A stability analysis of controllers subject to amplitude and rate constraints

This paper investigates the problem of actuators subject to both amplitude and rate constraints. Previous works studied these saturation types separately. Here a compensation structure catering to both constraints is proposed. Realizability of the compensator and its necessary conditions to maintain linear stabilities are presented, conforming to other established results. A simple design method of combining two individually selected compensators is proposed. Discussions focus on analysis of nonlinear stability when both saturations occur simultaneously. The analysis resorts to an approximation of frequency domain methods, enabling necessary conditions for asymptotic stability to be investigated A numerical example demonstrates the procedures and success of the proposed method.published_or_final_versio

Indirect adaptive control for systems with an unknown dead zone

Dead-zone inverse methods have been used in adaptive control schemes to compensate for systems with an unknown dead zone. The problem with these techniques is that steady state error may still exist. It is shown in this paper that controller with integrating action can be used to remove steady state error arising from the unknown dead zone. By treating the effect of an unknown dead zone as a bounded disturbance being injected into the system, a plant parametrization that is linear in a set of unknown parameters is developed and the estimation algorithm is proposed. A novel feature of the adaptive controller proposed here is the integrating action in the controller. Stability analysis shows that the adaptive scheme ensures boundedness of all closed-loop signals and eliminates tracking errors. As illustrated in a simulation example, the proposed adaptive controller is simple to implement and accurate tracking can be achieved.published_or_final_versio

A general actuator saturation compensator in the continuous-time domain.

A general compensator for actuator saturation that includes existing ones as special cases is presented. The conditions that must be satisfied for the implementation of the compensator are given. It is shown that for a given system there exists an arbitrarily large number of compensators such that the compensated system is absolute stable. The result suggests that a compensator can be derived from systems that is known to be absolute stable. If the system is unknown, then the compensator may have to be designed iteratively until the effective set-point is acceptable.published_or_final_versio

Control synthesis versus saturation compensation for systems with rate and amplitude constraints

A control synthesis theory was proposed by Horowitz (1984) to design a `three degrees of freedom' controller for rate and amplitude constrained systems. Following anti-reset windup techniques, we (1997) proposed a saturation compensation structure to design compensators for given linear controllers. It is shown that the compensator can be reformulated in terms of the control synthesis theory. Conversely, the `three degrees of freedom' controller is a special case of the compensator construction. From this analysis, shortcomings of the control synthesis theory are exposed and improvements using the compensator structure are discussed and illustrated by an example.published_or_final_versio

Multivariable saturation compensator designs through singular value decompositions

Using a general saturation compensation framework for multi-input multi-output control systems subject to actuator constraints, a simple expression relating the singular values of the uncompensated system, the compensator and the compensated system is established. This singular value decomposition offers numerous possibilities in shaping the desired responses for the saturation compensated system. Two specific practical designs are proposed from the SVD analysis. Another two possibilities are exposed for further theoretical development. Simulated example demonstrates the feasibility and practicality of the proposed designs.published_or_final_versio

Modelling of river discharges using neural networks derived from support vector regression

Neural networks are often used to model complex and nonlinear systems, as they can approximate nonlinear systems with arbitrary accuracy and can be trained from data. Amongst the neural networks, Associative Memory Networks (AMNs) are often used, since they are less computation intensive, and yet good generalization results can be obtained. However, this can only be achieved if the structure of the AMNs is suitably chosen. An approach to choose the structure of the AMNs is to use the Support Vectors (SVs) obtained from the Support Vector Machines. The SVs are obtained from a constrained optimization for a given data set and an error bound. For convenience, this class of AMNs is referred to as the Support Vector Neural Networks (SVNNs). In this paper, the modelling of river discharges with rainfall as input using the SVNN is presented, from which the nonlinear dynamic relationship between rainfall and river discharges is obtained. The prediction of river discharges from the SVNN can give early warning of severe river discharges when there are heavy rainfalls.published_or_final_versio

Lifestyle health promotion interventions for the nursing workforce: A systematic review

Aims and objectives. Study aims were to identify the efficacy of lifestyle health promotion interventions intended to improve behavioural health risk factors and/or behavioural or clinical outcomes of working-age nurses. Background. Nurses constitute around half the health workforce but global shortages and an ageing profile challenge future supply. The occupational hazards and stresses of nursing are well known. Health promotion, possibly workplace-based, presents opportunities to safeguard the health of nurses. Design. This was a systematic review undertaken in line with guidance for reviews in health care. Methods. Seven electronic databases were searched from 2000-2011 and references of relevant papers. Two reviewers independently reviewed and critiqued retrieved papers and extracted data. Methodological features were described using the CONSORT checklists; risk of bias was assessed using the Cochrane Handbook classification. Results. With design inclusion criteria relaxed to include an uncontrolled trial, only three intervention studies were retrieved, from the United States, Canada and Taiwan. All had limitations and high risk of bias, but benefits were reported. Outcomes included fewer cigarettes smoked during the intervention period, down from mean (SD) 20 (8)-12 (9) per day (p<0·001); significantly reduced fat mass (0·68 vs. 0·07kg; p=0·028); and significant gains across a battery of fitness assessments. The paucity of work focused on nurses' health behaviours was the important finding. Conclusion. The workplace is a potentially fruitful location for health promotion intervention but nurses have seldom been recognised as a target participant group. Given the international priority ascribed to nursing workforce retention, this is a missed opportunity for occupational health planning. Potential benefits to nurses' welfare and well-being may accrue from well-designed intervention studies. Relevance to clinical practice. Nurse leaders have a key role in driving recognition, spearheading commitment and development of targeted, whole-organisation programmes to promote health profile improvement for the nursing workforce. © 2012 Blackwell Publishing Ltd

Stability of systmes with deadzone nonlinearity

This paper studies the stabilization of control systems with deadband nonlinearity of unknown characteristics. A novel approach to treat the deadband is first proposed using techniques of saturation compensation, assuming crude estimates of gains and bounds for the saturation limiter. Stability of the compensated system is analyzed, revealing that for systems of conditional stability in the presence of deadzone nonlinearity, their stabilization is not possible for small inputs. However, proper stabilization always exists for regulatory control of large enough input magnitude. Simulated examples are given to illustrate the main results.published_or_final_versio

Fault estimation for a class of nonlinear dynamical systems

In this paper, model based fault estimation for a class of nonlinear dynamical systems is investigated. The state of the system is assumed unavailable, and a nonlinear observer is used to estimate the state. In the observer, neurofuzzy network is used as the approximator to estimate faults. The network is trained on-line and the convergence of the proposed learning algorithm is established. Abrupt fault and incipient fault are analyzed in the paper and they can be estimated accurately using neurofuzzy network with the proposed learning algorithm.published_or_final_versio

Online fault detection and isolation of nonlinear systems

This paper describes an online fault detection scheme for a class of nonlinear dynamic systems with modelling uncertainty and inaccessible states. Only the inputs and outputs of the system can be measured. The faults are assumed to be functions of the state, instead of the output and the input of the system. A nonlinear online approximator using dynamic recurrent neural network is utilised to monitor the faults in the system. The construction and the learning algorithm of the online approximator are presented. The stability, robustness and sensitivity of the fault detection scheme under certain assumptions are analysed. An example demonstrates the efficiency of the proposed fault detection scheme.published_or_final_versio