Automatic tuning of PID controllers using relay feedback experiments has received attention on and off since it was first proposed and industrially implemented in a control system in the 1980s. While optimal experiment design and modern system identification easily outperform the original automatic tuner, they rely on computational resources that are not always available in industrial control systems. Here we present a combination of experiment and subsequent output-error identification of continuous-time first-order time-delayed (FOTD) system models, that requires very little in terms of computations and memory. The method has been extensively evaluated in simulation, and a prototype has been implemented for the ABB AC 800M controller family.

High-precision measurements of joint displacements are available on robot manipulators. In contrast, velocity measurements obtained through tachometers are, in many cases, contaminated by noise. It is therefore economically and technically interesting to investigate the possibility of controlling robot dynamics by only using angular position measurements. Two alternative approaches for trajectory tracking control via nonlinear estimated state feedback are presented. The first scheme is based on smooth functions, whereas the second uses switching gains. The stability of the closed-loop system is investigated. Both approaches yield exponentially stable closed-loop systems. The local attraction areas are characterized in terms of controller and observer gains, initial state values, and robot model parameters.>

A simple servo controller built from components having neuronlike features is described. This VLSI servo controller uses pulses for control and is orders of magnitude smaller than a conventional system. The basic circuit elements are described. A key element is a component and neuronlike capability that takes voltages as inputs and generates a pulse train as the output. It is shown how the circuits are combined to a proportional and derivative controller. The advantages of using a pulsed output representation to improve slow-speed operation of a friction-limited system is demonstrated. The utility of exploiting parallelism, aggregation, and redundancy to improve system-level performance given imprecise low-level components is discussed. Experimental results illustrate the properties of the system compared with conventional controllers.

A design frame and a set of circuit elements with which generic motor controllers can be implemented are described. A simple proportional-derivative motor controller was embedded in the design frame. Its performance advantages over a more traditional controller are described. Also discussed are the merits of biologically inspired systems used in applications related to robotics.>

Adaptive control is now finding its way into the marketplace after many years of effort. This paper reviews some ideas used to design adaptive control systems. It covers early ideas which primarily attempt to compensate for gain variations and more general methods like gain scheduling, model reference adaptive control, and self-tuning regulators. It is shown that adaptive control laws can be obtained using stochastic control theory. Techniques for analyzing adaptive systems are discussed. This covers stability and convergence analysis. Issues of importance for applications like parameterization, tuning, and tracking, as well as different ways of using adaptive control are also discussed. An overview of applications which includes feasibility studies as well as products based on adaptive techniques concludes the paper.

A control scheme is proposed where the nonlinear effects of friction are compensated adaptively. When the friction is compensated, the motor drive can approximately be described by a constant coefficient linear model. Standard methods can be applied to design a regulator for such a model. This results in a control law which is a combination of a fixed linear controller and an adaptive part which compensates for nonlinear friction effects. Experiments have clearly shown that both static and dynamic friction have nonsymmetric characteristics. They depend on the direction of motion. This is considered in the design of the adaptive friction compensation. The proposes scheme has been implemented and tested on a laboratory prototype with good results. The control law is implemented on an IBM PC. The ideas, algorithm, and experimental results are described. The results are relevant for many precision drives, such as those found in industrial robots.

This paper proposes a control scheme where the nonlinear effects of friction are compensated adaptively. When the friction is compensated the motor drive can approximately be described by a constant coefficient linear model. Standard methods can be applied to design a regulator for such a model. This results in a control law which is a combination of a fixed linear controller and an adaptive part which compensates for nonlinear friction effects. Experiments have clearly shown that both static and dynamic friction have nonsymmetric characteristic. They depend on the direction of motion. This is considered in the design of the adaptive friction compensation. The proposed scheme has been implemented and tested on a laboratory prototype with good results. The control low is implemented on an IBM-PC. The paper describes the ideas, the algorithm and the experimental results. The results are relevant for many precision drives like those found in industrial robots.