Adaptive control of siso plants with unmodelled dynamics

In this paper we pursue a twofold aim. First we want to simplify the complexity of the classical Monopoli's scheme, the so-called ‘Augmented error signal control scheme’. Then we also wish to cope with the realistic situation in which the presence of unmodelled dynamics has to be taken into account. This latter problem has been faced in the literature by suitably modifying the adaptation mechanism in order to avoid undesired phenomena as well as to obtain an attractive stability region for the state trajectories starting from any point in a predefined initial condition set. In our case the necessity of introducing any sort of modification in the adaptation mechanism is completely avoided, but we still obtain asymptotic stability of the output error signal.     

Robustness of VS-MRAC with respect to unmodelled dynamics and external disturbances

A variable structure model reference adaptive controller (VS-MRAC) using only input and output measurements was recently proposed and shown to be globally asymptotically stable with superior transient behaviour and disturbance rejection properties. In this paper a singular perturbation approach is used in order to establish the robustness of the controller in the presence of unmodelled dynamics (parasitics) and disturbances. We develop a new Lyapunov-based technique to analyse the overall system and show that for sufficiently small parasitics the system remains stable and the output error is small in some sense.     

Results of the ASTM field test of tristimulus weighting functions

In 1993, the American Society for Testing and Materials carried out a field test of newly calculated tristimulus weighting factors. These weighting factors had been calculated by a method proposed by Venable. the test also included a method of correction for bandpass dependence put forth by Stearns. the purpose of the trial was to assess the possible reduction in bandpass dependence introduced by each of these sets of weights. A large number of sets of spectral data were gathered from the cooperators in the field test. Results of integration by the various sets of tristimulus weighting factors were calculated. A total of 15 120 color differences were calculated and statistics were derived to test the probable error resulting from each method of correction. Errors attributable to bandpass dependence were on the order of a few tenths to as much as one CIELAB unit when uncorrected weight sets were used. These errors could be reduced to a few hundreths of a CIELAB unit, and in some cases to a few thousandths of a unit, by employing one correcting strategy or the other. an overall mix of strategies was ultimately chosen to minimize the bandpass dependence over the entire range of weight sets. Utilizing this mixed strategy, the median error introduced into 10-nm integration by bandpass dependence was only 0.004 CIELAB units. © 1995 John Wiley & Sons, Inc.     

Generation of adaptive gait patterns for quadruped robot with CPG network including motor dynamic model

This paper describes the generation of adaptive gait patterns using new Central Pattern Generators (CPGs) including motor dynamic models for a quadruped robot under various environments. The CPGs act as the flexible oscillators of the joints and adjust joint angles to required values. The CPGs are interconnected with each other and sets of their coupling parameters are adjusted by a genetic algorithm so that the quadruped robot can realize stable and adequate gait patterns. Generation of gait patterns results in the formation of the CPG networks suitable for the formation of not only a straight walking pattern but also of rotating gait patterns. Experimental results demonstrate that the proposed CPG networks are effective for the automatic adjustment of the adaptive gait patterns for the tested quadruped robot under various environments. Furthermore, the target tracking control based on image processing is achieved by combining the general gait patterns. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 155(1): 35–43, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20225     

A novel robust current control approach using adaptive line enhancer for three‐phase current‐source active power filter

An effective system control method is presented for applying a three‐phase current‐source PWM converter with a deadbeat controller to active power filters (APFs). In the shunt‐type configuration, the APF is controlled such that the current drawn by the APF from the utility is equal to the current harmonics and reactive current required for the load. To attain the time‐optimal response of the APF supply current, a two‐dimensional deadbeat control scheme is applied to APF current control. Furthermore, in order to cancel both the delay in the two‐dimensional deadbeat control scheme and the delay in DSP control strategy, an Adaptive Line Enhancer (ALE) is introduced in order to predict the desired value three sampling periods ahead. ALE has another function of bringing robustness to the deadbeat control system. Due to the ALE, settling time is made short in a transient state. On the other hand, total harmonic distortion (THD) of source currents can be minimized compared to the case where ideal identification of the controlled system can be made. The experimental results obtained from the DSP‐based APF are also reported. The compensating ability of this APF is very high in accuracy and responsiveness although the modulation frequency is rather low. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(1): 50–61, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20014     

Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.     

Adaptive control in a heating vessel: A comparative study

This paper presents experimental results obtained in temperature adaptive control of a heating vessel. A non-linear model of the process showed that the feed flow rate causes severe variations in time constant and process gain. An extended horizon self-tuning controller and two different model reference adaptive controllers were tested. The influence of design parameters on control performance for each algorithm was assessed. The control system was disturbed with load and setpoint changes.     

Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations

Due to the complexity of the machine tool structure and the cutting process, the dynamics of machining processes are still not completely understood. This is especially true due to the demand of high-speed machining to increase productivity. In order to model and control these complex processes, new approaches, which can represent complex phenomenon combined with learning ability, are needed. The combined neural–fuzzy approach appears to be ideally suited for this purpose. In this paper, the recently developed fuzzy adaptive network (FAN) is used to model surface roughness in turning operations. The FAN network has both the learning ability of neural network and linguistic representation of complex, not well-understood, vague phenomenon. Furthermore, it can continuously improve the initially obtained rough model based on the daily operating data. To illustrate this approach, a model representing the influences of machining parameters on surface roughness is established and then the model is verified by the use of the results of pilot experiments. Finally, a comparison with the results based on statistical regression is provided.     

CCA-secure unidirectional proxy re-encryption in the adaptive corruption model without random oracles

Up to now, it is still an open question of how to construct a chosen-ciphertext secure unidirectional proxy re-encryption scheme in the adaptive corruption model. To address this problem, we propose a new unidirectional proxy re-encryption scheme, and prove its chosen-ciphertext security in the adaptive corruption model without random oracles. Compared with the best known unidirectional proxy re-encryption scheme proposed by Libert and Vergnaud in PKC’08, our scheme enjoys the advantages of both higher effi...