Showing papers in "Automatica in 1992"

TL;DR: In this paper, the authors focus on the promise of artificial neural networks in the realm of modelling, identification and control of nonlinear systems and explore the links between the fields of control science and neural networks.

TL;DR: It is shown that, while straightforward application of the linearization theory to a non-minimum phase system results in a system with a linear input-output response but unstable internal dynamics, designing a feedback control based on a minimum phase approximation to the true system results with desirable properties such as bounded tracking and asymptotic stability.

TL;DR: Two practical methods are presented for predicting the existence and the location of chaotic motions as a function of the system parameters, when the system structure is fixed by rather general input-output or state equation models.

TL;DR: This paper describes some features that may be included in the next generation of PID controllers, which seem technically feasible with the increased computing power that is now available in single-loop controllers.

TL;DR: This paper identifies a new type of universal fuzzy controller that is independent of any controllable process P and can be controlled by some fuzzy controller in b.

TL;DR: From the structure of the problem it follows that irrespective of the order of the approximation, a feasible sampled-data controller can be found which has the same order as the system, and this problem can be solved to any degree of accuracy.

TL;DR: This optimal control model of cancer chemotherapy constructs drug schedules that most effectively reduce the size of a tumour after a fixed period of treatment has elapsed using an established numerical solution technique known as control parametrization.

TL;DR: It is shown that with external torques, the equations for the rigid body with momentum wheels are Hamiltonian with respect to a Lie-Poisson bracket structure and these equations are shown to generalize the dual-spin equations.

TL;DR: In this paper, a class of algorithms for the problem of system identification in ~ are investigated, and conditions in terms of properties of the window functions are derived, which guarantee robust convergence of the algorithms.

TL;DR: The suitability of the artificial neural network methodology for solving some process engineering problems is discussed and the technique to provide estimates of difficult to measure quality variables is demonstrated by application to industrial data.

TL;DR: An iterative learning control scheme is presented for a class of nonlinear dynamic systems which includes holonomic systems as its subset and neither uses derivative terms of feedback errors nor assumes external input perturbations as a prerequisite.

TL;DR: In this paper, the authors present results on frequency-dependent tools for analysis, structure selection and design of control systems, including relationships between the relative gain array (RGA) and right half plane zeros, and the use of the RGA as a sensitivity measure with respect to individual element uncertainty and diagonal input uncertainty.

TL;DR: The robust output tracking control problem of general nonlinear multi-input multi-output (MIMO) systems is discussed and it is shown that for unperturbed dynamics, the sliding phase of the SMC applications have a direct correspondence to the I/O linearization operations.

TL;DR: This paper addresses the motion and force control problem of multiple robot arms manipulating a cooperatively held object and shows that effective force regulation can be achieved even if little model information is available.

TL;DR: By using a simple exact linearization design method for scalar nonlinear control systems, a nonlinear excitation control of synchronous generator is proposed, which is new and effective for engineering.

TL;DR: This paper shows that it is possible to synthesize a live, bounded, and reversible PN and to use that net description for the control of a medium sized FMS, and guarantees that the desirable properties of liveness, boundedness, and reversibility are present in the resulting net.

TL;DR: A nonlinear adpative controller is designed, which is based on the nonlinear discretized model, and its performance is illustrated by simulation results on a fixed bed anaerobic waste water treatment process.

TL;DR: The output-nulling, unknown-input and composite subspaces are defined for singular systems, with recursions given for their computation, and the notions of composite preimage and composite image are introduced.

TL;DR: Simulation results are presented to both verify the theoretical analysis and relate the new control law with GPC, which yields stable closed-loop systems under sharp conditions.

TL;DR: It is shown that the numerator coefficients of the optimal approximant satisfy a weighted least squares problem and, on this basis, a two-step iterative algorithm is developed combining a least squares solver with a gradient minimizer.

TL;DR: A simple complete analytical restriction-free parametric solution with complete and explicit freedom of matrix equation AV + BW = EVF is presented and an approach for eigenstructure assignment for continuous descriptor system Ex = Ax + Bu via descriptor-variable feedback u = Kx is proposed.

TL;DR: The global stability of the proposed model reference adaptive control scheme is established subject to the assumption that the nonlinearity can be represented exactly by the linear spline function with a given set of breakpoints.

TL;DR: It is shown that a discrete control using state measurements based on Euler approximations for the systems response can achieve arbitrary tracking accuracy.

TL;DR: A discrete-time indirect adaptive control algorithm which contains a constrained gradient parameter estimator and a pole assignment control law synthesis module and it is shown that global robustness properties still hold when this simple algorithm is applied to systems with bounded disturbances and arbitrarily small fast parasitic dynamics.

TL;DR: It is now possible to determine the strategy which minimises fuel consumption by considering only strategies of optimal type, and for a given sequence of throttle settings it is shown that fuel consumption is minimised if the settings are changed only when the velocity reaches one of the critical values.

TL;DR: This paper provides a brief summary of the current state of the theory of 2-D implicit systems and suggests that the implicit models are more suited to the description of naturally occurring two-dimensional systems, such as are described by the hyperbolic equation and the heat equation.

TL;DR: A simple method for the automatic tuning of PID controllers in closed loop is proposed, where the amplitude and frequency of the oscillation are estimated and the control parameters are adjusted iteratively such that the closed loop transfer function from the controller reference to the process output attains a specified amplitude at the oscillations frequency.

TL;DR: It is shown how the pole-zero cancellation phenomenon is dependent upon the choice of weighting functions used in the problem formulation, and a particular construction of weighted function is given that gives the designer freedom to exploit or prevent the phenomenon.

TL;DR: This work states that the number of zeros of this system should be appropriate and they should be stable, and if these conditions are satisfied, the problem can easily be solved by eigenvalue and eigenvector assignment.

TL;DR: It is shown in particular that the LQ-optimal state feedback operator and its reachable restriction coincide whenever the unreachable state components are unobservable.