State Variable Feedback Control Research Articles

Handling Improvement for Distributed Drive Electric Vehicle Based on State Variable Feedback Control

The direct yaw moment control for distributed drive electric vehicle is studied. A handling improvement algorithm based on state variable feedback control is proposed. The yaw rate feedback is employed to improve the transient response of the yaw rate, the steer angle feedforward is employed to increase the steady gain of the yaw rate. According to the feedback coefficient's influence on the transient response, an optimization function is proposed to obtain optimum feedback coefficients under different speeds. The constraint of differential torque on the front axle is calculated from the requirement of power steering, together with the motor exterior characteristic constraint of the rear axle, the maximum feedforward coefficients under different speeds are obtained. A torque distribution algorithm is presented to help the driver to speed up during the direct yaw moment control. Simulations under multiple maneuvers is carried out. While the transient response and the steady gain of the yaw rate are improved, the algorithm can also decrease the steering wheel torque; the direct yaw moment control can rectify the understeering caused by accelerating, balance the friction usage of two axles, and increase the lateral stability margin of the vehicle.

Non-minimal state variable feedback decoupling control for multivariable continuous-time systems

Most research into non-minimal state variable feedback control, in which the state vector is implemented directly from the measured input and output signals of the controlled process, has considered discrete-time systems represented using either the backward shift or delta operator. However, mechanistic models with physically meaningful parameters are often expressed in terms of differential equations, represented using the Laplace transform or s-operator, and this article is concerned with multivariable design for such models. The controllability conditions are developed and it is shown how the introduction of a diagonal polynomial matrix for filtering yields a control system that is immediately realisable in practice. Worked examples include optimal control with multi-objective optimisation and pole assignment design with analytical multivariable decoupling, with the latter illustrated by its application to a nonlinear wind turbine simulation.

PI Sliding Mode Control for Mismatched Uncertain Systems

This paper focused on the proportional–integral sliding mode control for uncertain dynamic systems with mismatch uncertainties. First, the switching surface condition for the sliding mode control is synthesized. Then the control law is designed to drive the state trajectories of the system onto the sliding surface and the system remains in it thereafter. The proposed control law is applied to a numerical example and its performance is compared to the state variable feedback control system design methodology. Key words: sliding mode control; state variable feedback regulator; mismatched uncertainties

The Control System Research of Reheated Steam Temperature State Variables Based on the Mechanism Analysis of Dynamic Characteristic

In this paper, it is presented a method of the design and parameter calculation for state variable feedback control system of reheat steam temperature, which based on the mechanism analysis of reheater dynamic characteristics of supercritical 600WM unit. The simulation results show that the control quality and anti-interference ability is better, and the response is faster, while the control system of reheater steam temperature is established with this method.

Non-Certainty-Equivalent Adaptive Control of a Nonlinear Aeroelastic System

Non-Certainty-Equivalent Adaptive Control of a Nonlinear Aeroelastic SystemThe development of a non-certainty-equivalent adaptive control system for the control of a nonlinear aeroelastic system is the subject of this paper. The prototypical aeroelastic wing section considered here includes structural nonlinearity and a single control surface for the purpose of control. Its dynamical model has two-degree-of-freedom and describes the plunge and pitch motion. It is assumed that the model parameters (except the sign of one of the control input coefficients) are not known. The uncontrolled aeroelastic model exhibits limit cycle oscillation beyond a critical free-stream velocity. Based on the attractive manifold, and the immersion and invariance methodologies, a non-certainty-equivalent adaptive state variable feedback control law for the trajectory tracking of the pitch angle is derived. Using the Lyapunov analysis, asymptotic convergence of the state variables to the origin is established. It is shown that the trajectory of the system converges to a manifold. The special feature of the designed control system is that the closed-loop system asymptotically recovers the performance of a deterministic controller. This cannot happen if certainty-equivalent adaptive controllers are used. Simulation results are presented which show that the control system suppresses the oscillatory responses of the system in the presence of large parameter uncertainties.

Stabilizing global mean surface temperature: A feedback control perspective

In this paper, we develop a discrete time, state variable feedback control regime to analyze the closed-loop properties associated with stabilizing the global mean surface temperature anomaly at 2 °C within a sequential decision making framework made up of 20 year review periods beginning in 2020. The design of the feedback control uses an optimal control approach that minimizes the peak deceleration of anthropogenic CO 2 emissions whilst avoiding overshooting the 2 °C target. The peak value for emissions deceleration that satisfies the closed-loop optimization was found to be linearly related to climate sensitivity and a climate sensitivity of 3.5 °C gave a deceleration of −1.9 GtC/a/20 years 2. In addition to accounting for the predicted climate dynamics, the control system design includes a facility to emulate a robust corrective action in the face of uncertainty. The behavior of the overall control action is evaluated using an uncertainty scenario for climate model equilibrium sensitivity.

A robust sequential CO2 emissions strategy based on optimal control of atmospheric CO2 concentrations

This paper formally introduces the concept of mitigation as a stochastic control problem. This is illustrated by applying a digital state variable feedback control approach known as Non-Minimum State Space (NMSS) control to the problem of specifying carbon emissions to control atmospheric CO2 concentrations in the presence of uncertainty. It is shown that the control approach naturally lends itself to integrating both anticipatory and reflexive mitigation strategies within a single unified framework. The framework explicitly considers the closed-loop nature of climate mitigation, and employs a policy orientated optimisation procedure to specify the properties of this closed-loop system. The product of this exercise is a control law that is suitably conditioned to regulate atmospheric CO2 concentrations through assimilating online information within a 25-year review cycle framework. It is shown that the optimal control law is also robust when faced with significant levels of uncertainty about the functioning of the global carbon cycle.

TF/TA 2 trajectory tracking using nonlinear predictive control approach

The use of a methodology of nonlinear continuous predictive control to design the guidance control law for the aircraft TF/TA 2 trajectory tracking problem is emplojed. For the derivation of the predictive control law, by using Taylor series expansion, and based on optimizing a performance index which is a quadratic function of both the predictive value of the state variables and the control inputs, a state variable feedback controller for nonlinear systems is obtained, and it provides a tradeoff between satisfactory tracking performance and the control magnitude requirements. Numerical simulation results for a supersonic fighter aircraft model show the viability of this approach.

Multivariable proportional-integral-plus (PIP) control of the ALSTOM nonlinear gasifier simulation

Multivariable proportional-integral-plus (PIP) control methods are applied to the nonlinear ALSTOM Benchmark Challenge II. The approach utilises a data-based combined model reduction and linearisation step, which plays an essential role in satisfying the design specifications. The discrete-time transfer function models obtained in this manner are represented in a non-minimum state space form suitable for PIP control system design. Here, full state variable feedback control can be implemented directly from the measured input and output signals of the controlled process, without resorting to the design and implementation of a deterministic state reconstructor or a stochastic Kalman filter. Furthermore, the non-minimal formulation provides more design freedom than the equivalent minimal case, a characteristic that proves particularly useful in tuning the algorithm to meet the Benchmark specifications. The latter requirements are comfortably met for all three operating conditions by using a straightforward to implement, fixed gain, linear PIP algorithm.

User-Friendly Acceleration/Deceleration Control of Electric-Powered Wheelchair

Even slight differences in the movement of an electric-powered wheelchair may greatly affect riding comfort for wheelchair users. We focused on upper body tilt during acceleration and deceleration, a factor determining riding comfort and propose controlling tilt to control a user-friendly electric-powered wheelchair. We modeled the wheelchair and designed state variable feedback control with the upper body tilt angle and angular velocity of the upper body used as a state variable and an observer and an optimal regulator using Kalman filter for the presumption of the state variable. We assumed the state variable by the observer and state variable feedback control validated by the optimal regulator through computer simulation. We applied this control to the electric-powered wheelchair designed on a trial basis and indicated that upper body tilt could be suppressed by state variable feedback control.

State feedback control of an aeroelastic system with structural nonlinearity

The paper treats the question of state variable feedback control of prototypical aeroelastic wing sections with structural nonlinearity. This type of model has been traditionally used for the theoretical as well as experimental analyses of two-dimensional aeroelastic behavior. The chosen dynamic model describes the nonlinear plunge and pitch motion of a wing. A single control surface is used for the purpose of control. A control law is designed based on the state-dependent Riccati equation technique. Unlike feedback linearizing control systems reported in literature, this approach is applicable to minimum as well as nonminimum phase aeroelastic models. The closed-loop system is asymptotically stable. Simulation results are presented which show that in the closed-loop system, flutter suppression is accomplished.

Extension of tethered satellites in the atmosphere

An important application of tethered satellites is atmospheric studies by extension of a subsatellite into the atmosphere through tether while the parent spacecraft flies at an altitude high enough so that the deleterious effects of the atmosphere on it are inconsequential. The key issue in the operation is the swift extension of the tether. Inordinate librations of the tether during extension are undesirable. Tension control, in conjunction with a thruster to control the out-of-pane motion, is a popular technique of control during extension. Many nonlinear feedback tension control laws based on Liapunov's direct method have been proposed. In this paper, an alternate technique, a linear state variable feedback control law is used. The control gains are determined from theorems in analytical mechanics. Simulation of the nonlinear equations using this controller affirms that the tether extends to the desired length in a reasonable amount of time.

An Overview on Control Algorithms for Automated Highway Systems

This paper surveys lateral and longitudinal vehicle control algorithms in automated highway systems. In the lateral control, an onboard sensing system detects or captures a reference on a roadway indicating the path of an automated vehicle, and PID control and state variable feedback control based on the modern control theory with deviation from a planned path are mainly used to drive the vehicle along the path. In the longitudinal control, an inter-vehicle gap and relative speed to a preceding vehicle are measured, and feedback control with state variables including deviations in the gap, relative speed, and relative acceleration, some of which are obtained by the transmission over inter-vehicle communication rather the measurement, is used to maintain a predetermined gap in a platoon. Lateral and longitudinal vehicle control algorithms are explained with references to some systems developed since 1960's.

Triangular configuration of uncertain systems stabilizable by means of feedback controller

The uncertain linear systems with time-varying delays and limited measurable states variables are shown to have special configuration, called triangular configuration, to be stabilizable by means of state variable feedback controller. This configuration indicates the location of uncertainties among system parameters including input and output coefficients.

State space control system design based on non-minimal state-variable feedback: Further generalization and unification results

This paper shows how proportional-integral-plus linear-quadratic (PIP-LQ) control, based on non-minimal state space (NMSS) control system design, can be constrained to yield exactly the same control algorithm as both generalized predictive control (GPC) and standard, minimal state, linear quadratic gaussian (LQG) design methods. However, while NMSS includes these other approaches as special cases, it is less constrained and so more flexible in general terms: for example, while PIP-LQ has the simplicity of GPC, it is formulated like LQG in the powerful context of state variable feedback (SVF) control, which allows for ready access to modern robust control methods. Furthermore, the paper suggests that the NMSS approach provides the greater design freedom, with a wider range of possible LQ solutions than its minimal state space equivalent.

Job flow control in assembly operations

The authors develop a state variable feedback control for a class of assembly operations. The objective of this control is to increase the number of jobs completed within a time horizon T while keeping the job cycle times within an acceptable range with a prespecified probability. The assembly operations are modeled as stochastic timed-event graphs which in the (max, +) algebra are characterized by a set of linear stochastic difference equations.

Performance of a rail car equipped with independently rotating wheelsets having yaw control

Rail vehicles experience problems of hunting and severe wheel/rail wear which result in lower critical speeds. The design of the conventional railway wheelset, consisting of two wheels mounted rigidly on an axle, is one of the main factors inhibiting high-speed operation of rail vehicles. In this paper the potential for good dynamic stability at high speeds and improved ride comfort in a rail vehicle equipped with an independently rotating wheelset (IRW) having yaw control are examined. The control for the yaw rotation is provided by a state-variable feedback controller.

Proportional-integral-plus (PIP) control of time delay systems

The paper shows that the digital proportional-integral-plus (PIP) controller formulated within the context of non-minimum state space (NMSS) control system design methodology is directly equivalent, under certain non-restrictive pole assignment conditions, to the equivalent digital Smith predictor (SP) control system for time delay systems. This allows SP controllers to be considered within the context of NMSS state variable feedback control, so that optimal design methods can be exploited to enhance the performance of the SP controller. Alternatively, since the PIP design strategy provides a more flexible approach, which subsumes the SP controller as one option, it provides a superior basis for general control system design. The paper also discusses the robustness and disturbance response characteristics of the two PIP control structures that emerge from the analysis and demonstrates the efficacy of the design methods through simulation examples and the design of a climate control system for a large horticultural glasshouse system.

Proportional-integral-plus (PIP) design for delta (delta) operator systems Part 1. SISO systems

The paper presents a general approach to state variable feedback control of rapidly sampled linear systems described by discrete differential or delta (delta) operator transfer function models. This is based on the formulation of a special nonminimum state-space representation of the system which ensures that the state variable feedback control law can be implemented in terms of realizable compensation filters, thus avoiding the complication and limitations of state reconstruction filter (observer or Kalman filter) design. The necessary and sufficient conditions for the controllability and pole assignability of the proportional-integral-plus (PIP) controller obtained in this manner are developed and, in the case of SVF pole assignment, the relationships between the coefficients of the desired closed-loop characteristic polynomial and the control feedback gains are developed. Singleinput single-output deterministic systems are considered, but the approach can be extended to multivariable and stochastic systems, as described in two companion papers. The effectiveness of the design procedure is illustrated by both simulation and practical examples.

A perturbation approach to finite dimensional stabilization of time-lag systems

A finite dimensional state variable feedback controller is proposed for time-lag systems described by differential-difference equations. The result is made explicit for scalar systems.