Hierarchical Robust Adaptive Control for Wind Turbines with Actuator Fault

This paper solves the problem of regulating the rotor speed tracking error for wind turbines in the full-load region by an effective robust-adaptive control strategy. The developed controller compensates for the uncertainty in the control input effectiveness caused by a pitch actuator fault, unmeasurable wind disturbance, and nonlinearity in the model. Wind turbines have multi-layer structures such that the high-level structure is nonlinearly coupled through an aggregation of the low-level control authorities. Hence, the control design is divided into two stages. First, an ℒ2 controller is designed to attenuate the influence of wind disturbance fluctuations on the rotor speed. Then, in the low-level layer, a controller is designed using a proposed adaptation mechanism to compensate for actuator faults. The theoretical results show that the closed-loop equilibrium point of the regulated rotor speed tracking error dynamics in the high level is finite-gain ℒ2 stable, and the closed-loop error dynamics in the low level is globally asymptotically stable. Simulation results show that the developed controller significantly reduces the root-mean- square of the rotor speed error compared to some well-known works, despite the largely fluctuating wind disturbance, and the time-varying uncertainty in the control input effectiveness.

Yaw-rate-tracking-based Automated Vehicle Path Following: An MRAC Methodology with A Closed-Loop Reference Model

Concerning automated vehicles, various path-following controllers have been designed by the model reference adaptive control (MRAC) approach. Through appropriate Lyapunov redesigns, asymptotical stability and signal boundedness are ensured for the path-tracking control loops. However, transient behaviors of the closed-loop responses are seldom considered in the context of MRAC synthesis. To bridge the foregoing gap, a closed-loop reference model-based MRAC, which yields an improved transient performance compared with a traditional MRAC, is exploited to synthesize a vehicular path following control law. Besides, an infinitely differentiable projection operator is complemented to the control parameters' adaptation schemes for estimation speed-up and robustness enhancement. Hardware-in-the loop experiments are used to evaluate the proposed method and to demonstrate its improvement over some conventional MRAC designs.

Fisher Identifiability Analysis of Longitudinal Vehicle Dynamics

This paper investigates the theoretical Cram´er-Rao bounds on estimation accuracy of longitudinal vehicle dynamics parameters. This analysis is motivated by the value of parameter estimation in various applications, including chassis model validation and active safety. Relevant literature addresses this demand through algorithms capable of estimating chassis parameters for diverse conditions. While the implementation of such algorithms has been studied, the question of fundamental limits on their accuracy remains largely unexplored. We address this question by presenting two contributions. First, this paper presents theoretical findings which reveal the prevailing effects underpinning vehicle chassis parameter identifiability. We then validate these findings with data from on-road experiments. Our results demonstrate, among a variety of effects, the strong relevance of road grade variability in determining parameter identifiability from a drive cycle. These findings can motivate improved experimental designs in the future.

Multi-model structured H-infinity design of a robust and aggressive turbofan jet engine controller

Jet engine control comprises tracking either the fan speed or engine pressure ratio setpoints. Further, safe operation entails maintaining several additional parameters, such as high-pressure turbine temperature, combustor pressure, core shaft acceleration and other ones within prescribed limits. A Min-Max selector that features PI controllers is frequently used to handle these requirements. However, this arrangement is overly conservative in the limits management, which unnecessarily slows down the engine response. To overcome this shortcoming, a new controller that adopts the traditional Min-Max structure in combination with the Ndot control, the Conditionally Active and the Conditioning Technique approaches is developed. PI regulators are replaced by dynamic output feedback controllers, which are designed according to a multi-model structured H-infinity methodology. This approach makes it possible to marry robustness with performance, which are two conflicting objectives. Singular value analysis tools demonstrate the robustness of the resulting design. Linear and nonlinear simulations indicate that the proposed controller optimizes the engine response time under the constraint of keeping a set of parameters within prescribed bounds. The features of the proposed design are lucrative for actual implementation in the industry.

Balancing inverted pendulum cart on inclines using accelerometers

The balance of inverted pendulum on inclined surfaces is the precursor to their control in unstructured environments. Researchers have devised control algorithms with feedback from contact (encoders - placed at the pendulum joint) and non-contact (gyroscopes, tilt) sensors. We present feedback control of Inverted Pendulum Cart (IPC) on variable inclines using non-contact sensors and a modified error function. The system is in the state of equilibrium when it is not accelerating and not falling over (rotational equilibrium). This is achieved when the pendulum is aligned along the gravity vector. The control feedback is obtained from non-contact sensors comprising of a pair of accelerometers placed on the inverted pendulum and one on the cart. The proposed modified error function is composed of the dynamic (non-gravity) acceleration of the pendulum and the velocity of the cart. We prove that the system is in equilibrium when the modified error is zero. We present algorithm to calculate the dynamic acceleration and angle of the pendulum, and incline angle using accelerometer readings. Here, the cart velocity and acceleration are assumed to be proportional to the motor angular velocity and acceleration. Thereafter, we perform simulation using noisy sensors to illustrate the balance of IPC on surfaces with unknown inclination angles using PID feedback controller with saturated motor torque, including valley profile that resembles a downhill, flat and uphill combination. The successful control of the system using the proposed modified error function and accelerometer feedback argues for future design of controllers for unstructured and unknown environments using all-accelerometer feedback.

An Efficient Design Procedure for MEMS Electrothermal Microgripper

With the development of miniaturization technology, MEMS electrothermal microgrippers have been widely used owing to their compact size, ease of manufacturing, and low production cost. Since most of these systems are governed by partial differential equations (PDEs), modeling of microgrippers poses a significant challenge for designers. To reduce the overall computational complexity, it is a common practice to model the microgripper system using the finite element method (FEM). During the design process, the geometric and analytical properties of the microgripper influence the system dynamics to a great extent, and this work focuses on studying the effects of such parameter changes. In low voltage applications, the performance of the microgripper is influenced by the geometrical variations, and the air gap. Hence, for the modeling of the microgripper, actuator arm lengths, and the gap between the arms are chosen as the two main geometric design parameters, while the input current density is considered as the analytical design parameter. In this work, the optimized design parameter values for maximum possible displacement are obtained with the use of Sine Cosine Algorithm (SCA). Further, an averaging operation is proposed for efficiently designing the MEMS electrothermal microgripper, and the efficacy of the proposed design methodology is demonstrated through simulation studies.

A Novel Concept for Energy-Optimal, Independent-Phase Control of Brushless Motor Drivers

In this work, a new drive concept for brushless direct current (BLDC) motors is introduced. Energy regeneration is optimally managed with the aim of improving the energy efficiency of robot motion controls. The proposed scheme has three independent regenerative drives interconnected in a wye configuration. An augmented model of the robot, joint mechanisms, and BLDC motors is formed, and then a voltage-based control scheme is developed. The control law is obtained by specifying an outer-loop torque controller followed by minimization of power consumption via online constrained quadratic optimization. An experiment is conducted to assess the performance of the proposed concept against an off-the-shelf driver. It is shown that, in terms of energy regeneration and consumption, the developed driver has better performance. Furthermore, the proposed concept showed a reduction of 15% energy consumption for the conditions of the study.

Speed- and Range-based Filter Design for Dual-Stage Actuator Control

Dual-stage actuators, which combine two actuators with different characteristics, have gained interest due to their large-range, high-resolution positioning capabilities. Control of such systems is challenging because it requires balancing the relative contributions of the individual actuators in terms of speed, range and precision. The most common approach is to allocate effort to the actuators based on frequency but this can lead to misallocation in the case of low-frequency short-range trajectories. In this paper, the problem of trajectory allocation in dual-stage actuator systems is addressed using a recently developed range-based filter. The theoretical basis of the range-based filter is rigorously derived for the first time and insights regarding its use, specifically its reinterpretation as a speed-based filter, and its range-frequency response characteristics are presented. The new analysis not only explains the behavior of the filter clearly, but it provides a more robust strategy for incorporating range constraints in filter design for different desired trajectories.

Slip-Clutch Torque Estimation via Real-Time Adaptive Lookup Table

Transfer case clutch is crucial in determining traction torque distribution between front and rear tires for four-wheel-drive (4WD) vehicles. Estimating time-varying clutch surface friction coefficient is critical for traction torque control since it is proportional to the clutch output torque. As a result, this paper proposes a real-time adaptive lookup table strategy to provide the time-varying clutch surface friction coefficient. Specifically, the clutch-parameter-dependent (such as clutch output torque and clutch touchpoint distance) friction coefficient is first estimated with available low-cost vehicle sensors (such as wheel speed and vehicle acceleration); and then a clutch-parameter-independent approach is developed for clutch friction coefficient through a one-dimensional lookup table. The table nodes are adaptively updated based on a fast recursive least-squares (RLS) algorithm. Furthermore, the effectiveness of adaptive lookup table is demonstrated by comparing the estimated clutch torque from adaptive lookup table with that estimated from vehicle dynamics, which achieves 14.8 Nm absolute mean squared error (AMSE) and 2.66% relative mean squared error (RMSE).