Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning

This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

An improved reliability Cuk based solar inverter with sliding mode control

Many photovoltaic inverter designs make use of a buck based switched mode power supply (SMPS) to produce a rectified sinusoidal waveform. This waveform is then unfolded by a low frequency switching structure to produce a fully sinusoidal waveform. The Cuk SMPS could offer advantages over the buck in such applications. Unfortunately the Cuk converter is considered to be difficult to control using classical methods. Correct closed loop design is essential for stable operation of Cuk converters. Due to these stability issues, Cuk converter based designs often require stiff low bandwidth control loops. In order to achieve this stable closed loop performance, traditional designs invariably need large, unreliable electrolytic capacitors. In this paper, an inverter with a sliding mode control approach is presented which enables the designer to make use of the Cuk converters advantages, while ameliorating control difficulties. This control method allows the selection of passive components based predominantly on ripple and reliability specifications while requiring only one state reference signal. This allows much smaller, more reliable non-electrolytic capacitors to be used. A prototype inverter has been constructed and results obtained which demonstrate the design flexibility of the Cuk topology when coupled with sliding mode control.

Development and experimental identification of a biomechanical model of the trunk for functional electrical stimulation control in paraplegia

Objectives. Theoretic modeling and experimental studies suggest that functional electrical stimulation (FES) can improve trunk balance in spinal cord injured subjects. This can have a positive impact on daily life, increasing the volume of bimanual workspace, improving sitting posture, and wheelchair propulsion. A closed loop controller for the stimulation is desirable, as it can potentially decrease muscle fatigue and offer better rejection to disturbances. This paper proposes a biomechanical model of the human trunk, and a procedure for its identification, to be used for the future development of FES controllers. The advantage over previous models resides in the simplicity of the solution proposed, which makes it possible to identify the model just before a stimulation session ( taking into account the variability of the muscle response to the FES). Materials and Methods. The structure of the model is based on previous research on FES and muscle physiology. Some details could not be inferred from previous studies, and were determined from experimental data. Experiments with a paraplegic volunteer were conducted in order to measure the moments exerted by the trunk-passive tissues and artificially stimulated muscles. Data for model identification and validation also were collected. Results. Using the proposed structure and identification procedure, the model could adequately reproduce the moments exerted during the experiments. The study reveals that the stimulated trunk extensors can exert maximal moment when the trunk is in the upright position. In contrast, previous studies show that able-bodied subjects can exert maximal trunk extension when flexed forward. Conclusions. The proposed model and identification procedure are a successful first step toward the development of a model-based controller for trunk FES. The model also gives information on the trunk in unique conditions, normally not observable in able-bodied subjects (ie, subject only to extensor muscles contraction).

Hydrogelation and self-assembly of Fmoc-tripeptides: unexpected influence of sequence on self-assembled fibril structure, and hydrogel modulus and anisotropy

The self-assembly and hydrogelation properties of two Fmoc-tripeptides [Fmoc = N-(fluorenyl-9-methoxycarbonyl)] are investigated, in borate buffer and other basic solutions. A remarkable difference in self-assembly properties is observed comparing Fmoc-VLK(Boc) with Fmoc-K(Boc)LV, both containing K protected by N(epsilon)-tert-butyloxycarbonate (Boc). In borate buffer, the former peptide forms highly anisotropic fibrils which show local alignment, and the hydrogels show flow-aligning properties. In contrast, Fmoc-K(Boc)LV forms highly branched fibrils that produce isotropic hydrogels with a much higher modulus (G' > 10(4) Pa), and lower concentration for hydrogel formation. The distinct self-assembled structures are ascribed to conformational differences, as revealed by secondary structure probes (CD, FTIR, Raman spectroscopy) and X-ray diffraction. Fmoc-VLK(Boc) forms well-defined beta-sheets with a cross-beta X-ray diffraction pattern, whereas Fmoc-KLV(Boc) forms unoriented assemblies with multiple stacked sheets. Interchange of the K and V residues when inverting the tripeptide sequence thus leads to substantial differences in self-assembled structures, suggesting a promising approach to control hydrogel properties.

A hyperstable neural network for the modelling and control of nonlinear systems

A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.

Parallelism in control

A parallel structure is suggested for feedback control systems. Such a technique can be applied to either single or multi-sensor environments and is ideally suited for parallel processor implementation. The control input actually applied is based on a weighted summation of the different parallel controller values, the weightings being either fixed values or chosen by an adaptive decision-making mechanism. The effect of different controller combinations is a field now open to study.

Neural networks for linear control: an analysis

This paper considers the use of radial basis function and multi-layer perceptron networks for linear or linearizable, adaptive feedback control schemes in a discrete-time environment. A close look is taken at the model structure selected and the extent of the resulting parameterization. A comparison is made with standard, nonneural network algorithms, e.g. self-tuning control.

A critique of neural networks for discrete-time linear control

This paper discusses the use of multi-layer perceptron networks for linear or linearizable, adaptive feedback.control schemes in a discrete-time environment. A close look is taken at the model structure selected and the extent of the resulting parametrization. A comparison is made with standard, non-perceptron algorithms, e.g. self-tuning control, and it is shown how gross over-parametrization can occur in the neural network case. Because of the resultant heavy computational burden and poor controller convergence, a strong case is made against the use of neural networks for discrete-time linear control.

Synthesis, structure and magnetic properties of mono- and di-nuclear nickel(II) thiocyanate complexes with tridentate N3 donor Schiff bases

The 1:1 condensation of N-methyl-1,3-diaminopropane and N,N-diethyl-1,2-diminoethane with 2-acetylpyridine, respectively at high dilution gives the tridentate mono-condensed Schiff bases N-methyl-N'-(1-pyridin-2-yl-ethylidene)-propane-1,3-diamine (L-1) and N,N-diethyl-N'-(1-pyridin-2-yl-ethylidene)-ethane-1,2-diamine (L-2). The tridentate ligands were allowed to react with methanol solutions of nickel(II) thiocyanate to prepare the complexes [Ni(L-1)(SCN)(2)(OH2) (1) and [{Ni(L-2)(SCN)}(2)] (2). Single crystal X-ray diffraction was used to confirm the structures of the complexes. The nickel(II) in complex 1 is bonded to three nitrogen donor atoms of the ligand L-1 in a mer orientation, together with two thiocyanates bonded through nitrogen and a water molecule, and it is the first Schiff base complex of nickel(II) containing both thiocyanate and coordinated water. The coordinated water initiates a hydrogen bonded 2D network. In complex 2, the nickel ion occupies a slightly distorted octahedral coordination sphere, being bonded to three nitrogen atoms from the ligand L-2, also in a mer orientation, and two thiocyanate anions through nitrogen. In contrast to 1, the sixth coordination site is occupied by a sulfur atom from a thiocyanate anion in an adjacent molecule, thus creating a centrosymmetric dimer. A variable temperature magnetic study of complex 2 indicates the simultaneous presence of zero-field splitting, weak intramolecular ferromagnetic coupling and intermolecular antiferromagnetic interactions between the nickel(II) centers.

Synthesis, crystal structure and magnetic properties of three unprecedented tri-nuclear and one very rare tetra-nuclear copper(II) Schiff-base complexes supported by mixed azido/phenoxo/nitrato or acetato bridges

Three novel mixed bridged trinuclear and one tetranuclear copper(II) complexes of tridentate NNO donor Schiff base ligands [Cu-3(L-1)(2)(mu(LI)-N-3)(2)(CH3OH)(2)(BF2)(2)] (1), [Cu-3(L-1)(2)(mu(LI)-NO3-I kappa O.2 kappa O')(2)] (2), [Cu-3(L-2)(2)(mu(LI)-N-3)(2)(mu-NOI-I kappa O 2 kappa O')(2)] (3) and [Cu-4(L-3)(2)(mu(LI)-N-3)(4)(mu-CH3COO-I kappa O 2 kappa O')(2)] (4) have been synthesized by reaction of the respective tridentate ligands (L-1 = 2[1-(2-dimethylamino-ethylimino)-ethyl]-phenol, L-2 = 2[1-(2-diethylamino-ethylimino)-ethyl]-phenol, L-3 = 2-[1-(2-dimethylamino-ethylimino)-methyl]-phenol) with the corresponding copper(II) salts in the presence of NaN3 The complexes are characterized by single-crystal X-ray diffraction analyses and variable-temperature magnetic measurements Complex 1 is composed of two terminal [Cu(L-1)(mu(LI)-N-3)] units connected by a central [Cu(BF4)(2)] unit through nitrogen atoms of end-on azido ligands and a phenoxo oxygen atom of the tridentate ligand The structures of 2 and 3 are very similar, the only difference is that the central unit is [Cu(NO1)(2)] and the nitrate group forms an additional mu-NO3-I kappa O 2 kappa O' bridge between the terminal and central copper atoms In complex 4, the central unit is a di-mu(L1)-N-3 bridged dicopper entity, [Cu-2(mu(L1)-N-3)(2)(CH3COO)(2)] that connects two terminal [Cu(L-3)(mu(L1)-N-3)] units through end-on azido; phenoxo oxygen and mu-CH3COO-1 kappa O center dot 2 kappa O' triple bridges to result in a tetranuclear unit Analyses of variable-temperature magnetic susceptibility data indicates that there is a global weak antiferromagnetic interaction between the copper(II) ions in complexes 1-3, with the exchange parameter J of -9 86, -11 6 and -19 98 cm(-1) for 1-3, respectively In complex 4 theoretical calculations show the presence of an antiferromagnetic coupling in the triple bridging ligands (acetato, phenoxo and azido) while the interaction through the double end-on azido bridging ligand is strongly ferromagnetic.

Control strategy for Boolean input systems

The purpose of this paper is to design a control law for continuous systems with Boolean inputs allowing the output to track a desired trajectory. Such systems are controlled by items of commutation. This type of systems, with Boolean inputs, has found increasing use in the electric industry. Power supplies include such systems and a power converter represents one of theses systems. For instance, in power electronics the control variable is the switching OFF and ON of components such as thyristors or transistors. In this paper, a method is proposed for the designing of a control law in state space for such systems. This approach is implemented in simulation for the control of an electronic circuit.

Structure adaptation of linear MMSE adaptive filters

The tap-length, or the number of the taps, is an important structural parameter of the linear MMSE adaptive filter. Although the optimum tap-length that balances performance and complexity varies with scenarios, most current adaptive filters fix the tap-length at some compromise value, making them inefficient to implement especially in time-varying scenarios. A novel gradient search based variable tap-length algorithm is proposed, using the concept of the pseudo-fractional tap-length, and it is shown that the new algorithm can converge to the optimum tap-length in the mean. Results of computer simulations are also provided to verify the analysis.

Model predictive control using dynamic integrated system optimisation and parameter estimation (DISOPE)

DISOPE is a technique for solving optimal control problems where there are differences in structure and parameter values between reality and the model employed in the computations. The model reality differences can also allow for deliberate simplification of model characteristics and performance indices in order to facilitate the solution of the optimal control problem. The technique was developed originally in continuous time and later extended to discrete time. The main property of the procedure is that by iterating on appropriately modified model based problems the correct optimal solution is achieved in spite of the model-reality differences. Algorithms have been developed in both continuous and discrete time for a general nonlinear optimal control problem with terminal weighting, bounded controls and terminal constraints. The aim of this paper is to show how the DISOPE technique can aid receding horizon optimal control computation in nonlinear model predictive control.

Correlations of control variables in variational data assimilation

Variational data assimilation systems for numerical weather prediction rely on a transformation of model variables to a set of control variables that are assumed to be uncorrelated. Most implementations of this transformation are based on the assumption that the balanced part of the flow can be represented by the vorticity. However, this assumption is likely to break down in dynamical regimes characterized by low Burger number. It has recently been proposed that a variable transformation based on potential vorticity should lead to control variables that are uncorrelated over a wider range of regimes. In this paper we test the assumption that a transform based on vorticity and one based on potential vorticity produce an uncorrelated set of control variables. Using a shallow-water model we calculate the correlations between the transformed variables in the different methods. We show that the control variables resulting from a vorticity-based transformation may retain large correlations in some dynamical regimes, whereas a potential vorticity based transformation successfully produces a set of uncorrelated control variables. Calculations of spatial correlations show that the benefit of the potential vorticity transformation is linked to its ability to capture more accurately the balanced component of the flow.