust stability of the global closed-loop singularly perturbed system despite loss of effectiveness of actuators. The stability is proved based on the Lyapunov stability theory in the case where the singular perturbation parameter is sufficiently small. A numerical example is provided to illustrate the proposed method.     

Boundary Control for a Flexible Inverted Pendulum System Based on a PDE Model with Input Saturation

This research considers the control problem of a flexible inverted pendulum system (FIPS) in the presence of input saturation. The model for a flexible inverted pendulum system (FIPS) is derived via the Hamilton principle. The FIPS model is divided into a fast subsystem and a slow subsystem via the singular perturbation method. We introduce an auxiliary system to deal with the input saturation of a fast subsystem. To stabilize the fast subsystem, a boundary anti‐windup control force is applied at the free end of the beam. It is proven that the closed‐loop subsystem is stable. For the slow subsystem, a sliding mode control method is employed to design a controller and a new decoupling method to design the sliding surface. Then it is shown that the slow subsystem is stable. Finally, simulation results are provided to confirm the efficacy of the proposed controller.     

Robust decentralized eigenvalues clustering for multi-time-scale systems with perturbations

The formulation of the robust decentralized eigenvalues clustering with the design technique of the decentralized robust state feedback controller for multi-time-scale systems is facilitated. The multi-time-scale system, consisting of a slow subsystem and some fast subsystems with perturbations, is considered. From the eigenvalues locations of the multi-time-scale system, it is known that the locations of the fast subsystems are far from the slow subsystem ones. Furthermore, presented here are some sufficient conditions of robust eigenvalue clustering in specified regions for the uncertain slow subsystem and the uncertain fast subsystems with the parameter perturbations. An algorithm for the design of a decentralized robust state feedback controller for multitime-scale systems is then presented. It not only ensures that the eigenvalues of these subsystems are located in the desired regions, but also makes sure that all the eigenvalues of the whole system are in our desired regions. An illustrative example is adopted, and the result is satisfactory.     

Output feedback control of linear two-time-scale systems

Output feedback control of linear time-invariant singularly perturbed systems is studied. The set of all compensators that stabilize a singularly perturbed system while preserving its two-time-scale structure is parameterized. The parameterization is used to show that any two-frequency-scale stabilizing compensator can be asymptotically approximated by a compensator designed via a sequential procedure. In this procedure, a fast (high-frequency) compensator is designed first to stabilize the fast model of the system. Then, a strictly proper slow (low-frequency) compensator is designed to stabilize a modified slow model. The parallel connection of the two compensators forms a two-frequency-scale stabilizing compensator for the singularly perturbed system.     

Economic model predictive control of nonlinear singularly perturbed systems

We focus on the development of a Lyapunov-based economic model predictive control (LEMPC) method for nonlinear singularly perturbed systems in standard form arising naturally in the modeling of two-time-scale chemical processes. A composite control structure is proposed in which, a “fast” Lyapunov-based model predictive controller (LMPC) using a quadratic cost function which penalizes the deviation of the fast states from their equilibrium slow manifold and the corresponding manipulated inputs, is used to stabilize the fast dynamics while a two-mode “slow” LEMPC design is used on the slow subsystem that addresses economic considerations as well as desired closed-loop stability properties by utilizing an economic (typically non-quadratic) cost function in its formulation and possibly dictating a time-varying process operation. Through a multirate measurement sampling scheme, fast sampling of the fast state variables is used in the fast LMPC while slow-sampling of the slow state variables is used in the slow LEMPC. Appropriate stabilizability assumptions are made and suitable constraints are imposed on the proposed control scheme to guarantee the closed-loop stability and singular perturbation theory is used to analyze the closed-loop system. The proposed control method is demonstrated through a nonlinear chemical process example.     

Modeling and vibration control for a flexible pendulum inverted system based on a PDE observer

This study addresses the problem of trajectory control of a flexible pendulum inverted system on the basis of the partial differential equation (PDE) and ordinary differential equation (ODE) dynamic model. One of the key contributions of this study is that a new model is proposed to simplify the complex system. In addition, this study proposed a nonlinear PDE observer to estimate distributed positions and velocities along flexible pendulum. Singular perturbation method is proposed to solve the coupling system of nonlinear PDE observer. The nonlinear PDE observer is divided into a fast subsystem and a slow subsystem by the use of the singular perturbation method. To stabilise this fast subsystem, a boundary controller is proposed at the free end of the beam. The sliding-mode control method is proposed to design controller for slow subsystems. The asymptotic stability of both the proposed nonlinear PDE observer and controller is validated by theoretical analysis. The results are illustrated by simulation.     

Feedback control of two-time-scale block implemented discrete-time systems

The block processing technique is applied to a class of two-time-scale linear discrete-time systems. Block state-space structures for slow and fast subsystems have been obtained. Based upon these models, blocked slow and fast controls are designed. In addition, an extra control is designed to exactly compensate for the effects of the parasitics.     

Decentralized overlapping control of a formation of unmanned aerial vehicles

Decentralized overlapping feedback laws are designed for a formation of unmanned aerial vehicles. The dynamic model of the formation with an information structure constraint in which each vehicle, except the leader, only detects the vehicle directly in front of it, is treated as an interconnected system with overlapping subsystems. Using the mathematical framework of the inclusion principle, the interconnected system is expanded into a higher dimensional space in which the subsystems appear to be disjoint. Then, at each subsystem, a static state feedback controller is designed to robustly stabilize the perturbed nominal dynamics of the subsystem. The design procedure is based on the application of convex optimization tools involving linear matrix inequalities. As a final step, the decentralized controllers are contracted back to the original interconnected system for implementation.     

H2/H∞ Control of discrete singularly perturbed systems: the state feedback case

The design of a mixed H₂/H_∞ linear state variable feedback suboptimal controller for a discrete-time singularly perturbed system using reduced order slow and fast subsystems is described. It is shown that the designed controller based on reduced order models and the corresponding performance index both are O(ε) close to those synthesized using the full order system.     

Pair-wise decomposition and coordinated control of complex systems

Pair-wise decomposition and coordinated control for complex interconnected systems with any information structure constraints are proposed in this paper. Based on the inclusion principle, a permuted inclusion principle is presented to expand the system into an expanded space, from which a recurrent reverse order of pair-wise subsystems is extracted. By a standard LQ control, pair-wise controllers can be designed to stabilize and coordinate the pair-wise subsystems. According to these controllers, a coordinated compensator of subsystem interconnections is introduced in order to obtain a coordination-based controller for the expanded system. Therefore, a coordinated controller of the system can be contracted from the expanded space under the conditions of the inclusion principle. Moreover, a sufficient condition of connective stability for the system is also proved by the Lyapunov function and M-matrix. A main advantage of the proposed decomposition and control is that it allows any variation of information structure constraints of the system, especially the increase and decrease of subsystem numbers. Finally, the effectiveness of the proposed methodology is demonstrated by an application of automatic generation control to a four-area electric power system.