Andrew Thomas Shenton

An interactive parameter space method for robust performance in mixed sensitivity problems

This paper presents an interactive graphical method to determine the set of fixed-order stabilizing controllers achieving robust performance, in the mixed sensitivity framework. The method is limited to single-input/single-output (SISO) systems but offers significant advantages over traditional loop gain shaping methods such as H/sup /spl infin// and /spl mu/-synthesis. It can handle pure time delays in an exact manner and the weighting functions need not be rational. The technique translates frequency-domain weighting functions and stability constraints into the parameter space and thus gives the user more insights into the design than conventional methods. By virtue of producing the required parameter space region for the frequency response criteria, subsequent optimization of secondary objectives is possible. The controllers obtained are of lower order for comparable performance than those produced by current H/sup /spl infin// and /spl mu/-synthesis techniques. The method is particularly well-suited to robust control problems where frequency-domain constraints emerge from the analysis of nonparametric uncertainties in the system and also to control problems where the frequency domain loop shaping is used to achieve time-domain specifications.

Interactive control system design by a mixed H/sup /spl infin//-parameter space method

This paper presents an interactive graphical method to determine sets of stabilizing controllers satisfying any combination of constraints on the sensitivity, complementary sensitivity, and input sensitivity transfer functions. The method is limited to single-input/single-output systems but offers significant advantages over current H/sup /spl infin// methods. It can handle pure time delays in an exact manner. The weighting functions need not be rational. By virtue of producing the required parameter space region for the frequency response criteria, subsequent direct time-domain optimization is possible. The controllers obtained are of lower order for comparable performance than those produced by current H/sup /spl infin// techniques. The method is particularly well suited to robust control problems, where frequency domain constraints emerge from the analysis of uncertainties in the system, and also to suboptimal problems, where the frequency-domain loop shaping is used to achieve time-domain specifications.

Interactive parameter space design for robust performance of MISO control systems

This paper presents a method for the design of nonconservative low-order controllers achieving robust performance in the case of multi-input single-output parallel structure plants subject to unstructured uncertainty. The first step is the analytical generation of gain-phase controller bounds, as in quantitative feedback theory (QFT). Then, to avoid the difficult step of QFT loop shaping, which often produces high-order controllers, these bounds are translated into the controller parameter space where the iterative design of low fixed order controllers takes place. This, as well as the design transparency offered by this technique, constitutes appreciable advantages over the other popular robust performance design method of /spl mu/-synthesis. Other important features are the fact that no extra conservatism is introduced by the method presented and the fact that the method is directly compatible with a sequential loop closing strategy. Finally, the direct search optimization of any additional secondary criteria is possible.

Automotive Driveline Modelling, Inverse-Simulation and Compensation

A nonlinear automotive driveline model and its inverse simulation are developed. The model contains four inertias comprising engine, clutch, transmission, coupling, and wheels. In this paper both nonlinear effects arising from the clutch and backlash are considered. The backlash in the proposed model is sandwiched between the compliance of the clutch and the compliance of the drive shafts. A basic simulation approach is outlined for obtaining the Horowitz linear time-invariant equivalent (LTIE) of the automotive driveline model by a nonparametric identification using a Windowed Fourier Transformation (WFT) method. The inverse simulation model is used as a compensator and is shown to achieve calibrated uncertainty reductions over the crossover frequency range. The reduction in the equivalent linear uncertainty of the nonlinearity available from the inverse compensation is demonstrated by the WFT analysis.

Automotive driveline control by a nonlinear nonparametric QFT method

A new nonlinear Quantitative Feedback Theory (QFT) methodology is presented and applied to the control of the automotive driveline with nonlinear clutch and backlash. A driveline model is presented which incorporates the nonlinear clutch characteristics and the coupling backlash realistically sandwiched by compliant inertias. The model gives responses that are representative of typical driveline systems, with the backlash accentuating the magnitude of oscillatory shuffle response. A Nonparametric (NP) identification method is given for directly developing the QFT templates of the Linear Time-Invariant Equivalent (LTIE) plant model set. The identification uses a Discrete Fourier Transform (DFT) to convert the system data to the frequency domain (FD). To mitigate against windowing errors the frequency response (FR) data is locally smoothed by a sliding frequency weighting function. The LTIE set is obtained as set of NP identified models obtained directly from typical vehicle experimental input-output test data. Non-minimum phase (NMP) QFT bounds are determined from the nominal NP plant by determining the Hubert transform of the NMP plant. The controller design methodology is applied to the model and it is shown that predefined robust tracking and disturbance response performance specifications can be systematically obtained, without subsequent heuristic parameter tuning.

Nonparametric Driveline Identification and Control

A nonparametric identification and control approach to active driveline control is investigated. A nonlinear model incorporating nonlinear clutch characteristics and driveline backlash is developed. An approach using short time Fourier transforms for nonparametric frequency response identification and smoothing is presented. The identification method is used to identify a driveline model both with and without backlash present. Two nonparametric controller design techniques are employed. A parameter space method is used to design a PI controller and an analytic-optimisation mixed sensitivity H∞ method to design a high order controller for the cases with and without backlash. The controllers designed for the system without backlash proved unstable when applied to the system with it present. In contrast, both the PI controller and the higher order controller from the new technique give good control of the fully nonlinear driveline. The new approach should be directly applicable to experimentally produced time series data, which potentially allows a systematic controller calibration without the need for extensive in-vehicle tuning.