Peter J. Gawthrop

Neural networks for control systems: a survey

Abstract This paper focuses on the promise of artificial neural networks in the realm of modelling, identification and control of nonlinear systems. The basic ideas and techniques of artificial neural networks are presented in language and notation familiar to control engineers. Applications of a variety of neural network architectures in control are surveyed. We explore the links between the fields of control science and neural networks in a unified presentation and identify key areas for future research.

A nonlinear disturbance observer for robotic manipulators

A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well.

Brief Optimal control of nonlinear systems: a predictive control approach

A new nonlinear predictive control law for a class of multivariable nonlinear systems is presented in this paper. It is shown that the closed-loop dynamics under this nonlinear predictive controller explicitly depend on design parameters (prediction time and control order). The main features of this result are that an explicitly analytical form of the optimal predictive controller is given, on-line optimisation is not required, stability of the closed-loop system is guaranteed, the whole design procedure is transparent to designers and the resultant controller is easy to implement. By establishing the relationship between the design parameters and time-domain transient, it is shown that the design of an optimal generalised predictive controller to achieve desired time-domain specifications for nonlinear systems can be performed by looking up tables. The design procedure is illustrated by designing an autopilot for a missile.

Human control of an inverted pendulum: Is continuous control necessary? Is intermittent control effective? Is intermittent control physiological?

Homeostasis, the physiological control of variables such as body position, is founded on negative feedback mechanisms. The default understanding, consistent with a wealth of knowledge related to peripheral reflexes, is that feedback mechanisms controlling body position act continuously. For more than fifty years, it has been assumed that sustained control of position is best interpreted using continuous paradigms from engineering control theory such as those which regulate speed in a vehicle ‘cruise control’ system. Using a joystick to control an unstable load that falls over like a person fainting, we show that control using intermittent gentle taps is natural, more effective and robust to unexpected changes than continuous hand contact, works best with two taps per second, and can explain the upper frequency limit of control by both methods. Serial ballistic control, limited to an optimum rate, provides a new physiological paradigm for interpreting sustained control of posture and movement.

Continuous-time generalized predictive control (CGPC)

A continuous-time version of the discrete-time Generalized Predictive Controller is presented. The continuous-time formulation arises from a mixture of two kinds of analogy between continuous and discrete-time systems: a physical analogy and an algebraic analogy. Emphasis is placed on the differences arising from a continuous-time formulation, and the relative merits of a continuous and a discrete-time approach are given. Although mainly concerned with the design algorithm itself, the paper also indicates how a self-tuning version can be implemented. Illustrative simulations are given.

Bond-graph modeling

The bond-graph method is a graphical approach to modeling in which component energy ports are connected by bonds that specify the transfer of energy between system components. Power, the rate of energy transport between components, is the universal currency of physical systems. Bond graphs are inherently energy based and thus related to other energy-based methods, including dissipative systems and port-Hamiltonians. This article has presented an introduction to bond graphs for control engineers. Although the notation can initially appear daunting, the bond graph method is firmly grounded in the familiar concepts of energy and power. The essential element to be grasped is that bonds represent power transactions between components

Intermittent control: a computational theory of human control

The paradigm of continuous control using internal models has advanced understanding of human motor control. However, this paradigm ignores some aspects of human control, including intermittent feedback, serial ballistic control, triggered responses and refractory periods. It is shown that event-driven intermittent control provides a framework to explain the behaviour of the human operator under a wider range of conditions than continuous control. Continuous control is included as a special case, but sampling, system matched hold, an intermittent predictor and an event trigger allow serial open-loop trajectories using intermittent feedback. The implementation here may be described as “continuous observation, intermittent action”. Beyond explaining unimodal regulation distributions in common with continuous control, these features naturally explain refractoriness and bimodal stabilisation distributions observed in double stimulus tracking experiments and quiet standing, respectively. Moreover, given that human control systems contain significant time delays, a biological-cybernetic rationale favours intermittent over continuous control: intermittent predictive control is computationally less demanding than continuous predictive control. A standard continuous-time predictive control model of the human operator is used as the underlying design method for an event-driven intermittent controller. It is shown that when event thresholds are small and sampling is regular, the intermittent controller can masquerade as the underlying continuous-time controller and thus, under these conditions, the continuous-time and intermittent controller cannot be distinguished. This explains why the intermittent control hypothesis is consistent with the continuous control hypothesis for certain experimental conditions.

Self-tuning PID controllers: Algorithms and implementation

A class of controllers with integral action is shown to arise directly from appropriate system models. Via the zero-gain predictor approach, a corresponding class of hybrid self-tuning controllers is shown to have both integral action in the controller and offset removal in the tuning algorithm. Implementation details and some experimental results are given.

Identification of time delays using a polynomial identification method

Abstract An algorithm for the exact least-squares identification of an approximate continuous-time time-delay system is derived and its operation verified by simulation.

Implementation and application of microprocessor-based self-tuners

The implementation of a class of self-tuning controllers using a portable microcomputer system is described. The self-tuning control theory is shown to provide a variety of control objectives such as model-reference, optimal Smith prediction and the minimization of a general k-step-ahead cost-function. Hardware and software details of the portable computer, SESAME, are presented with particular reference to the use of a new high-level language, Control Basic. Studies of the application of self-tuning to the control of room-temperature, acid neutralization, and batch chemical reactors in industry are outlined.