Search

Original iterative learning control (OILC) has been proved a powerful tool in dealing with the model-free control problems by repetitively corrections based on the control error. However, the steady-state error under widely-used proportional-type original iterative learning control (P-type OILC) is highly corresponded to the proportional learning gain, making the algorithm parameter-determined. Therefore, a new gradient-descent iterative learning control (GDILC) algorithm is proposed to achieve a parameter-free approach by simulating the gradient-descent process. First, GDILC problem is formulated mathematically. Next, the idea of the algorithm is proposed, the analyses of the convergence and the steady-state error are conducted and the algorithm is implemented. GDILC will generate a random correction with a gradient-descent upper bound, rather than a correction proportional to the error in P-type OILC. Finally, illustrative and application simulations are conducted to validate the algorithm. Results show that the algorithm will be convergent after adequate iterations under proper corrections. The steady-state error will be less affected by the algorithm parameters under GDILC than that under OILC. [ABSTRACT FROM AUTHOR]

This paper presents a combination of both the Takagi–Sugeno–Kang fuzzy controller and the advantage of reinforcement learning for the reduction in the effect of external disturbances and system uncertainties. A neural network is used for the implementation of a critic network; the parameters are updated using the Lyapunov criteria for avoiding local minima problems. The fewer learning parameters used helps online tuning of the controller by the critic network based on the reward function. MATLAB/Simulink is used for simulation of the proposed system under different conditions in the investigation of the performance of the proposed controller. The actor parameters are updated based on the change in the reward function error and a control function. Five different conditions, namely, no-load condition, sudden load-torque changes, system parameter uncertainty, sudden phase interruption, and the impact of noise have been studied. The proposed method was found to meet the high-speed response with the tracking error of ±2.23% for the tracking reference trajectory and tracking error of ±2.5% under constant load-torque disturbance. The test results were compared with two benchmark controllers for the verification of the effectiveness of the proposed controller. Simulation results showed the proposed method providing an adaptive and precise speed response. Therefore, it is suitable for non-linear and uncertain applications. [ABSTRACT FROM AUTHOR]

This paper investigates a new disturbance observer based non-singular fast terminal sliding mode control technique for the path tracking and stabilization of non-linear second-order systems with compound disturbance. The compound disturbance is comprised of both parametric and non-parametric uncertainties. While warranting fast convergence rate and robustness, it also dominates the singularity and complex-value number issues associated with conventional terminal sliding mode control. Furthermore, due to the estimation properties of the observer, knowledge about the bounds of the uncertainties is not required. The simulation results of two case studies, the velocity and path tracking of an autonomous underwater vehicle and the stabilization of a chaotic Φ6-Duffing oscillator, validate the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

Sufficient criteria for input-to-state stability (ISS) of fixed-point state-space interfered digital filters with generalized overflow non-linearities are presented. The generalized overflow non-linearities under consideration cover the usual types of overflow arithmetic employed in practice, such as saturation, zeroing, two's complement and triangular. The criteria not only ensure diminishing consequence of external interference but also confirm the asymptotic stability of the system when external interference disappears. The criteria are derived in the linear matrix inequality (LMI) framework. Simulation results are provided to illustrate the utility of the presented approach. With the help of one example, it is illustrated that the presented approach can lead to a less stringent ISS condition for the digital filters with saturation non-linearities compared with a previously reported approach. [ABSTRACT FROM AUTHOR]

It is a critical issue to maintain stability in high-speed railway vehicles and to ensure comfortable and safe driving. Multi-body models of railway vehicles have non-linear properties originated from the wheel–rail contact and characteristics of the suspension systems. The critical speed values at which the unstable oscillations and the amplitudes of the limit cycle-type vibrations take place vary by adjusting the design parameters; therefore, these effects on non-linear railway dynamics must be evaluated with a higher precision by using numerical and/or analytical methods to determine the bifurcation behavior. The main objective of this paper is to examine the non-linear phenomena in a railway bogie from a broad perspective, concentrating on non-linear analysis methods. Thus, non-linear equations of motion of a 12-degrees of freedom railway bogie involving dual wheelsets, non-linear wheel flange contact, heuristic non-linear creep model, and suspension system are solved in the time domain with small time steps by using ode23s (stiff/Mod.Rosenbrock) method. The critical speeds were calculated with respect to the effects of various lateral stiffness and damping coefficients. The bifurcation diagrams of the maximum lateral displacement of the leading wheelset were depicted within a wide speed range. In the case of the suspension parameter set where the subcritical/supercritical Hopf bifurcation takes place, the phase portraits and the symmetric/asymmetric oscillations of the leading wheelset at the critical speed were represented. The type of the Hopf bifurcation can be transformed from the subcritical state to the supercritical state by increasing the given suspension ratio. The Lyapunov exponents of the lateral displacement, lateral velocity, yaw angular displacement, and yaw angular velocity of the leading wheelset were evaluated above the critical speeds to examine chaotic motion. The effect of the suspension parameters on the non-linear dynamical behavior of the railway bogie at the stability limit and on the bifurcation type has been proved. [ABSTRACT FROM AUTHOR]

Networked control systems (NCSs) are commonly modelled by the switched systems involving exponential non-linearities. A challenging problem is to obtain a tight linear approximation of the mentioned non-linear models to derive analysis and design criteria in terms of linear matrix inequalities (LMIs), which can be easily handled using the well-established algorithms. The present paper introduces a novel procedure to achieve an improved polytopic over-approximation of the non-linearities emerged in the modelling of NCSs. Moreover, stability of the NCSs is analysed to verify the merits of the proposed method; to this end, a benchmark numerical example is presented to illustrate the superior performance of the suggested approximation scheme compared with the existing approaches in the literature. [ABSTRACT FROM AUTHOR]

Experiments to obtain input/output data for system identification of some systems can be conducted only with the controllers in action. Estimating an open-loop system model using closed-loop data offers many difficulties, particularly when noise is present in the measurements. In this paper, a new indirect non-linear system identification technique using a non-linear auto regressive moving average with exogenous input (NARMAX) structure and employing input/output data obtained from closed-loop experiments is described for the first time. Furthermore, a new method to estimate the linear multivariable open-loop transfer function from closed-loop data using an algebraic equation set is presented. The effectiveness of the proposed linear and non-linear identification approaches is illustrated by simulation studies on a non-linear physical system. [ABSTRACT FROM AUTHOR]

In this paper, a new non-linear optimal controller for the planar motion of an articulated vehicle is proposed. The main goal of the control system is to enhance the planar stability through active braking of the wheels. The controller was designed such that the states of the system are forced to follow the reference values using an input-constrained non-linear model including the longitudinal dynamics, the lateral dynamics and the yaw dynamics of both units. Using the state-dependent Riccati equation method a servomechanism was designed which results in reasonable trade-offs between the control efforts and the allowable state errors while representing the non-linearities of the system. Furthermore, the brake torques were derived from the state-dependent Riccati equation control law by imposing constraints on the control inputs. Through proper selection of a weighting matrix, the control system distributes the brake forces optimally among the axles considering the coupling between the longitudinal tyre forces and the lateral tyre forces. In order to evaluate the performance and the effectiveness of the proposed controller, simulations were performed using the non-linear vehicle model. Additionally, the robustness of the controller is evaluated by analysis of its performance in the presence of parameter uncertainties. The simulation results prove the efficacy of the proposed controller in improving the yaw–roll stability, the handling and the manoeuvrability of the tractor–semitrailer. [ABSTRACT FROM AUTHOR]

The system is often described as a series of blocks linked together in non-linear system identification. Such block-oriented models are built with static non-linear subsystems and linear dynamic systems. This paper deals with the parameter estimation of Hammerstein systems with piecewise non-linearities, which is a blocked-oriented model where a static non-linear blocking is followed by a linear dynamic system. The basic idea is as follows. The key term separation technique is applied initially, and then a corresponding auxiliary model is constructed. Hence, the identification problem of the system is converted to a non-linear function optimization problem over parameter space. Once again, the estimates of all the parameters are obtained by a proposed particle swarm optimization algorithm. Finally, compared with the existing methods, the simulation results confirm that the presented method is valid. Moreover, the presented method is further extended to estimate Hammerstein systems with discontinuity non-linearities. [ABSTRACT FROM AUTHOR]

A chattering-free condition is proposed as a sufficient condition for the sliding mode control with unidirectional auxiliary surfaces (UAS-SMC) strategy in a class of non-linear systems. With this condition, the UAS-SMC controller would enjoy the following properties: 1) chattering-free property of the control input; 2) enhanced approaching speed on the switching surfaces (except the original point); 3) no requirement to measure the derivatives; 4) a positively invariant set formed by UAS. The stability of the closed-loop system is demonstrated with a chattering-free UAS-SMC controller. Numerical simulation is given to illustrate the benefits and properties of the proposed controller and algorithm. [ABSTRACT FROM PUBLISHER]

In this note, a consensus fault detection architecture for non-linear dynamical systems is investigated in discrete-time framework. Here, the discussed faults include abrupt and incipient faults. Moreover, the unstructured modelling uncertainty is taken into account in a large-scale system, which can be modelled as a set of subsystems, and the physical interaction between subsystems is described by non-linear functions, which can be learned on-line by neural networks. A network of local fault detectors (LFDs) is built so that each LFD monitors a single subsystem. For some overlapping components of subsystems, a co-operative estimator (CE) is embedded to avoid the consensus-less or non-co-operative case with respect to the LFDs. With the help of the designed CE, LFDs can be allowed to decide collectively on the presence of faults and the capability of detecting faults affecting overlapping variables may be improved by receiving more local diagnostic information. In addition, the derivation of rigorous analytical results for detectability properties is provided. Simulation results are given to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

A mean-value model of a diesel engine with a variable-geometry turbocharger (VGT) and exhaust gas recirculation (EGR) is developed, parameterized, and validated. The intended model applications are system analysis, simulation, and development of model-based control systems. The goal is to construct a model that describes the gas flow dynamics including the dynamics in the manifold pressures, turbocharger, EGR, and actuators with few states in order to obtain short simulation times. An investigation of model complexity and descriptive capabilities is performed, resulting in a model that has only eight states. A Simulink implementation including a complete set of parameters of the model are available for download. To tune and validate the model, stationary and dynamic measurements have been performed in an engine laboratory. All the model parameters are estimated automatically using weighted least-squares optimization and it is shown that it is important to tune both the submodels and the complete model and not only the submodels or not only the complete model. In static and dynamic validations of the entire model, it is shown that the mean relative errors are 5.8 per cent or lower for all measured variables. The validations also show that the proposed model captures the system properties that are important for control design, i.e. a non-minimum phase behaviour in the channel EGR valve to the intake manifold pressure and a non-minimum phase behaviour, an overshoot, and a sign reversal in the VGT to the compressor mass flow channel, as well as couplings between channels. [ABSTRACT FROM AUTHOR]

In many applications within the fields of science, engineering, mathematics, and socio-economics, the ‘inverse problem' (i.e. the problem of determining a system's input from its output) is commonplace. The current paper presents a new concept for solving the inverse problem, which the authors call inverse dynamics compensation via ‘simulation of feedback control systems' (IDCS). IDCS is a numerical method that obtains an approximate inverse dynamic solution via a feedback control simulation, using only the forward dynamic model of the linear or non-linear system. Simulations are ideal environments for feedback control, in the sense that they can be completely noise-free and precisely known, so that the IDCS method can be tuned for the best possible performance. It is seen that IDCS can use the advantages of such ideal control simulation performance in the real world of physical implementations.This paper first introduces the basic idea of IDCS. Then, the effectiveness of the proposed method is demonstrated via three illustrative examples, in which the systems to be controlled have continuous and discontinuous non-linearities. IDCS performance is also investigated via physical experimentation on a non-linear servohydraulic test rig. Finally, extensions of the basic IDCS formulation are introduced which are potentially useful for the solution of additional practical problems. [ABSTRACT FROM PUBLISHER]

The magnetic levitation system's control problem is of considerable scientific interest because the system is open-loop unstable and highly non-linear, and the system's parameters are uncertain. In this paper, the system is formulated by a third-order non-linear differential equation. Based on this third-order non-linear system, the system is first linearized by applying the feedback linearization method. Then, the controller is designed based on a global sliding mode technique, which is able to stabilize a linearized system. Experimental results show that, compared with the classic proportional—integral—derivative (PID) controller, the proposed controller provides excellent transient response performance and the system is robust against the non-linear parameter perturbation. Further experiments show that the sampling period is an important parameter to the system robustness. The reason is explained theoretically, and the analysis shows that in the practical global sliding mode control (GSMC) system the smaller the sampling period is, the more robust the controller will be. [ABSTRACT FROM PUBLISHER]

This paper investigates the observer-based H∞ control problem of networked nonlinear systems with global Lipschitz non-linearities and for multiple sensors with different packet-loss rates. It is supposed that in the communication channels from the multiple sensors to the controller each sensor has an individual random data missing probability. The random packet loss is modelled as a Bernoulli distributed white sequence with a known conditional probability distribution. In the presence of random multiple packet losses, sufficient conditions for the existence of an observer-based feedback controller are derived, such that the closed-loop networked non-linear system is globally exponentially stable in the sense of mean square and a prescribed H∞ disturbance-rejection-attenuation performance is also achieved. A linear matrix inequality (LMI) approach for designing such observer-based H∞ controller is then presented. With the help of the LMI solvers, the observer-based H∞ controller can easily be obtained. Finally, a numerical example is used to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

It is well known that sliding mode control can give good transient performance and system robustness. However, due to the sensitivity of the sliding mode control before reaching the sliding surface, the presence of chattering may introduce problems to the tracking control of the system. In this paper, a scheme of fuzzy time-varying sliding mode controller with global robustness is proposed for a class of non-linear system with uncertainties. Since the proper fuzzy logic control is applied to the time-varying sliding surface, the state of the control system always lies on the sliding surface from the beginning of any initial state and the reaching phase is avoided. As a consequence, the system is robust with respect to external disturbances and parameter uncertainties. Furthermore, the chattering phenomenon, which is inherent to a conventional sliding mode control, is avoided by proper fuzzy tuning of the controller. The effectiveness of proposed controller is demonstrated through comparative simulations for a second-order non-linear uncertain system. [ABSTRACT FROM AUTHOR]

In this paper the problem of full linearisation, which means linearising the state and output equations simultaneously, is tackled. First we present necessary and sufficient conditions for the full linearisation of a class of non-linear systems; then a method to design a closed-loop observer for linearised system is presented. Finally, the developed technique is used to investigate the control of an activated-sludge process. Some simulation results are given. [ABSTRACT FROM PUBLISHER]