PID autotuning using neural networks and model reference adaptive control

This paper describes the application of artificial neural networks for automatic tuning of PID controllers using the Model Reference Adaptive Control approach. The effectiveness of the proposed method is shown through a simulated application.

Advanced methods in adaptive control for industrial applications

This volume is based on a seminar concerned with advanced methods in adaptive control for industrial applications which was held in Prague in May 1990 and which brought together experts in the UK and Czechoslovakia in order to suggest solutions to specific current and anticipated problems faced by industry.

How is the balance of a forecast ensemble affected by adaptive and non-adaptive localization schemes?

This paper investigates the effect on balance of a number of Schur product-type localization schemes which have been designed with the primary function of reducing spurious far-field correlations in forecast error statistics. The localization schemes studied comprise a non-adaptive scheme (where the moderation matrix is decomposed in a spectral basis), and two adaptive schemes, namely a simplified version of SENCORP (Smoothed ENsemble COrrelations Raised to a Power) and ECO-RAP (Ensemble COrrelations Raised to A Power). The paper shows, we believe for the first time, how the degree of balance (geostrophic and hydrostatic) implied by the error covariance matrices localized by these schemes can be diagnosed. Here it is considered that an effective localization scheme is one that reduces spurious correlations adequately but also minimizes disruption of balance (where the 'correct' degree of balance or imbalance is assumed to be possessed by the unlocalized ensemble). By varying free parameters that describe each scheme (e.g. the degree of truncation in the schemes that use the spectral basis, the 'order' of each scheme, and the degree of ensemble smoothing), it is found that a particular configuration of the ECO-RAP scheme is best suited to the convective-scale system studied. According to our diagnostics this ECO-RAP configuration still weakens geostrophic and hydrostatic balance, but overall this is less so than for other schemes.

Farmer attitudes and livestock disease: exploring citizenship behaviour and peer monitoring across two BVD control schemes in the UK

The eradication of BVD in the UK is technically possible but appears to be socially untenable. The following study explored farmer attitudes to BVD control schemes in relation to advice networks and information sharing, shared aims and goals, motivation and benefits of membership, notions of BVD as a priority disease and attitudes toward regulation. Two concepts from the organisational management literature framed the study: citizenship behaviour where actions of individuals support the collective good (but are not explicitly recognised as such) and peer to peer monitoring (where individuals evaluate other’s behaviour). Farmers from two BVD control schemes in the UK participated in the study: Orkney Livestock Association BVD Eradication Scheme and Norfolk and Suffolk Cattle Breeders Association BVD Eradication Scheme. In total 162 farmers participated in the research (109 in-scheme and 53 out of scheme). The findings revealed that group helping and information sharing among scheme members was low with a positive BVD status subject to social censure. Peer monitoring in the form of gossip with regard to the animal health status of other farms was high. Interestingly, farmers across both schemes supported greater regulation with regard to animal health, largely due to the mistrust of fellow farmers following voluntary disease control measures. While group cohesiveness varied across the two schemes, without continued financial inducements, longer-term sustainability is questionable

Mitigation of symmetry condition in positive realness for adaptive control

Feasibility of nonlinear and adaptive control methodologies in multivariable linear time-invariant systems with state-space realization (A, B, C) is apparently limited by the standard strictly positive realness conditions that imply that the product CB must be positive definite symmetric. This paper expands the applicability of the strictly positive realness conditions used for the proofs of stability of adaptive control or control with uncertainty by showing that the not necessarily symmetric CB is only required to have a diagonal Jordan form and positive eigenvalues. The paper also shows that under the new condition any minimum-phase systems can be made strictly positive real via constant output feedback. The paper illustrates the usefulness of these extended properties with an adaptive control example. (C) 2006 Elsevier Ltd. All rights reserved.

Adaptive control charts: A Markovian approach for processes subject to independent disturbances

Recent studies have shown that adaptive X control charts are quicker than traditional X charts in detecting small to moderate shifts in a process. In this article, we propose a joint statistical design of adaptive X and R charts having all design parameters varying adaptively. The process is subjected to two independent assignable causes. One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. It is assumed that the quality characteristic is normally distributed and the time that the process remains in control has exponential distribution. Performance measures of these adaptive control charts are obtained through a Markov chain approach. (c) 2005 Elsevier B.V. All rights reserved.

Adaptive control charts for attributes

We develop a general model for adaptive c, np, u and p control charts in which one, two or three design parameters (sample size, sampling interval and control limit width) switch between two values, according to the most recent process information. For a given in-control average sampling rate and a given false alarm rate, the adaptive chart detects changes in the process much faster than a chart with fixed parameters. Moreover, this study also offers general guidance on how to choose an effective design.

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

Adaptive control system based on lineal control theory for the path-following problem of a car-like mobile robot

The objective of this paper is to design a path following control system for a car-like mobile robot using classical linear control techniques, so that it adapts on-line to varying conditions during the trajectory following task. The main advantages of the proposed control structure is that well known linear control theory can be applied in calculating the PID controllers to full control requirements, while at the same time it is exible to be applied in non-linear changing conditions of the path following task. For this purpose the Frenet frame kinematic model of the robot is linearised at a varying working point that is calculated as a function of the actual velocity, the path curvature and kinematic parameters of the robot, yielding a transfer function that varies during the trajectory. The proposed controller is formed by a combination of an adaptive PID and a feed-forward controller, which varies accordingly with the working conditions and compensates the non-linearity of the system. The good features and exibility of the proposed control structure have been demonstrated through realistic simulations that include both kinematics and dynamics of the car-like robot.

Adaptive Control for ZVS Three Phase Full Active Bridge Converter with ARCN

This paper presents an adaptive control for the auxiliary circuit, called ARCN (Auxiliary Resonant Commutating Network), used to achieve ZVS in full active bridge converters under a wide load range. Depending on the load conditions, the proposed control adapts the timing of the ARCN to minimize the losses. The principle of operation and implementation considerations are presented for a three phase full active bridge converter, proposing different methods to implement the control according to the specifications. The experimental results shown verify the proposed methodology.

Nitric oxide plays a key role in adaptive control of locomotion in cat

Diverse roles in cellular functions have been ascribed to nitric oxide (NO), and its involvement in induction of long-term depression in cerebellar Purkinje cells has been demonstrated. Manipulations of NO concentration or its synthesis in cerebellar tissues therefore provide a means for investigating roles of NO in cerebellar functions at both cellular and behavioral levels. We tested adaptive control of locomotion to perturbation in cats, and found that this form of motor learning was abolished by application of either an inhibitor of NO synthase or a scavenger of NO to the cerebellar cortical locomotion area. This finding supports the view that NO in the cerebellum plays a key role in motor learning.

Countermanding in rats as a practical model for investigation of adaptive control of behaviour, lifespan changes in behavioural control and neurotransmitter function

The countermanding paradigm was designed to investigate the ability to cancel a prepotent response when a stop signal is presented and allows estimation of the stop signal response time (SSRT), an otherwise unobservable behaviour. Humans exhibit adaptive control of behaviour in the countermanding task, proactively lengthening response time (RT) in expectation of stopping and reactively lengthening RT following stop trials or errors. Human performance changes throughout the lifespan, with longer RT, SSRT and greater emphasis on post-error slowing reported for older compared to younger adults. Inhibition in the task has generally been improved by drugs that increase extracellular norepinephrine. The current thesis examined a novel choice response countermanding task in rats to explore whether rodent countermanding performance is a suitable model for the study of adaptive control of behaviour, lifespan changes in behavioural control and the role of neurotransmitters in these behaviours. Rats reactively adjusted RT in the countermanding task, shortening RT after consecutive correct go trials and lengthening RT following non-cancelled, but not cancelled stop trials, in sessions with a 10 s, but not a 1 s post-error timeout interval. Rats proactively lengthened RT in countermanding task sessions compared to go trial-only sessions. Together, these findings suggest that rats strategically lengthened RT in the countermanding task to improve accuracy and avoid longer, unrewarded timeout intervals. Next, rats exhibited longer RT and relatively conserved post-error slowing, but no significant change in SSRT when tested at 12, compared to 7 months of age, suggesting that rats exhibit changes in countermanding task performance with aging similar to those observed in humans. Finally, acute administration of yohimbine (1.25, 2.5 mg/kg) and d-amphetamine (0.25, 0.5 mg/kg), which putatively increase extracellular norepinephrine and dopamine respectively, resulted in RT shortening, baseline-dependent effects on SSRT, and attenuated adaptive RT adjustments in rats in the case of d-amphetamine. These findings suggest that dopamine and norepinephrine encouraged motivated, reward-seeking behaviour and supported inhibitory control in an inverted-U-like fashion. Taken together, these observations validate the rat countermanding task for further study of the neural correlates and neurotransmitters mediating adaptive control of behaviour and lifespan changes in behavioural control.