A method is presented to analyze the stability of feedback systems with neural network controllers. Two stability theorems are given to prove asymptotic stability and to compute an ellipsoidal inner-approximation to the region of attraction (ROA). The first theorem addresses linear time-invariant systems, and merges Lyapunov theory with local (sector) quadratic constraints to bound the nonlinear activation functions in the neural network. The second theorem allows the system to include perturbations such as unmodeled dynamics, slope-restricted nonlinearities, and time delay, using integral quadratic constraint (IQCs) to capture their input/output behavior. This in turn allows for off-by-one IQCs to refine the description of activation functions by capturing their slope restrictions. Both results rely on semidefinite programming to approximate the ROA. The method is illustrated on systems with neural networks trained to stabilize a nonlinear inverted pendulum as well as vehicle lateral dynamics with actuator uncertainty.
In this paper, we propose a novel linear quadratic Gaussian controller whose parameters can be automatically tuned. While linear quadratic regulator method has been widely used in adaptive cruise control system design, researchers have not yet proposed a feasible and effective linear quadratic regulator. Neither did they well tackle with process and measurement noise, nor did they solve the tedious and inefficient tuning problem in adaptive cruise control system design. To compensate for the noise, the authors introduced linear quadratic Gaussian where Kalman filter is applied. And to make the…
This paper presents an algebraic technique to compute the maximum time-delay that can be accepted in the control loop of a Brushless DC Motor (BLDCM) speed controller before the closed loop response becomes unstable. Using a recently proposed time-delay stability analysis methodology, we derive accurate stability conditions for the BLDCM speed controller. The results of applying the new method show that tuning the PI controller for very fast response in the order of magnitude of the BLDCM mechanical time constant cause the time-delay to significantly affect the system stability.
An optimal control law for networked control systems with a discrete-time linear time-invariant (LTI) system as plant and networks between sensor and controller as well as between controller and actuator is proposed. This controller is designed by solving an optimization problem that is a generalization of the optimization problem used to obtain the Linear Quadratic Regulator (LQR) for deterministic discrete-time LTI systems. The networks are represented by random delays and drop outs of transmitted data packets.
Controller design for nonlinear systems with Control Lyapunov Function (CLF) based quadratic programs has recently been successfully applied to a diverse set of difficult control tasks. These existing formulations do not address the gap between design with continuous time models and the discrete time sampled implementation of the resulting controllers, often leading to poor performance on hardware platforms. We propose an approach to close this gap by synthesizing sampled-data counterparts to these CLF-based controllers, specified as quadratically constrained quadratic programs (QCQPs). Assumi…
The problem of controller reduction has a rich history in control theory. Yet, many questions remain open. In particular, there exist very few results on the order reduction of general non-observer based controllers and the subsequent quantification of the closed-loop performance. Recent developments in model-free policy optimization for Linear Quadratic Gaussian (LQG) control have highlighted the importance of this question. In this paper, we first propose a new set of sufficient conditions ensuring that a perturbed controller remains internally stabilizing. Based on this result, we illustrat…
Saturations in control signal can challenge the stability proof of a feedback-linearization-based controller, even leading the system unstable [1]. Thus, several approaches are established to avoid reaching the saturation bound [2,3]. Meanwhile, to help design the controller for a quad-tilt-rotor, [1] modeled a tilt vehicle with implementing the feedback-linearization-based controllers. In this article, we provide a gait plan for this tilt vehicle and control it utilizing the feedback linearization. Since saturations exist in the control signals, we study the stability based on Lyapunov theory…
The linear-quadratic controller is one of the fundamental problems in control theory. The optimal solution is a linear controller that requires access to the state of the entire system at any given time. When considering a network system, this renders the optimal controller a centralized one. The interconnected nature of a network system often demands a distributed controller, where different components of the system are controlled based only on local information. Unlike the classical centralized case, obtaining the optimal distributed controller is usually an intractable problem. Thus, we ado…
In networked control systems, often the sensory signals are quantized before being transmitted to the controller. Consequently, performance is affected by the coarseness of this quantization process. Modern communication technologies allow users to obtain resolution-varying quantized measurements based on the prices paid. In this paper, we consider joint optimal controller synthesis and quantizer scheduling for a partially observed Quantized-Feedback Linear-Quadratic-Gaussian (QF-LQG) system, where the measurements are quantized before being sent to the controller. The system is presented with…
In networked control systems, often the sensory signals are quantized before being transmitted to the controller. Consequently, performance is affected by the coarseness of this quantization process. Modern communication technologies allow users to obtain resolution-varying quantized measurements based on the prices paid. In this paper, we consider optimal controller synthesis of a Quantized-Feedback Linear-Quadratic-Gaussian (QF-LQG) system where the measurements are to be quantized before being transmitted to the controller. The system is presented with several choices of quantizers, along w…
The principal task to control dynamical systems is to ensure their stability. When the system is unknown, robust approaches are promising since they aim to stabilize a large set of plausible systems simultaneously. We study linear controllers under quadratic costs model also known as linear quadratic regulators (LQR). We present two different semi-definite programs (SDP) which results in a controller that stabilizes all systems within an ellipsoid uncertainty set. We further show that the feasibility conditions of the proposed SDPs are \emph{equivalent}. Using the derived robust controller syn…
In this paper, we propose a new Robust Nonlinear Quadratic Gaussian (RNQG) controller based on State-Dependent Riccati Equation (SDRE) scheme for continuous-time nonlinear systems. Existing controllers do not account for combined noise and disturbance acting on the system. The proposed controller is based on a Lyapunov function and a cost function includes states, inputs, outputs, disturbance, and the noise acting on the system. We express the RNQG control law in the form of a traditional Riccati equation. Real-time applications of the controller place high computational burden on system imple…
Current commercial adaptive cruise control (ACC) systems consist of an upper-level planner controller that decides the optimal trajectory that should be followed, and a low-level controller in charge of sending the gas/brake signals to the mechanical system to actually move the vehicle. We find that the low-level controller has a significant impact on the string stability (SS) even if the planner is string stable: (i) a slow controller deteriorates the SS, (ii) slow controllers are common as they arise from insufficient control gains, from a "weak" gas/brake system or both, and (iii) the integ…
This paper considers the Linear Quadratic Regulator problem for linear systems with unknown dynamics, a central problem in data-driven control and reinforcement learning. We propose a method that uses data to directly return a controller without estimating a model of the system. Sufficient conditions are given under which this method returns a stabilizing controller with guaranteed relative error when the data used to design the controller are affected by noise. This method has low complexity as it only requires a finite number of samples of the system response to a sufficiently exciting input…
We study the distributed Linear Quadratic Gaussian (LQG) control problem in discrete-time and finite-horizon, where the controller depends linearly on the history of the outputs and it is required to lie in a given subspace, e.g. to possess a certain sparsity pattern. It is well-known that this problem can be solved with convex programming within the Youla domain if and only if a condition known as Quadratic Invariance (QI) holds. In this paper, we first show that given QI sparsity constraints, one can directly descend the gradient of the cost function within the domain of output-feedback cont…
Vehicle stability control systems are important components of active safety systems for road transport. The problem of vehicle lateral stability control is addressed in this paper using active front wheel steering and individual braking. Vehicle lateral stability control means keeping the vehicle yaw rate and the vehicle side slip angle in desired values. For this reason, a model-based controller is designed. The desired yaw rate is obtained from the single track vehicle model and the desired side slip angle is chosen as zero. Controller design consists of two parts, lower and upper controller…
Exponential stability of a PI plus reset integrator controller by a sampled-data system approach
Gipsa-lab（吉普萨实验室）；CNRS, LAAS（法国国家科学研究中心，图卢兹航空航天实验室）；Univ de Toulouse, UPS, LAAS（图卢兹大学，国立高等邮电学校，图卢兹航空航天实验室）；Dpto. Informática y Sistemas, University of Murcia（穆尔西亚大学，计算机与系统系）；Univ de Toulouse, LAAS（图卢兹大学，图卢兹航空航天实验室）
On the Optimization Landscape of Observer-based Dynamic Linear Quadratic Control
University of Science and Technology Beijing（北京科技大学）；Chongqing University（重庆大学）；Johns Hopkins University（约翰斯·霍普金斯大学）；Tsinghua University（清华大学）；National University of Singapore（新加坡国立大学）
This paper introduces an analytical framework for the derivation of hybrid equations of motion of a flexible quadrotor. This approach helps obtain rigid and elastic equations of motion simultaneously, in a decoupled form, which facilitates the controller design. A delay-dependent stability condition is obtained for the overall system dynamics, including the operator with reaction time delay, the adaptive controller and the flexible quadrotor dynamics. Two different adaptive controllers are implemented to address the uncertainties. It is demonstrated via simulations that the flexible arm tip os…
Aiming at the difficulty of stability analysis in practical application of existing control methods, a controller strategy based on lyapunov stability theory is proposed to realize stable control for any control method. In order to illustrate the effectiveness of this control scheme, this paper lists two different lyapunov functions to test the control effect of different system models in tracking the target function. The simulation results show that the proposed method has excellent control effect on different types of systems and is advanced.
In the past couple of decades, non-quadratic convex penalties have reshaped signal processing and machine learning; in robust control, however, general convex costs break the Riccati and storage function structure that make the design tractable. Practitioners thus default to approximations, heuristics or robust model predictive control that are solved online for short horizons. We close this gap by extending $H_\infty$ control of discrete-time linear systems to strictly convex penalties on state, input, and disturbance, recasting the objective with Bregman divergences that admit a completion-o…
Today, linear PID controllers cannot satisfy requirements of high-precision industry due to the development of technology. According to the literature, reset controllers can overcome this important barrier. However, similar to other non-linear controllers, stability analysis for these controllers is complex and needs parametric models of the systems. Consequently, the applicability of these controllers may diminish in industry. The well-known Hb method is one of the solutions of this significant problem. Nevertheless, assessing the Hb condition in the frequency-domain is complex, particularly …
Recent advances in learning for control allow to synthesize vehicle controllers from learned system dynamics and maintain robust stability guarantees. However, no approach is well-suited for training linear time-invariant (LTI) controllers using arbitrary learned models of the dynamics. This article introduces a method to do so. It uses a robust control framework to derive robust stability criteria. It also uses simulated policy rollouts to obtain gradients on the controller parameters, which serve to improve the closed-loop performance. By formulating the stability criteria as penalties with …
Nowadays, the demand for an alternative to linear PID controllers has increased because of the rising expectations of the high-precision industry. The potential of reset controllers to solve this important challenge has been extensively demonstrated in the literature. However, similarly to other non-linear controllers, the stability analysis for these controllers is complex and relies on parametric models of the systems which may hinder the applicability of these controllers in industry. The well-known Hbeta method tries to solve this significant issue. However, assessing the H\b{eta} conditio…
Single-lane car-following is a fundamental task in autonomous driving. A desirable car-following controller should keep a reasonable range of distances to the preceding vehicle and do so as smoothly as possible. To achieve this, numerous control methods have been proposed: some only rely on local sensing; others also make use of non-local downstream observations. While local methods are capable of attenuating high-frequency velocity oscillation and are economical to compute, non-local methods can dampen a wider spectrum of oscillatory traffic but incur a larger cost in computing. In this artic…
High voltage direct current links based on voltage source converters (VSC-HVDC) embedded in alternating current (AC) systems are receiving a great deal of attention recently because they can contribute positively to the flexibilisation of modern power systems. Among several possibilities, AC-line-emulation control has been highlighted as an simple-but-useful alternative for these type of systems. With this strategy, the power flow through the link is controlled proportionally to the angle difference between its two AC terminals and this provides self-adaptation of the power flow in case of con…
Ensuring nominal asymptotic stability of the Nonlinear Model Predictive Control controller is not trivial. Stabilizing ingredients such as terminal penalty term and terminal region are crucial in establishing the asymptotic stability. Current work presents alternate approaches namely arbitrary controller based approach and linear quadratic regulator based approach, which provide larger degrees of freedom for enlarging the terminal region as against conservative approaches from the literature. Efficacy of the proposed approaches is demonstrated using benchmark two state continuous stirrer tank …
We present a full review of PID passivity-based controllers (PBC) applied to power electronic converters, discussing limitations, unprecedented merits and potential improvements in terms of large-signal stability, robustness and performance. We provide four main contributions. The nominal case is first considered and it is shown, under the assumption of perfect knowledge of the system parameters, that the PID-PBC is able to guarantee global exponential stability of a desired operating point for any positive gains. Second, we analyze robustness of the controller to parameters uncertainty for a …
This paper proposes a novel unit-quaternion observer-based controller for attitude tracking (attitude and angular velocity) with guaranteed transient and steady-state performance. The proposed approach is computationally cheap and can operate based on measurements provided, for instance by a typical low-cost inertial measurement unit (IMU) or magnetic, angular rate, and gravity (MARG) sensor without the knowledge of angular velocity. First, an observer evolved on $\mathbb{S}^{3}\times\mathbb{R}^{3}$ is developed guaranteeing asymptotic stability of the closed loop error signals starting from a…
Small-Signal Stability Manifolds in Converter-Dominated Power Systems
Università Campus Bio-Medico di Roma（罗马生物医学大学）；University of Colorado Denver（科罗拉多大学丹佛分校）；Università degli Studi di Genova（热那亚大学）；Politecnico di Milano（米兰理工大学）
In this paper, the stability and stabilization problem of positive nonlinear systems, described by the Takagi-Sugeno discrete-time fuzzy model, is studied. The proposed approach is based on the linear co-positive Lyapunov function and parallel distributed controller. Necessary and sufficient conditions for the existence of a state feedback controller, which guarantees the positivity and stability of the closed-loop system, are obtained by a new approach as linear programming, and to solve it and obtain the controller coefficients, the optimal Convex Optimization algorithm is used. Moreover, th…
