一种基于输出反馈的显式实时优化控制方法

针对一阶最优性必要条件跟踪法优化间隔较长的缺点, 提出一种基于输出反馈的显式实时优化方法. 对系统进行不同工况下的离线优化, 经函数拟合得到最优控制输入与输出变量的显式回归模型, 直接应用于实时优化, 避免了在线梯度估计. 研究一个连续搅拌釜式反应器的反应过程, 并对比两种方法的优化效果, 结果验证了所提出方法的实际使用效果

     

Robust resilient control for parametric strict feedback systems with prescribed output and virtual tracking errors

This paper investigates the robust resilient control problem for a class of parametric strict feedback nonlinear systems with prescribed output and virtual tracking errors performance. The resilience is governed by a continuously nonlinear control gains function, which endows the virtual and actual controllers with self‐adjusting abilities with respect to transformed error surfaces. The proposed control scheme is adaptation, estimation, and approximation‐free in the presence of unknown parameters and nonlinearities, and only a number of control gains, which is equal to the relative degree of the considered plants, need to be selected in applications. It is proved by rigorous analysis that the output tracking errors are confined in predefined prescribed performance functions under some nonrestrictive initial conditions, and the bounds of states are obtained characterized as control gains and systemic function‐associated constants. Finally, comparative illustrative examples are given to demonstrate the effectiveness of the proposed control scheme.     

Event-triggered output feedback control for two-time-scale systems with structured uncertainty

This paper investigates the event-triggered output feedback control problem for the two-time-scale systems with structured uncertainty. Due to the non-ignorable problem in applications such as equipment aging or parameter drifting, the robustness of the designed controller is worth discussing. A dynamic event-triggered scheme is proposed to reduce the computational cost of the control signal. The results indicate that with the proposed event-triggered controller, the system can achieve asymptotic stability without some common restrictions on the fast system rather than practical stability. Moreover, the Zeno behavior is excluded. Simulation examples with comparison studies illustrate the effectiveness of the proposed method.     

含有参数不确定性的挠性航天器姿态跟踪滑模控制

对有不确定参数的挠性航天器姿态跟踪控制, 提出了一种基于滑模控制的姿态跟踪控制律. 挠性航天器动力学采用混合坐标法进行建模; 构造挠性模态观测器对挠性模态变量进行观测. 基于Lyapunov稳定性原理得到含有挠性模态观测器的滑模控制律, 并给出了全局渐近稳定性的证明. 对各个仿真结果进行比较, 显示出本文提出的滑模控制律针对航天器惯量阵不确定性具有良好的鲁棒性, 而且具有较强的扰动抑制能力.     

A comparison of nonlinear observers for output feedback model-based control of seeded batch crystallization processes

This paper presents a comparative analysis of various nonlinear estimation techniques when applied for output feedback model-based control of batch crystallization processes. Several nonlinear observers, namely an extended Luenberger observer, an extended Kalman filter, an unscented Kalman filter, an ensemble Kalman filer and a moving horizon estimator are used for closed-loop control of a semi-industrial fed-batch crystallizer. The performance of the nonlinear observers is evaluated in terms of their closed-loop behavior as well as their ability to cope with model imperfections and process uncertainties such as measurement errors and uncertain initial conditions. The simulation results suggest that the extended Kalman filter and the unscented Kalman filter provide accurate state estimates that ensure adequate fulfillment of the control objective. The results also confirm that adopting a time-varying process noise covariance matrix further enhances the estimation accuracy of the latter observers at the expense of a slight increase in their computational burden. This tuning method is particularly suited for batch processes as the state variables often vary significantly along the batch run. It is observed that model imperfections and process uncertainties are largely detrimental to the accuracy of state estimates. The degradation in the closed-loop control performance arisen from inadequate state estimation is effectively suppressed by the inclusion of a disturbance model into the observers.     

An ILMI approach to robust static output feedback sliding mode control

This paper proposes a systematic methodology for designing robust static output feedback sliding mode control (SOFSMC) for a class of systems with mismatched uncertainties. This methodology consists of two parts: one is a new sufficient and necessary condition for the existence problem in terms of two matrix inequalities; the other is a direct solving method using the iterative linear matrix inequality (ILMI) technique. The main advantages of this method are that only original system parameters are involved without any extra coordinate changes, and that appealing to solving the static output feedback stabilization (SOFS) problem is no longer required. In addition, the ILMI algorithm includes an optimal part to avoid high control efforts. A numerical example also demonstrates the efficacy of the proposed approach.     

An integrated approach to active model adaptation and on-line dynamic optimisation of batch processes

In the application of on-line, dynamic process optimisation, adaptive estimation of the system states and parameters is usually needed to minimise the unavoidable model-process mismatch. This work presents an integrated approach to optimal model adaptation and dynamic optimisation, with specific focus on batch processes. An active approach is proposed whereby the input variables are designed so as to maximise the information content of the data for optimal model adaptation. Then, this active adaptation method is combined with the objective of process performance to form a multi-objective optimisation problem. This integrative approach is in contrast to the traditional adaptation method, where only the process performance is considered and adaptation is passively carried out by using the data as is. Two strategies for solving the multi-objective problem are investigated: weighted average and constrained optimisation, and the latter is recommended for the ease in determining the balance between these two objectives. The proposed methodology is demonstrated on a simulated semi-batch fermentation process.     

A direct parametric approach to spacecraft attitude tracking control

Through the direct parameter approach, a solution for spacecraft attitude tracking is presented. First of all, the spacecraft attitude tracking control model is built up by the error equation of the second-order nonlinear quaternion-based attitude system. Based on the control model, a suitable controller is designed by the direct parameter approach. Compared with other control strategies, the direct parameter approach can offer all degrees of freedom for the controller to satisfy the requirements for system properties and turn the original nonlinear system into closed-loop linear system. Furthermore, this paper optimizes the controller according to the robustness, limitation of controller output and closed-loop eigenvalue sensitivity. Putting the controller into the original system, the state response of the closed-loop system and the output of controller are plotted in Matlab to verify the availability and robustness of the controller. Therefore, the controlled spacecraft can achieve the goal of tracking on the mobile target with the external disturbance torque.     

Logarithmic based robust approach to parametric uncertainty for control of robot manipulators

In this paper, a new robust control law for controlling robot manipulators with parameter uncertainty is presented. A controller is designed based on the Lyapunov function and the control law that guarantees the system stability is derived as a result of analytical solution. Apart from previous studies, uncertainty bound and adaptation gain matrix are determined using the estimation law to control the system properly, and so this estimation law is developed as a logarithmic function depending on robot kinematics inertia parameters and tracking error. An application of the proposed control input to a two‐link robot manipulator is presented and numerical simulations are included. Copyright © 2005 John Wiley & Sons, Ltd.     

Evaluation study of an efficient output feedback nonlinear model predictive control for temperature tracking in an industrial batch reactor

The paper illustrates the benefits of nonlinear model predictive control (NMPC) for the setpoint tracking control of an industrial batch polymerization reactor. Real-time feasibility of the on-line optimization problem from the NMPC is achieved using an efficient multiple shooting algorithm. A real-time formulation of the NMPC that takes computational delay into account is described. The control relevant model for the NMPC is derived from the complex-first principles model and is fitted to the experimental data using maximum likelihood estimation. A parameter adaptive extended Kalman filter (PAEKF) is used for state estimation and on-line model adaptation. The performance of the NMPC implementation is assessed via simulation and experimental results.     

A parametric approach to deductive databases with uncertainty

Numerous frameworks have been proposed in recent years for deductive databases with uncertainty. On the basis of how uncertainty is associated with the facts and rules in a program, we classify these frameworks into implication-based (IB) and annotation-based (AB) frameworks. We take the IB approach and propose a generic framework, called the parametric framework, as a unifying umbrella for IB frameworks. We develop the declarative, fixpoint, and proof-theoretic semantics of programs in our framework and show their equivalence. Using the framework as a basis, we then study the query optimization problem of containment of conjunctive queries in this framework and establish necessary and sufficient conditions for containment for several classes of parametric conjunctive queries. Our results yield tools for use in the query optimization for large classes of query programs in IB deductive databases with uncertainty     

Static output feedback control for continuous-time T-S fuzzy systems: An LMI approach

This paper presents a design method of static output feedback control for continuous-time T-S fuzzy systems. Based on parallel distributed compensation (PDC), a static output feedback control is utilized. A new sufficient condition for the existence of static output feedback gains is represented in terms of linear matrix inequalities (LMIs). The sufficient condition does not need any transformation matrices, equality constraints, and block diagonal assumption of positive definite matrices in order to convert a bilinear matrix inequality (BMI) problem to an LMI one.     

An output feedback tracking controller for systems diffeomorphic to the non-linear observer form

An output feedback tracking controller is proposed for single-input, single-output non-linear systems that are diffeomorphic to the non-linear observer form. Difficulty in obtaining the output injection terms of the non-linear observer form is solved by a numerical technique and the interpolation method using the radial basis function (RBF) network. The trained RBF networks approximate output injection terms in a compact interval and are utilized for building a non-linear observer. In constructing the output tracking controller the backstepping control method is adopted based on the state estimates.     

Global output feedback tracking control for a class of Lagrangian systems

The problem of global tracking control without velocity measurement of the so-called Euler–Lagrange systems has been paid a lot of attention for the past several years. In this note, a nice property of one-degree-of-freedom Euler–Lagrange systems is highlighted, which in particular allows us to obtain a new solution to the problem of tracking control for this class of systems. The solution is under the form of a linear-like observer-based controller which gives fairly good results, as illustrated in the simulation. The method can be generalized to any system having the same property.     

Global output feedback control of nonlinear time-delay systems with input matching uncertainty and unknown output function

This paper studies the problem of global output feedback control for nonlinear time-delay systems with input matching uncertainty and the unknown output function, whose nonlinearities are bounded by lower triangular linear unmeasured states multiplying the unknown constant, polynomial-of-output and polynomial-of-input growth rates. By constructing a new extended state observer and skillfully combining the dynamic gain method, backstepping method and Lyapunov–Krasovskii theorem, a delay-independent output feedback controller can be developed with only one dynamic gain. It is proved that all the signals of the closed-loop system are bounded, the states of the original system and the corresponding observer converge to zero, and the estimation of input matching uncertainty converges to its actual value. Two examples demonstrate the effectiveness of the control scheme.     

Finite‐time consensus tracking for harmonic oscillators using both state feedback control and output feedback control

This paper investigates the distributed finite‐time consensus‐tracking problem for coupled harmonic oscillators. The objective is to guarantee a team of followers modeled by harmonic oscillators to track a dynamic virtual leader in finite time. Only a subset of followers can access the information of the virtual leader, and the interactions between followers are assumed to be local. We consider two cases: (i) The followers can obtain the relative states between their neighbors and their own; and (ii) Only relative outputs between neighboring agents are available. In the former case, a distributed consensus protocol is adopted to achieve the finite‐time consensus tracking. In the latter case, we propose a novel observer‐based dynamic protocol to guarantee the consensus tracking in finite time. Simulation examples are finally presented to verify the theoretical analysis. Copyright © 2012 John Wiley & Sons, Ltd.     

Robust output feedback control of polynomial growth nonlinear systems with measurement uncertainty

Even in the presence of uncertainty in both state and output equations, we prove that global asymptotic stabilization is still possible by output feedback for a family of uncertain nonlinear systems dominated by a triangular system with a polynomial output‐dependent growth rate. In contrast to the linear growth requirement in the recent work the nonlinear perturbations in this paper are allowed to satisfy a linear growth condition with a polynomial output‐dependent rate. To handle simultaneously the polynomial nonlinearities and unknown parameter in the system output, we propose a high‐gain estimator with a dynamic gain that is updated online through a Riccati‐type dynamic equation. Then, an estimator‐based controller is designed by a recursive algorithm that makes it possible to assign the controller gains step by step. The globally stabilizing output‐feedback controller developed in this paper is robust with respect to uncertainties in the system dynamics and output equations.     

Off-line approach to dynamic output feedback robust model predictive control

This paper presents an off-line approach to the dynamic output feedback robust model predictive control (OFRMPC) for a system with both polytopic uncertainty and bounded disturbance. For the off-line optimization, a sequence of controller parameters and the corresponding regions of attraction are calculated for all combinations of the pre-specified estimated states and estimation error sets (EESs). These controller parameters and the corresponding regions of attraction are stored in a look-up table. On-line, the controller parameters are searched in this look-up table corresponding to real-time EES, and to the region of attraction with the closest containment of real-time estimated state. This method considerably reduces the on-line computational burden. Two numerical examples are given to illustrate the effectiveness of the approach.     

Robust tracking control for a class of MIMO nonlinear systems with measurable output feedback

This paper proposes a robust output feedback controller for a class of nonlinear systems to track a desired trajectory. Our main goal is to ensure the global input-to-state stability (ISS) property of the tracking error nonlinear dynamics with respect to the unknown structural system uncertainties and external disturbances. Our approach consists of constructing a nonlinear observer to reconstruct the unavailable states, and then designing a discontinuous controller using a back-stepping like design procedure to ensure the ISS property. The observer design is realized through state transformation and there is only one parameter to be determined. Through solving a Hamilton–Jacoby inequality, the nonlinear control law for the first subsystem specifies a nonlinear switching surface. By virtue of nonlinear control for the first subsystem, the resulting sliding manifold in the sliding phase possesses the desired ISS property and to certain extent the optimality. Associated with the new switching surface, the sliding mode control is applied to the second subsystem to accomplish the tracking task. As a result, the tracking error is bounded and the ISS property of the whole system can be ensured while the internal stability is also achieved. Finally, an example is presented to show the effectiveness of the proposed scheme. Copyright © 2007 John Wiley & Sons, Ltd.