This paper proposes an adaptive control for vehicle active suspensions with unknown nonlinearities (e.g., nonlinear springs and piecewise dampers). A prescribed performance function that characterizes the convergence rate, maximum overshoot, steady-state error is incorporated into design to stabilize vertical pitch motions, such both transient suspension response are guaranteed. Moreover, a novel law used achieve precise estimation of essential parameters mass body moment inertia motion),...

This paper presents a new adaptive fuzzy control scheme for active suspension systems subject to input time delay and unknown nonlinear dynamics. First, predictor-based compensation is constructed address the effect of in closed-loop system. Then, logic system (FLS) employed as function approximator nonlinearities. Finally, enhance transient response, novel parameter estimation error-based finite-time (FT) algorithm developed online update FLS weights, which differs from traditional methods,...

This paper presents a novel control strategy for nonlinear uncertain vehicle active suspension systems without using any function approximators [e.g., neural networks (NNs) or fuzzy logic (FLSs)]. Unlike previous results that neglect the effect of actuator dynamics, this incorporates dynamics hydraulic is used to create required forces into controller design. To address nonlinearities system, an approximation-free method introduced. In method, widely NNs and FLSs are not needed. leads...

Most of the existing control methods for servo systems driven by hydraulic actuators have been developed using a backstepping scheme and assuming that all system states (including internal signals) are measurable. In this paper, we propose new design method high-order with actuator dynamics, where is avoided only output (e.g., motion displacement) required implementation. For purpose, model first transformed into canonical form, unknown dynamics in lumped as one term. Then, introduce simple...

Although adaptive control design with function approximators, for example, neural networks (NNs) and fuzzy logic systems, has been studied various nonlinear the classical laws derived based on gradient descent algorithm σ-modification or e-modification cannot guarantee parameter estimation convergence. These nonconvergent learning methods may lead to sluggish response in system make tuning complex. The aim of this paper is propose a new strategy driven by error alternative servo systems....

In this paper, we propose an alternative, simple, yet efficient estimation method to handle unknown dynamics and external disturbances for motion control of robotic systems. An system estimator (USDE) is first proposed by introducing filter operations simple algebraic calculations, where the Coriolis/gravity can be estimated simultaneously. specific case only disturbance unknown, a further modified (MUDE) introduced. These USDE MUDE easily implemented their parameter tuning straightforward...

A reliable, efficient, and simple control is presented validated for a quarter-car active suspension system equipped with an electro-hydraulic actuator. Unlike the existing techniques, this does not use any function approximation, e.g., neural networks (NNs) or fuzzy-logic systems (FLSs), while unmolded dynamics, including hydraulic actuator behavior, can be accommodated effectively. Hence, heavy computational costs tedious parameter tuning phase remedied. Moreover, both transient...

This paper proposes a new control approach for full-car active suspension systems with unknown nonlinearities.The main advantage of this is that the uncertainties and nonlinearities in system can be handled without using any function approximator (e.g.neural networks (NNs), fuzzy logic (FLSs)), associated online adaptation.Hence, heavy computational cost sluggish learning phase to achieve convergence remedied.To maintain transient steady-state responses, coordinate error transformation...

This article presents a novel proportional-integral approximation-free control (PIAFC) for nonlinear robotic systems with unknown Coriolis and gravity dynamics. One key merit is to transform the original motion tracking problem into an alternative system stabilization by introducing prescribed performance functions (PPFs) associated error transformation. Another idea develop compensation mechanism incorporate it synthesis, such that converges zero in steady-state. In this framework, only...

This article proposes a novel control method for vehicle active suspension systems in the presence of time-varying input delay and unknown nonlinearities. An system dynamics estimator (USDE), which employs first-order low-pass filter operations has only one tuning parameter, is constructed to deal with With this USDE, widely used function approximators (e.g., neural networks fuzzy-logic systems) are not needed, intermediate variables observer traditional estimators required. reduced...

This article studies the multi- [Formula: see text] controls for input-interference nonlinear systems via adaptive dynamic programming (ADP) method, which allows multiple inputs to have individual selfish component of strategy resist weighted interference. In this line, ADP scheme is used learn Nash-optimization solutions system such that performance indices can reach defined Nash equilibrium. First, given and equilibrium defined. An neural network (NN) observer introduced identify dynamics....

This paper proposes a new robust adaptive law for control of vehicle active suspensions with unknown dynamics (e.g. non-linear springs and piece-wise dampers), where precise estimation essential parameters mass body, moment inertia the pitch motions) may be achieved. is designed by introducing novel leakage term parameter error, such that exponential convergence both tracking error proved simultaneously. Appropriate comparisons several traditional laws gradient σ-modification method)...

This brief addresses the emission reduction of spark ignition engines by proposing a new control to regulate air-fuel ratio (AFR) around ideal value. After revisiting engine dynamics, AFR regulation is represented as tracking injected fuel amount. allows take film dynamics into consideration and simplify design. The lumped unknown in formulation are online estimated suggesting effective system estimator. variable can be superimposed on commercially configured, well-calibrated gain scheduling...

In this paper, a simple but effective control scheme is proposed for bilateral teleoperation systems with variable communication time-delays. The robotic models are first reformulated and an unknown system dynamics estimator (USDE) constructed to estimate the lumped uncertainties without using accelerations, where only low-pass filtering operations trivial algebraic calculations used. USDE then incorporated into controller design compensate effects of uncertainties. stability closed-loop...

The Hammerstein model has proven its ability for modeling many industrial servo systems, but the corresponding parameter estimation remains as a challenging problem, especially purpose of achieving fast convergence. This paper presents fixed-time (FxT) adaptive scheme systems with an asymmetric dead-zone to ensure convergence estimated parameters in fixed-time. A continuous piecewise linear (CPL) function is adopted nonlinear dynamics remedy use intermediate variable. To avoid using system...

This brief presents a novel one-step adaptive parameter estimation framework for identification of unknown asymmetric dead-zone characteristic parameters (e.g., width and slopes) in the sandwich systems, which avoids using intermediate variables or carrying out two-step recursive procedure. By applying continuous piecewise linear neural network (CPLNN), nonlinearities can be represented into parameterized form, where derived based on online updated CPLNN weights. Moreover, after representing...

Abstract Although optimal regulation problem has been well studied, resolving tracking control via adaptive dynamic programming (ADP) not completely resolved, particularly for nonlinear uncertain systems. In this paper, an online learning method is developed to realize the design motor driven systems (NMDSs), which adopts concept of ADP, unknown system estimator (USDE), and prescribed performance function (PPF). To end, USDE in a simple form first proposed address NMDSs with bounded...

This article focuses on solving the optimal control problem for magnetorheological fluid (MRF)-based semiactive suspension (SAS) systems with input saturation and time-varying delay. A robust switched H <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\infty$</tex-math></inline-formula> method is proposed in this work based Takagi–Sugeno (T–S) fuzzy theory. novel hybrid model that incorporates both flow...

The Hammerstein model has been successfully used to various industrial systems, while the parameter estimation of such a is difficult. In this article, novel adaptive scheme proposed for continuous-time with an asymmetric dead-zone, which avoids using immeasurable intermediate variables and system states. First, continuous piecewise linear neural network adopted reformulate dead-zone dynamics, thus facilitating derivation characteristic parameters. By applying K-filter operation, integrated...