Читать книгу PID Passivity-Based Control of Nonlinear Systems with Applications - Romeo Ortega - Страница 16

Motivated by current practice, in this book, we explore the possibility of applying the industry‐standard proportional‐integral‐derivative (PID) controllers to regulate the behavior of nonlinear systems. As is well known, PID controllers are universal, in the sense that they incorporate knowledge of the system's past, present, and future, and they are overwhelmingly dominant in engineering practice. PIDs are highly successful when the main control objective is to drive a given output signal to a constant value. PIDs, however, have two main drawbacks, first, the task of tuning the gains is far from obvious when the system's operating region is large; second, in some practical applications, the control objective cannot be captured by the behavior of output signals.

In this book we show that, for a wide class of systems, these two difficulties can be overcome by exploiting the property of passivity, which in the case of physical systems captures the universal feature of energy conservation. To achieve this end, we propose a new class of controllers called PID passivity‐based controls (PBCs), whose main construction principle is to wrap the PID around a passive output of the plant. Since PIDs define (output strictly) passive systems for all positive gains, and the feedback interconnection of passive systems is stable, the proposed architecture yields a highly robust design that preserves stability for all tuning gains – considerably simplifying the task of commissioning the controller. To enable potential designers to use PID‐PBCs, we present in the book a comprehensive coverage of this topic.

Since passivity for physical systems is simply a reformulation of energy balancing, it is possible in many practical examples to easily identify some passive outputs. However, in many examples, either these outputs are not the ones we would like to regulate, and/or their desired value is not equal to zero. To address the first problem, we explore in the book the possibility of adding an integral action to nonpassive outputs preserving some stability properties. For the second problem, we propose to wrap the PID around the error of the output signal, and then we investigate whether the system is passive with respect to this error signal – a property called shifted passivity.

Another scenario of practical interest is when the control objective is to drive the full system state to a desired constant value. A classical example is mechanical systems, whose passive outputs are the actuated velocities, but in many applications – e.g. robotics – the objective is to drive all positions to some desired constant values. To formulate mathematically this objective, we aim at achieving Lyapunov stability of the desired equilibrium, a task that entails the need to construct a Lyapunov function, i.e., a nonincreasing function of the state with a minimum at the desired equilibrium. The approach we adopt in the book to solve this new task is to identify passive outputs whose integral can be expressed as a function of the system's state. The identification of these outputs boils down to finding first integrals for the closed‐loop dynamics that, in its turn, requires the solution of partial differential equations. The design is completed by projecting the closed‐loop dynamics onto the invariant manifold defined by the first integrals and verifying that the resulting function, which depends only on the state of the system, is positive definite.

The aforementioned integrability conditions can be obviated if the system is shifted passive, with a storage function that is positive definite with respect to a desired equilibrium. In spite of the intensive efforts to characterize the class of passive systems that are also shifted passive, the currently available results are quite restrictive – two common requirements being, for instance, that the input matrix is constant and the storage function of the original system is convex. The main results along these lines of research are reviewed in the book.

Another control scenario that we consider in the book pertains to the case when some stabilizing controller has already been added to the system, but we would like to include an additional integral action to reject the effect of additive disturbances that were neglected in the design of the aforementioned stabilizing controller. We treat the cases of constant or time‐varying disturbances as well as the scenario where the disturbances enter into the image of the input matrix – called matched disturbances – or when they are unmatched. In all cases, we give constructive solutions to the problem of designing this new integral action (IA).

Motivated by the application of PID in physical systems, we pay particular attention in the book to port‐Hamiltonian (pH) systems. It is well known that pH models describe the behavior of many physical processes and have the central feature of underscoring the importance of the energy function, the interconnection pattern, and the dissipation of the system, which are the essential ingredients of PBC. As shown throughout the book, the possibility of exploiting the latter features of pH systems in the design of a PID‐PBC or an IA allows us to obtain sharper, and in many cases, more constructive results than the ones available for general nonlinear systems.

The book is organized as follows. In Chapter 2, we give the general framework of PID‐PBC and show how they can be used to solve several stabilization and output regulation problems. In this chapter, we also discuss some obstacles for the application of PID‐PBC, in particular the dissipation obstacle, and show the relationship of PID‐PBC with the well‐known, and conceptually appealing, control‐by‐interconnection technique.

In Chapter 3, we show, via several practical examples, how the concept of passivity can be used for the analysis and tuning of PIDs.

In Chapter 4, we discuss the problem of designing of PID‐PBCs for the case when the desired value for the regulated output is different from zero. Some results on shifted passivity are presented and their use to solve this problem is discussed. This chapter is wrapped‐up with four modern practical applications.

Chapter 5 is devoted to the characterization of passive outputs for pH systems. This result is then used in Chapter 6 to design PID‐PBCs for pH systems that ensure Lyapunov stability. The particular case of underactuated mechanical systems is discussed in Chapter 7, where the results are illustrated with several practical examples.

In the final Chapter 8, we present the results pertaining to robustification of nonlinear controllers via the addition of IA – again, paying particular attention to pH and mechanical systems.

The appendices provide the basic definitions and background theory that is used throughout the book. In particular, some preliminaries on passivity and stability theory of state‐space systems and a brief discussion on pH systems are given. Some additional technical results and some useful lemmas needed in the book are also presented.