Designing control systems with bounded input is a practical consideration since realizable physical systems are limited by the saturation of actuators. The actuators' saturation degrades the performance of the control system, and in extreme cases, the stability of the closed-loop system may be lost. However, actuator saturation is typically neglected in the design of control systems, with compensation being made in the form of over-designing the actuator or by post-analyzing the resulting system to ensure acceptable performance..

Designing control systems with bounded input is a practical consideration since realizable physical systems are limited by the saturation of actuators. The actuators' saturation degrades the performance of the control system, and in extreme cases, the stability of the closed‐loop system may be lost. However, actuator's saturation is typically neglected in the design of control systems, with compensation being made in the form of overdesigning the actuator or by postanalyzing the resulting system to ensure acceptable performance. The bounded input control of fully actuated mechanical systems has been investigated in multiple studies, but it is not generalized for underactuated mechanical systems. This article proposes a systematic framework for finding the upper bound of control effort in underactuated systems, based on interconnection and the damping assignment passivity based control approach. The proposed …

Finding the general solution of partial differential equations (PDEs) is essential for controller design in newly developed methods. Interconnection and damping assignment passivity-based control (IDA-PBC) is one of such methods in which the solution to corresponding PDEs which are called matching equations is needed to apply it in practice. In this paper, these matching equations are transformed to corresponding Pfaffian differential equations. Furthermore, it is shown that upon satisfaction of the integrability condition, the solution to the corresponding third-order Pfaffian differential equation may be obtained quite easily. The method is applied to the PDEs of IDA-PBC in some benchmark systems such as Magnetic levitation system, Pendubot, and underactuated cable-driven robot to verify its applicability.

Interconnection and damping assignment passivity-based control scheme has been used to stabilize many physical systems such as underactuated mechanical systems through total energy shaping. In this method, some partial differential equations (PDEs) arisen by kinetic and potential energy shaping, shall be solved analytically. Finding a suitable desired inertia matrix as the solution of nonlinear PDEs related to kinetic energy shaping is a challenging problem. In this paper, a systematic approach to solve this matching equation for systems with one degree of underactuation is proposed. A special structure for desired inertia matrix is proposed to simplify the solution of the corresponding PDE. It is shown that the proposed method is more general than that of some reported methods in the literature. In order to derive a suitable desired inertia matrix, a necessary condition is also derived. The proposed method is applied to three examples, including VTOL aircraft, pendubot and 2D SpiderCrane system.

Increasing the speed and precision of operation in
cable robots is crucial due to the flexibility of cables. On the other hand, due to the frequent dynamical uncertainties present in
cable robots, providing a robust control method is necessary. The
performance of the fast terminal sliding mode (FTSM) controller
has been investigated in various systems, which ensures that
the state of the system is rapidly converged to the equilibrium
point at a finite time. In this paper, the FTSM controller has
been developed in such a way to be able to track the optimal robot path in the presence of dynamic uncertainties at different operating speeds. The main innovation of this paper is to provide
an adaptive robust control method for controlling cable robots and analyzing the stability of the closed-loop control system
based on the Lyapunov stability theory. In order to demonstrate
the effectiveness of the proposed controller, simulation results,
as well as experimental implementation on ARAS–CAM, a four
cable suspended robot with three degrees of freedom, has been
investigated and it is shown that the proposed controller can
provide suitable tracking performance in practice.

The UTDTR Robot is a human inspired robotic platform based on a two-wheeled mobile robot. This robot is designed for the purpose of dome shaped structures inspection and maintenance, and it is a tethered robot to stably climb steep surfaces on the top of dome structures. In this paper analysis and controller design of this robot modelled as a MIMO system is represented in order to provide the desired performance on the operating surface with minimum control effort and complexity. Two PID-based controllers are designed such that the stability and desired performance conditions are obtained. In the first design a fuzzy PID controller with self-tuning scale factors is designed to tune the controller gains is forwarded, while in the second approach a multi model gain scheduling controller based on conventional PID controller is considered. Finally, the effectiveness and simplicity of the proposed controller is verified through simulation, comparing the resulting closed loop transient and steady-state response to that of the previously proposed controllers.

The UTDTR Robot is a human inspired robotic platform based on a two-wheeled mobile robot. This robot is designed for the purpose of dome shaped structures inspection and maintenance, and it is a tethered robot to stably climb steep surfaces on the top of dome structures. In this paper analysis and controller design of this robot modelled as a MIMO system is represented in order to provide the desired performance on the operating surface with minimum control effort and complexity. Two PID-based controllers are designed such that the stability and desired performance conditions are obtained. In the first design a fuzzy PID controller with self-tuning scale factors is designed to tune the controller gains is forwarded, while in the second approach a multi model gain scheduling controller based on conventional PID controller is considered. Finally, the effectiveness and simplicity of the proposed controller is verified through simulation, comparing the resulting closed loop transient and steady-state response to that of the previously proposed controllers.

Tethered Segway is a robotic platform inspired by human climbers. It is a two-wheeled mobile platform tethered to the top of a structure in order to climb steep surfaces with varying slopes, such as domes. The unstructured environment may cause uncertainties in the dynamic behavior of the robot while operating on different parts of the dome. In this paper analysis and synthesis of a robust controller for a tethered Segway is presented in order to provide desired performance in the presence of uncertainties. To design the robust controller, structured and unstructured uncertainties of the model are encapsulated into a structured singular perturbation. A linear robust controller is designed such that the robust stability of the closed loop system is preserved in the presence of modeling uncertainties. Finally, the effectiveness of the proposed controller is verified through simulation by comparing its closed loop transient response and sufficiently suitable steady-state performance to that of a previously proposed LQR controller for the robot.

In this paper a gain scheduling method is proposed for robust model predictive control of a useful class of nonlinear discrete-time systems. The system is composed of a linear model perturbed by an additive state-dependent nonlinear term. Robust model predictive controllers are designed in the literature to compensate for the uncertainty of the system. In order to enlarge the region of convergence it is assumed that system has several equilibrium points and multiple robust controllers are designed. By switching between the controllers it is verified that the region of convergence shall be enlarged, while the overall stability of the system is preserved. In the proposed method, the stability analysis based on Lyapunov functions for each level set is performed, while state feedback control law is designed by minimization of a desired cost function formed in linear matrix inequalities. The simulation results show the applicability of the proposed method.

Time delays are encountered in many physical systems, and they usually threaten the stability and performance of closed-loop systems. The problem of determining all stabilising proportional-integral-derivative (PID) controllers for systems with perturbed delays is less investigated in the literature. In this study, the Rekasius substitution is employed to transform the system parameters to a new space. Then, the singular frequency (SF) method is revised for the Rekasius transformed system. A novel technique is presented to compute the ranges of time delay for which stable PID controller exists. This stability range cannot be readily computed from the previous methods. Finally, it is shown that similar to the original SF method, finite numbers of singular frequencies are sufficient to compute the stable regions in the space of time delay and controller coefficients.

In this paper, a precise and nonlinear model is developed for Nekka power plant turbine from its experimental data and documents. It is proposed to use boiler-turbine coordinated control system to increase effective efficiency of the steam unit. Identification procedures have been performed to obtain continuous time models of Nekka steam turbine at various loads. After determining the upper bound for uncertainty and choosing a good performance weighting function, a robust controller has been designed and implemented in closed loop for the turbine nonlinear model. Since the closed loop performance was not as required, a cascade controller structure is proposed, in which the turbine loop is closed by a PI controller in order to significantly reduce the uncertainty. Simulation results demonstrate the suitable performance of the closed loop in terms of tracking, speed of response, and damping of oscillations.

One of the most complex issues which are proposed in designing a controller for autopilots is robustness. This requirement is due to the dynamic model changes and also, the resistance to environmental disturbances. A main factor that changes the dynamic model of the helicopter autopilot is any change in body mass center, such as any additional load. Furthermore, wind is one of the main causes of environmental disturbances. In this paper model identification of four systems in helicopter by using real data is presented. For all systems robust H2/H-Infinity and mixed sensitivity controller are designed. The simulation results show the robustness of designed controllers in the existence of uncertainty. The designed controller was implemented on the real case study. Results demonstrate the robustness of the system.

In order to remedy the effects of modeling uncertainty, measurement noise and input disturbance on the performance of the standard state-dependent Riccati equation (SDRE) filter, a new robust SDRE filter design is developed in this paper. Based on the infinity-norm minimization criterion, the proposed filter effectively estimates the states of nonlinear uncertain system exposed to unknown disturbance inputs. Moreover, by assuming a mild Lipschitz condition on the chosen state-dependent coefficient form, fulfillment of a modified performance index is guaranteed in the proposed filter. The effectiveness of the robust SDRE filter is demonstrated through numerical simulations where it brilliantly outperforms the conventional SDRE filter in presence of model uncertainties, disturbance and measurement noise, in terms of estimation error and region of convergence.

This paper considers the robust stability of uncertain teleoperation systems. Sufficient stability conditions are derived in terms of LMI by representing the teleoperation scheme in retarded form of time-delay systems. By choosing Lyapunov-Krasovski functional, a delay-independent robust stability criterion is presented. We show that the teleoperation system is stable and has good performance under specific LMI condition. With the given controller parameters, stability of system is guaranteed in the presence of any value of delay and admissible uncertainty. To evaluate the theoretical analysis, Numerical simulations are performed.

In this paper, a new adaptive robust approach for non-minimum phase systems is proposed, based on the synthesis algorithm of dynamical backstepping design procedure. The previously proposed adaptive robust backstepping method has a limitation in stabilization of non-minimum phase systems, which is removed in this paper. The dynamic model of the voice coil motor actuator, which is used in the read/write head of hard disk drive, is considered as a case study to apply the proposed method. A simple but accurate model of this system is presented the proposed control method is applied onto this model. Simulations are performed for the embedded control system of hard disk drives. The obtained results verify the effectiveness of the proposed control law in terms of transient performance, tracking errors, and disturbance rejection, in both track seeking and track following modes.

In this paper the problem of model based internal control of singular systems is investigated. The limitations of directly extending the control schemes for normal systems to singular ones are thoroughly developed, and a robust approach is proposed in order to establish a control scheme for singular systems. The proposed method presents a general framework for robust control design of singular systems in presence of modeling uncertainties. Two simulation examples are given to how the proposed method can be implemented, and to show the effectiveness of such controllers in closed loop performance.

Based on the synthesis algorithm of dynamical backstepping design procedure, in this paper a new adaptive robust approach for non-minimum phase systems is proposed. The proposed controller consists of two parts; a backstepping controller as the robust part and a model reference (MRAS) controller as the adaptive part. In this control scheme the daptive part acts not only as a medium to converge to suitable values for the unknown parameters and to reduce the uncertainty, but also provides a minimum-phase model for the robust controller to be well stabilized. A simulation case study is studied to show how to perform the proposed control law, and to illustrate the effectiveness of this method compared to that of conventional robust controllers.

The descriptor observer approach is improved further to a more suitable observer scheme which is applicable to a more general group of faults and systems. Also a disturbance decoupling scheme is added to the mentioned observer in order to enable the observer to distinguish faults from disturbances.

Using a non-linear model in model predictive control (MPC) changes the control problem from a convex quadratic programme to a non-convex non-linear problem, which is much more challenging to solve. In this study, we introduce an MPC algorithm for non-linear discrete-time systems. The systems are composed of a linear constant part perturbed by an additive state-dependent non-linear term. The control objective is to design a state-feedback control law that minimises an infinite horizon cost function within the framework of linear matrix inequalities. In particular, it is shown that the solution of the optimisation problem can stabilise the non-linear plants. Three extensions, namely, application to systems with input delay, non-linear output tracking and using output-feedback, are followed naturally from the proposed formulation. The performance and effectiveness of the proposed controller is illustrated with numerical examples.

H-Infinity control problem for input-delayed systems is considered in this paper. A composite state-derivative control law is used, in which, a composition of the state variables and their derivatives appear in the control law. Thus, the resulting closed-loop system turns into a specific time-delay system of neutral type. The significant specification of this neutral system is that its delayed term coefficients depend on the control law parameters. This condition provides new challenging issues which has its own merits in theoretical research as well as application aspects. New delay-dependent sufficient condition for the existence of H ? controller in terms of matrix inequalities is derived in the present paper. The resulting H-Infinity controller guarantees asymptotic stability of the closed-loop system as well as a guaranteed limited H ? norm smaller than a prescribed level. Numerical examples are presented to illustrate the effectiveness of the proposed methods.

Identifying a robotic system, especially in presence of some nonlinear phenomena, such as friction and backlash, is a troublesome problem. In this paper, initially single link parameter identification is discussed. Parameters such as actuators parameter, link inertia, friction and backlash are identified in this section. A combination of actuator's model and a model of two flexible masses in attendance of friction and backlash is utilized for this purpose. Identifying two link robot parameters will be under debate afterwards and identification results for the second link are presented in three distinct forms. Furthermore, a method is introduced for selecting best estimated parameters set, in order to be exerted on systems controller. The effects of identified friction torques and backlash modeling on controller improvement are presented. Grey box structure model, available in Matlab's system identification tool box is utilized in this research.

Smith predictor is one of the first structures used to compensate the time delay in closed loop systems. One of the simplest controllers which are used to control the industrial systems is PID controller. Although, we know that the derivative term is rarely used for controlling the time delay systems. Subtle identification of time delay is usually impossible in reality; on the other hand, PI controller design with smith structure is practiced upon the open loop delay free system. Therefore the structural uncertainty will be existed in open loop systems which make the designing of the PI controller very difficult. In this paper, at first, we analyze the effect of difference between modeled time delay and real time delay on the PI parameters, then the performance of the closed loop system compared with a second order delay free system is investigated; and finally, we compare the tracking of variable time delay system with fixed time delay system which both of them have the same parameters. In this analysis we assume that the fixed time delay is max of variable time delay.

This paper considers stability problem for input- delayed systems for both constant and time-varying delay case. A new composite state-derivative control law is introduced, in which, a composition of the state variables and their derivatives appear in control law. By this means, the resulting closed-loop system becomes a particular time-delay system of neutral type. The significant specification of this neutral system is that its delayed term coefficients depend on the control law's parameters. This condition provides new challenging issues which has its own merits in theoretical as well as practical aspects. In the present paper, new delay-dependent sufficient conditions are derived in presence of both constant and varying time-delay in terms of matrix inequalities. The resulting controllers guarantee asymptotic stability of the closed-loop system. Simulation studies are presented to verify the stability conditions obtained within the theorems.

We assessed on Monte-Carlo simulated excitatory post-synaptic currents the ability of autoregressive (AR)-model fitting to evaluate their fluctuations. AR-model fitting consists of a linear filter describing the process that generates the fluctuations when driven with a white noise. Its fluctuations provide a filtered version of the signal and have a spectral density depending on the properties of the linear filter. When the spectra of the non-stationary fluctuations of excitatory post-synaptic currents were estimated by fitting AR-models to the segments of current fluctuations, assumed to be stationary and independent, the parameter and spectral estimates were scattered. The scatter was much reduced if the time-variant AR-models were fitted using stochastic adaptive estimators (Kalman, recursive least squares and least mean squares). The ability of time-variant AR-models to accurately fit the current fluctuations was monitored by comparing the fluctuations with predicted fluctuations, and by evaluating the model-learning rate. The median frequency of current fluctuations, which could be rapidly tracked and estimated from the individual quantal events (either Monte-Carlo simulated or recorded from pyramidal neurons of rat hippocampus), rose during the rise phase, before declining to a lower steady-state level during the decay phase of quantal event, whereas the variance showed a broad peak. The closing rate of AMPA channels directly affects the steady-state median frequency, whereas the transient peak can be modulated by a variety of factors—number of molecules released, ability of glutamate molecules to re-enter the synaptic cleft, diffusion constant of glutamate in the cleft and opening rate of AMPA channels. In each case, the effect on the amplitude and decay time of mEPSCs and on the current fluctuations differs. Each factor thus leaves its own kinetic fingerprint arguing that the contribution of such factors can be inferred from the combined kinetic properties of individual mEPSCs.

In this paper, robust controllers have been proposed for oscillation suppression in the RTAC benchmark problem. A nominal plant and an uncertainty model are extracted out of varieties of linear models, identified for the nonlinear system and the generalized plant for the unstructured uncertainty problem has been presented. Based on passivity, a cascade controller has been designed to reduce amount of uncertainty in lower frequencies. It is verified that through a nonlinear feedback controller in the inner loop, the uncertainty of linear estimates of the system reduces significantly, and becomes plausible to use linear robust techniques such as mixed sensitivity and H 2 /H-Infinity to design controller for the system. Finally H-Infinity and H 2 /H-Infinity controllers have been designed for new generalized plant and results are compared with the previous reports in literature.

The Rotational/Translational Actuator (RTAC) benchmark problem considers a fourth-order dynamical system involving the nonlinear interaction of a translational oscillator and an eccentric rotational proof mass. This problem has been posed to investigate the utility of a rotational actuator for stabilizing translational motion. In order to experimentally implement any of the model-based controllers proposed in the literature, the values of model parameters are required which are generally difficult to determine rigorously. In this paper, an approach to the least-squares estimation of the parameters of a system is formulated and practically applied to the RTAC system. On the other hand, this paper shows how to model a nonlinear system as a linear uncertain system via nonparametric system identification, in order to provide the information required for linear robust H-Infinity control design. This method is also applied to the RTAC system, which demonstrates severe nonlinearities due to the coupling from the rotational motion to the translational motion. Experimental results confirm that this approach can effectively condense the whole nonlinearities, uncertainties, and disturbances within the system into a favorable perturbation block.

The Yazd Integrated Solar Combined Cycle (ISCC) Power Plant consists of two gas turbines that are generating power synchronous to Iranian national electrical network. One steam turbine will be supplied by gas units, while a parabolic through solar field is integrated with the System, as a combined cycle. In this paper an integrated model of the solar field with the purpose is presented, and a multivariable generalized predictive temperature controller is proposed for the system. As it is Illustrated in the simulation results, such a control strategy can robustly regulate both the temperature of outlet oil, and the temperature of outlet steam water of the solar boiler, despite the variation of the inherent time delays of the system and external disturbances.

In this paper, a novel vector control method for permanent magnet synchronous motors is presented. In this method, the velocity estimation is completely removed and vector control is accomplished in a new coordinate system. In conventional vector control methods, the control effort is calculated in rotating coordinates with a synchronous speed of omega. However, in the proposed method, the control effort is calculated in rotating coordinates with reference speed omega. This change of coordinate decreases the calculation effort significantly. In order to verify the applicability of the proposed control law, a Lyapunov-based stability condition is derived and the performance of the controller is verified through simulations and experiments. The obtained results illustrate the effectiveness of the proposed method despite the simplicity of its implementation.

An analytical investigation of a half-car model including passenger dynamics, subjected to random road disturbances is performed, and the advantage of active over conventional passive suspension systems are examined. Two different performance indices for optimal controller design are proposed. The performance index is a quantification of both ride comfort and road handling. Due to practical limitations, all the states required for the state-feedback controller are not measurable, and thus must be estimated with an observer. Stochastic inputs are applied to simulate realistic road surface conditions, and statistical comparisons between passive system and the two controllers, with and without state estimator, are carried out to gain a clearer insight into the performance of the controllers.The simulation results demonstrate that an optimal observer- based controller, when including passenger acceleration in the performance index, retains both excellent ride comfort and road handling characteristics.

The torque control of harmonic drive system is examined in detail. An empirical nominal model for the system is obtained through experimental frequency response estimates, and the deviation of the system from the model is encapsulated by multiplicative uncertainty. A robust torque controller is subsequently designed in an H-Infinity framework and implemented using Kalman filtered torque estimates. Exceptional performance results are obtained from the time and frequency response of the closed-loop system. To further improve the performance of the system, a model-based friction-compensation algorithm is implemented in addition to the robust torque control. It is shown that the friction-compensation reduced the model uncertainty at low frequencies. Hence, the performance of the closed-loop system is improved for tracking signals with low-frequency content.

Despite widespread industrial application of harmonic drives, mathematical representation of their dynamics has not been fully addressed. In this paper a systematic way to capture and rationalize the dynamic behavior of the harmonic drive systems is developed. Simple and accurate models for compliance, hysteresis, and friction are proposed, and the model parameters are estimated using least--squares approximation for linear and nonlinear regression models. A statistical measure of variation is defined, by which the reliability of the estimated parameter for different operating condition, as well as the accuracy and integrity of the proposed model is quantified. By these means, it is shown that a linear stiffness model best captures the behavior of the system when combined with a good model for hysteresis. Moreover, the frictional losses of harmonic drive are modelled at both low and high velocities. The model performance is assessed by comparing simulations with the experimental result...

The unique performance features of harmonic drives, such as high gear ratios and high torque capacities in a compact geometry, justify their widespread industrial application. However, harmonic drive can exhibit surprisingly more complex dynamic behavior than conventional gear transmission. In this paper a systematic way to capture and rationalize the dynamic behavior of the harmonic drive systems is developed. Simple and accurate models for compliance, hysteresis, and friction are proposed, and the model parameters are estimated using least-squares approximation for linear and nonlinear regression models. A statistical measure of variation is defined, by which the reliability of the estimated parameter for different operating condition, as well as the accuracy and integrity of the proposed model is quantified. By these means, it is shown that a linear stiffness model best captures the behavior of the system when combined with a good model for hysteresis. Moreover, the frictional losses of harmonic drive are modeled at both low and high velocities. The model performance is assessed by comparing simulations with the experimental results on two different harmonic drives. Finally, the significance of individual components of the nonlinear model is assessed by a parameter sensitivity study using simulations.

A harmonic drive is a compact, light-weight and high-ratio torque transmission device which is used in many electrically actuated robot manipulators. In many robotic control strategies it is assumed that the actuator is an ideal torque source. However, converting harmonic drive systems to ideal torque sources is still a challenging control problem for researchers. In this paper the torque control of harmonic drive system under free motion is examined in detail. A built-in torque sensor is developed in order to measure the torque, and by employing a Kalman filter the undesired torque signatures like torque ripples and misalignment torque are filtered out. An empirical nominal model for the system is obtained through experimental frequency response estimates, and the deviation of the system from the model is encapsulated by multiplicative uncertainty. A robust torque controller is subsequently designed in an H_?-framework and implemented employing Kalman filtered torque estimates. From time and frequency domain experiments, it is shown that the closed-loop system retains robust stability, while improving the tracking performance exceptionally well

The unique performance features of harmonic drives, such as high gear ratios and high torque capacities in a compact geometry, justify their widespread industrial application, especially in robotics. However, harmonic drives can exhibit surprisingly more complex dynamic behavior than conventional gear transmissions. In this report, a systematic way to capture and rationalize the dynamic behavior of the harmonic drive systems is examined. Simple and accurate models for compliance, hysteresis, and friction are proposed, and the model parameters are estimated using least--squares approximation for linear and nonlinear regression models. A statistical measure of variation is defined, by which the reliability of the estimated parameter for different operating condition, as well as the accuracy and integrity of the proposed model is quantified. Finally, the model performance is assessed by a simulation verifying the experimental results. R' esum' e Les performances uniques de l'entrainement ...

The unique performance features of harmonic drives, such as high gear ratios and high torque capacities in a compact geometry, justify their widespread industrial application especially in many electrically actuated robot manipulators. In many robotic control strategies it is assumed that the actuator is acting as a torque source, and in order to implement such algorithms it is necessary to accurately measure the transmitted torque by the harmonic drive. In this paper a built-in torque sensor for harmonic drive systems is developed and examined in detail, in which strain-gauges are directly mounted on the harmonic drive flexspline. To minimize sensing inaccuracy, four Rosette strain gauges are used employing an accurate positioning method. To cancel the torque ripples, the oscillation observed on the measured torque and caused mainly by gear teeth meshing, Kalman filter estimation is used. A simple fourth order harmonic oscillator proved to accurately model the torque ripples. Moreover, the error model is extended to incorporate any misalignment torque. By on line implementation of the Kalman filter, it has been shown that this method is a fast and accurate way to filter torque ripples and misalignment torque. Hence, the intelligent built-in torque sensor is a viable and economical way to measure the harmonic drive transmitted torque and to employ that for torque feedback strategies.

Despite widespr ad industrial application of harmonic drives, modelling and control of such systems has not been fully addressed. In this theoretical/experimental study of harmonic drive systems a systematic way to capture and rationalize the dynamics of the system is proposed. Simple and accurate models for their compliance, hysteresis, and friction are given and model parameters are estimated from experimental data using least square approximation. A statistical measure of consistency is defined, by which the reliability of the estimated parameter for different operating condition, as well as the accuracy and integrity of the proposed model is quantified. The validity of the modelling scheme is evaluated by comparing the experimental and simulation results. Two separate simulations are developed for the harmonic drive system operating in restrained and unrestrained motion. The problem of torque control of harmonic drive is addressed in the H1 controller design framework. I...

An analytical investigation of a half-car model with passenger dynamics, subjected to random road disturbance, is performed. Two diierent methods of deening the performance index for optimal controller design are proposed. Nondeterministic inputs are applied to simulate the road surface conditions more realistically. Results obtained illustrate that using an optimal state-feedback controller, with passenger acceleration included in the performance index, would exhibit not only an improved passenger ride comfort, but also, a better road handling and stability.