Reduced complexity adaptive nonlinear control of a distributed collector solar field

An approach to the control of a distributed collector solar field relying on feedback linearization, Lyapunov based adaptation and a simplified plant model is presented. The control objective consists of manipulating the oil flow so that the outlet oil temperature is regulated around a given setpoint. For dealing with plant nonlinearities and external disturbances, a nonlinear transformation is performed on the accessible variables such that the transformed system behaves as an integrator, to which linear control techniques are then applied. Since the transformation depends on an unknown parameter, an adaptation law is designed so as to minimize a Lyapunov function for the whole system's state. For the sake of control synthesis a simplified plant model which retains the bilinear nonlinearity is employed. The resulting control law has the same control structure of the one yielding exact input-output linearization but assumes a different placement of a temperature sensor. In order to justify this procedure, plant internal dynamics is studied. Experimental results obtained in the actual field are presented.     

Energy-based control of a distributed solar collector field

Model-based control of the outlet temperature of a distributed solar collector field is studied. An energy-based controller is derived using internal energy as a controlled variable. The controller relies on a distributed parameter nonlinear plant model and includes feedforward from the solar irradiation and inlet temperature. Convergence of the closed loop is proved, and the method is experimentally verified to perform well on a pilot-scale solar power plant.     

Implementation of feedback linearization GPC control for a solar furnace

In this paper the temperature control of a solar furnace is addressed. In particular, we propose the use of a feedback linearization generalized predictive control strategy where both the reference tracking task and the rejection of disturbances (represented by the variation of the input energy provided by the Sun, mainly because of the solar daily cycle and passing clouds) are considered. This allows the physical and security constraints to be explicitly taken into account in the design. Simulation and experimental results show the effectiveness of the methodology and that this kind of plants can be considered as a cheap or alternative option for the material treatment and testing in the industrial context.     

Feedback linearization based control of a rotational hydraulic drive

The technique of feedback linearization is used to design controllers for displacement, velocity and differential pressure control of a rotational hydraulic drive. The controllers, which take into account the square-root nonlinearity in the system's dynamics, are implemented on an experimental test bench and results of performance evaluation tests are presented. The objective of this research is twofold: firstly, to present a unified method for tracking control of displacement, velocity and differential pressure; and secondly, to experimentally address the issue of whether the system can be modeled with sufficient accuracy to effectively cancel out the nonlinearities in a real-world system.     

Cascade control of a distributed collector solar field

This paper reports experimental results on the cascade control of a distributed collector solar field. The control problem consists of keeping constant the field outlet oil temperature by acting on the circulating oil flow used for heat transfer. In the inner loop an adaptive model based predictive controller exploiting the information conveyed by accessible disturbances (radiation changes and inlet oil temperature) is used, while in the outer loop a PID is employed. The need for adaptive control arises from the time varying behaviour of the plant. Due to the generality of the methods employed, the experience reported is relevant to a wide class of industrial processes.     

Adaptive time-warped control of molten salt distributed collector solar fields

This paper concerns the temperature control of a new class of distributed collectors solar fields, which employ molten salt as heat transfer fluid (HTF). Distinctive characteristics of these plants are the high operating temperatures, close to the thermal limits of receiver pipes, and the high solidification temperature of HTF. By means of a novel hybrid adaptive control scheme, based on the Unscented Kalman Filter and on a time-warped predictive controller, the HTF temperature can be effectively controlled within prescribed constraints also in presence of uncertainty in model parameters and faults on collectors.     

A switching control strategy applied to a solar collector field

This work presents a new switching control procedure that has been chosen to deal with the changes in plant dynamics. Several control systems composed of IMC-based PID controllers and feedforward compensators are designed for each operation region and a continuous switching mechanism for the overall control system is defined. Experimental tests which have been performed in a distributed collector field of a solar air cooling system, are presented showing promising results for the proposed strategy.     

Feedback linearization of the nonlinear model of a small-scale helicopter

In order to design a nonlinear controller for small-scale autonomous helicopters, the dynamic characteristics of a model helicopter are investigated, and an integrated nonlinear model of a small-scale helicopter for hovering control is presented. It is proved that the nonlinear system of the small-scale helicopter can be transformed to a linear system using the dynamic feedback linearization technique. Finally, simulations are carried out to validate the nonlinear controller.     

Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects. Recommended by Editorial Board member Hyo-Choong Bang under the direction of Editor Hyun Seok Yang. This work was supported by the Korea Research Foundation Grant (MOEHRD) KRF-2005-204-D00002, the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government(MOST) R0A-2007-000-10017-0 and Engineering Research Institute at Seoul National University. Daewon Lee received the B.S. degree in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical and Aerospace Engineering. He has been a member of the UAV research team at SNU since 2005. His research interests include applications of nonlinear control and vision-based control of UAV. H. Jin Kim received the B.S. degree from Korea Advanced Institute of Technology (KAIST) in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from University of California, Berkeley in 1999 and 2001, respectively. From 2002–2004, she was a Postdoctoral Researcher and Lecturer in Electrical Engineering and Computer Science (EECS), University of California, Berkeley (UC Berkeley). From 2004–2009, she was an Assistant Professor in the School of in Mechanical and Aerospace Engineering at Seoul National University (SNU), Seoul, Korea, where she is currently an Associate Professor. Her research interests include applications of nonlinear control theory and artificial intelligence for robotics, motion planning algorithms. Shankar Sastry received the B.Tech. degree from the Indian Institute of Technology, Bombay, in 1977, and the M.S. degree in EECS, the M.A. degree in mathematics, and the Ph.D. degree in EECS from UC Berkeley, in 1979, 1980, and 1981, respectively. He is currently Dean of the College of Engineering at UC Berkeley. He was formerly the Director of the Center for Information Technology Research in the Interest of Society (CITRIS). He served as Chair of the EECS Department from January, 2001 through June 2004. In 2000, he served as Director of the Information Technology Office at DARPA. From 1996 to 1999, he was the Director of the Electronics Research Laboratory at Berkeley (an organized research unit on the Berkeley campus conducting research in computer sciences and all aspects of electrical engineering). He is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences and holds faculty appointments in the Departments of Bioengineering, EECS and Mechanical Engineering. Prior to joining the EECS faculty in 1983 he was a Professor with the Massachusetts Institute of Technology (MIT), Cambridge. He is a member of the National Academy of Engineering and Fellow of the IEEE.     

Feedback linearization and driftless systems

The problem of dynamic feedback linearization is recast using the notion of dynamic immersion. We investigate here a generic property which holds at every point of a dense open subset, but may fail at some points of interest, such as equilibrium points. Linearizable systems are then systems that can be immersed into linear controllable ones. This setting is used to study the linearization of driftless systems: a geometric sufficient condition in terms of Lie brackets is given; this condition is also shown to be necessary when the number of inputs equals two. Though noninvertible feedbacks are nota priori excluded, it turns out that linearizable driftless systems with two inputs can be linearized using only invertible feedbacks, and can also be put into a chained form by (invertible) static feedback. Most of the developments are done within the framework of differential forms and Pfaffian systems.This work was partially supported by INRIA, NSF Grant ECS-9203491, GR Automatique (CNRS), and DRED (Ministère de l'Éducation Nationale). Part of it was done while the first author was visiting the Center for Control Engineering and Computation, University of California at Santa Barbara.     

Quotient submanifolds for static feedback linearization

A procedure for finding locally the linearizing output of a single input nonlinear affine system is proposed. It relies on successive integrations of one-dimensional distributions and projections along these submanifolds. The algorithm proceeds recursively reducing the dimension one by one of both the number of coordinates and the number of vector fields, until the solution is obtained. A variant of the algorithm is also proposed, which does not require the computation of the full initial distribution. The proof of convergence of this second algorithm shows the importance of a new anti-symmetrical product. Besides providing a new insight into the involutivity condition, the algorithm can lead to a simple way of integrating the system of partial differential equations defining the linearizing output.     

Automatic differentiation and nonlinear controller design by exact linearization

Various modern algorithms for controller design are based on differential-geometric concepts. A method of particular importance is called exact linearization via feedback. In this case, the implementation of the controller requires the computation of Lie derivatives, which have been computed symbolically. This can be very time consuming. We present a new computation method relying on automatic differentiation.     

On approximate linearization of nonlinear control systems

A method for the approximate linearization of nonlinear control systems based on the ‘state-space exact linearization’ method is presented. An explicit procedure, both for the single-input and for the multiple-input case, is given, which is straightforward to implement.     

基于扩张状态观测器的反馈线性化无人飞行器姿态控制

随着集成电子等技术逐渐成熟,无人飞行器得到了广泛的关注和应用;其中,由于飞行器在飞行阶段具有高响应速度、耦合动力学和非线性等特点,使其在飞行阶段的姿态控制成为该领域重点研究的方向之一;针对该研究方向,文章提出了一种基于反步法技术的反馈线性化无人飞行器姿态跟踪控制方案来解决其在受到环境干扰的条件下可以精准跟踪姿态角度的问题;在该方法中,设计了反步法技术拆分简化模型和反馈线性化减少调节参数,并利用扩张状态观测器(ESO)来对扰动进行估计和补偿,同时给出了ESO的收敛性和闭环系统的稳定性来证明该方法的可实施性;最后给出了仿真结果,验证了该方法在干扰的环境下仍可以精准控制无人飞行器姿态。     

An adaptive temperature control law for a solar furnace

This paper describes the development of an adaptive control law based on the exact feedback linearization and Lyapunov adaptation of the process dynamics applied to a solar furnace. The algorithm resulting from these underlying design principles is approximated in order to relate it with an adaptive PI controller with feedforward. The controller is tested on a 6 kW solar furnace model that represents a plant installed at the Odeillo Processes Materials and Solar Energy Laboratory (Oriental Pyrenees in the South of France). The adaptive features allow to tackle the problems posed by knowledge uncertainty about furnace dynamics. It is concluded that the specifications related to material testing are met.     

Feedback linearization of a flexible manipulator near its rigid body manifold

It is shown that a ‘slow’ 2n-dimensional manifold exists in the 4n-dimensional state space of an n-link manipulator with n flexible joints. While the flexible manifold is not linearizable by feedback, its restriction to'the slow manifold is. A method is given for computing a feedback control which achieves an approximate linearization.     

Gain-scheduling model predictive control of a Fresnel collector field

Model predictive control strategies have been applied successfully when controlling solar plants. If the control algorithm uses a linear model associated only to an operating point, when the plant is working far from the design conditions, the performance of the controller may deteriorate.In this paper, a gain scheduling model predictive control strategy is designed for the Fresnel collector field located at the Escuela Superior de Ingenieros de Sevilla. Simulation results are provided comparing the proposed strategy with another linear MPC controller showing a better performance. Furthermore, two real tests are presented showing the effectiveness of the proposed strategy.     

磁悬浮系统的两种线性化控制方法

本文首先利用动力学和电磁学方法建立了磁悬浮系统的模型 ,然后给出了直接反馈线性化方法的控制器设计 ,接着给出了基于平衡点展开的控制器设计 ,最后将两种控制方法的性能做了仿真比较 ,得出了两种方法的优劣结论。     

自主车队的非线性建模与控制

针对自主式车队建模与控制这一重要课题,建立了包含路面坡度和风力因素的非线性车辆动力学模型,进而基于反馈线性化方法提出一种对坡度和风速变化具有一定适应能力的非线性PID控制算法,并给出了一种可以克服燃油和传输延时的控制器设计方法以及可允许的延时上限.所得的非线性模型在很大程度上完善了现有的车辆动力学模型.仿真实验表明,该控制方法不但可实现车队的稳定运行控制,而且使车队控制效果大大改善.     

On the problem of feedback linearization

The paper studies and solves in a geometric framework the problem of partial feedback linearization for discrete-time dynamics. An algorithm for computing the largest linearizable subsystem is proposed. This approach can be considered as dual to the one already proposed in literature in an algebraic context.