Nominal System Research Articles

Constraint‐Driven Multilane Merging Control for Underactuated Connected and Automated Vehicle System With Mismatched Uncertainty

ABSTRACTThis article investigates the merging control for underactuated connected and automated vehicle (CAV) systems with mismatched uncertainty. The objective is to guarantee the safe and prescribed dynamic performance of the system during multilane merging. For CAV multidimensional motions, a strongly coupled vehicle dynamics with time‐varying uncertainties is constructed. For the nominal system, the control objectives are designed as system constraints, with equality constraints guaranteeing merging and time‐varying inequality constraints guaranteeing dynamic performance bounds. Based on the diffeomorphism method and bounded constraint, the system constraints are reconstructed to a unified representation. Combining system constraints and underactuated structure, the nominal controller is derived based on constraint‐following. For the uncertain system, the uncertainty is decomposed into matched and mismatched portions by orthogonal decomposition. The adaptive robust controller is designed based only on matched uncertainty. Through Lyapunov minimax analysis, the control renders the errors uniformly bounded and uniformly ultimately bounded. Simulation results show that merging and platooning are effectively achieved with the proposed control. The system has excellent transient and steady state performance even in the presence of time‐varying uncertainties.

A simplified automated approach for a preliminary safety assessment of distributed electric and hybrid propulsion systems

AbstractTo reduce the environmental impact of future aircraft, the usage of disruptive hybrid electric propulsion systems, in conjunction with distributed propulsion systems, is envisioned. The complexity of those novel powertrain concepts increases significantly. Besides nominal system characteristics, this particularly applies for off-nominal behaviour and consequences. As the safety impact on aircraft level is not always obvious, the suitability of a given component failure rate has to be analysed already in a preliminary design stage. Within this work, a method shall be introduced that allows a simplified automated safety assessment of any powertrain architecture. All relevant combinations of single and multiple failures are identified and a combined failure rate is derived. Thereafter, the impact of single and multiple component failures is evaluated on aircraft level. A selection of metrics for top-level-aircraft functions is used to implement an impact-driven analysis for each relevant failure case. The metrics used assess the adverse effects on climb performance, lateral controllability and range degradation. For all failure combinations, these effects can be validated against requirements imposed on the configuration. The possibility to formulate failure rate-related requirements follows the idea to target an equivalent level of safety compared to existing regulations, independently of the nature of the failure scenario. Results of this study show the necessity for a reevaluation of the configurations assessed, either regarding their architecture or the assumed component failure rate. The method allows an early detection of configuration-specific shortcomings of complex powertrain architectures already in a preliminary aircraft design stage.

Optimal tongue weight selection criteria for light vehicle-trailer combinations

When towing a trailer, proper weight distribution between the vehicle and trailer axles is crucial for system stability and manoeuvrability. Therefore, drivers are strongly recommended to keep the tongue weight, the downward force applied by the trailer at the hitch, within 10–15% of the trailer's gross weight. Despite extensive searches, the current academic and technical literature appears to lack quantitative analyses justifying the standard tongue weight recommendations. This paper presents comprehensive analyses of the lateral behaviour characteristics of light vehicle-trailer combinations influenced by variations in tongue weight. Subsequently, it proposes two novel selection criteria for determining the optimal tongue weight from the perspectives of stability and consistency. The optimal tongue weights for the stability and consistency of the nominal vehicle-trailer system are identified as 22.61% and 48.61% of the trailer weight respectively. Finally, the effectiveness of the proposed criteria is verified through CarSim simulation experiments, assessing 3% settling time and Root-Mean-Square error of vehicle yaw rate.

Constitutional Court Decision No.60/Puu-XXII/2024 Protects the Constitutional Rights of Citizens and Political Parties in Simultaneous Regional Elections in the Regions

Since Indonesia's establishment and independence, the process of filling the seats or positions of Regional Heads has changed many times, starting from the Old Order era, the New Order, and the reform period. These changes are actually in accordance with the needs of the times and not motivated by the interests of maintaining power. The decision of the Constitutional Court (MK) Number 60/PUU-XXII/2024 is right for now. At least it saves democracy from the cartel politics being played by the political elites in the country. The Constitutional Court's decision, which changed the threshold to resemble or almost the same as the requirements for individual candidates, opened the faucet for competition to become even more alive. This includes guaranteeing the constitutional rights of non-parliamentary political parties (without seats) to be able to nominate candidates for Regional Heads who were originally unable to as specified in Article 40 of Law 10 of 2016 concerning Pilkada. However, for the sustainability of democracy in the future, the author views that this decision is not optimal or still leaves problems. In the future, the implementation or application of a threshold or minimum requirement of support for the nomination of candidates for Regional Heads and even the President is no longer appropriate. In the future, an open nomination system should be applied, in which all political parties participating in the elections that pass the KPU verification are automatically entitled to propose candidates for Regional Heads. Some countries that adhere to the Presidential system do not recognize the term threshold. America, Brazil, Peru, Mexico, Colombia, and Kyrgyzstan.

Robust deadbeat predictive current control for unipolar sinusoidal excited SRM with multi-parameter mismatch compensation

In the control of unipolar sinusoidal excited switched reluctance motors (SRMs), deadbeat predictive current controllers (DPCCs) have gained attention for their enhanced dynamic performance. However, periodic disturbances caused by mismatches between the predictive model’s nominal and actual system parameters degrade the control performance of SRMs. To address this issue, a robust DPCC with multi-parameter compensation is proposed to improve dq0-axes current control performance. By analyzing the impact of parameter mismatches, a Kalman filter (KF) is developed to compensate for inductance coefficient mismatches, mitigating periodic disturbances. Additionally, a disturbance estimator with measurement noise suppression is integrated into the DPCC for both state and disturbance estimation to handle residual uncertainties, including winding resistance mismatches, magnetic saturation, and unmodeled dynamics. Compared simulation and experimental results validate the effectiveness of the proposed robust DPCC.

A Dependent Nominal Physical Type System for Static Analysis of Memory in Low Level Code

We tackle the problem of checking non-proof-carrying code , i.e. automatically proving type-safety (implying in our type system spatial memory safety) of low-level C code or of machine code resulting from its compilation without modification. This requires a precise static analysis that we obtain by having a type system which (i) is expressive enough to encode common low-level idioms, like pointer arithmetic, discriminating variants by bit-stealing on aligned pointers, storing the size and the base address of a buffer in distinct parts of the memory, or records with flexible array members, among others; and (ii) can be embedded in an abstract interpreter. We propose a new type system that meets these criteria. The distinguishing feature of this type system is a nominal organization of contiguous memory regions, which (i) allows nesting, concatenation, union, and sharing parameters between regions; (ii) induces a lattice over sets of addresses from the type definitions; and (iii) permits updates to memory cells that change their type without requiring one to control aliasing. We provide a semantic model for our type system, which enables us to derive sound type checking rules by abstract interpretation, then to integrate these rules as an abstract domain in a standard flow-sensitive static analysis. Our experiments on various challenging benchmarks show that semantic type-checking using this expressive type system generally succeeds in proving type safety and spatial memory safety of C and machine code programs without modification, using only user-provided function prototypes.

Loss of the Sturm–Liouville Property of Time-Varying Second-Order Differential Equations in the Presence of Delayed Dynamics

This paper considers a nominal undelayed and time-varying second-order Sturm–Liouville differential equation on a finite time interval which is a nominal version of another perturbed differential equation subject to a delay in its dynamics. The nominal delay-free differential equation is a Sturm–Liouville system in the sense that it is subject to prescribed two-point boundary conditions. However, the perturbed differential system is not a Sturm–Liouville system, in general, due to the presence of delayed dynamics. The main objective of the paper is to investigate the loss of the boundary values of the Sturm–Liouville nominal undelayed system in the presence of the delayed dynamics. Such a delayed dynamics is considered a perturbation of the nominal dynamics related to the Sturm–Liouville system with given two-point boundary values. In particular, this loss of the Sturm–Liouville exact tracking of the prescribed two-point boundary values might happen because the nominal boundary values may become lost by the state trajectory solution in the presence of delays, related to the undelayed case, due to the presence of the delayed dynamics. The worst-case error description of the deviation of the two-point boundary values of the current perturbed differential with respect to those of the nominal Sturm–Liouville system is characterized in terms of error norms related to the nominal system. Under sufficiently small deviations of the parameterization of the perturbed system with respect to the nominal one, such a worst-error characterization makes the current perturbed system an approximate Sturm–Liouville system of the nominal undelayed one.

Fractional-order Sliding Mode Control of Manipulator Combined with Disturbance and State Observer

A fractional-order sliding mode control (FSMC) method for a manipulator based on disturbance and state observers is proposed. First, a state estimator is designed that can estimate the velocity and acceleration, and only joint position feedback and the mathematical model of the manipulator are needed. The state estimator converges in finite time. Then, the disturbance observer is designed. By designing the nominal system model of the manipulator, a disturbance observation error is introduced into the closed-loop control so that the performance of the manipulator can track the nominal system. Finally, a sliding mode controller (SMC) based on the fractional differential operator theory is also designed. The value of the sliding mode variable in the derivation of the controller is composed of the fractional derivative of the trajectory tracking error of the manipulator, whereas the fractional differentiation operation uses integration in its realization, and the integration is a low-pass filter, thus, high-frequency noise is suppressed. In the experimental section, the method designed is compared with the conventional sliding mode, which further reveals the rapidity and control accuracy of FSMC.

Malmquist orthogonal functions based Tube model predictive control with sliding mode for DC motor servo system

This paper introduces a novel approach to the conventional model predictive control design within a tube model predictive control framework for a DC motor servo system that is an important component of various control systems in process industries. Tube model predictive control proves to be an effective method in the formulation, analysis, and implementation of robust control strategies. The objective is to include all possible trajectories of an uncertain system within a tube of the nominal system trajectories. Therefore, the proposed method incorporates discrete-time generalized Malmquist orthogonal functions for nominal model predictive controller design, which is the first time that these functions are used for this purpose in combination with the auxiliary sliding mode controller. The sliding mode controller has a crucial role in determining the robust dynamics of a closed-loop system in the presence of disturbances and plant nonlinearities. Experimental results of DC servo motor angular position control are presented and discussed for two different sliding mode control algorithms. The analysis shows improved performance in terms of fast reference tracking and disturbance rejection.

To caucus or primary? Why state parties change their presidential nomination contests

AbstractPresidential nominations are generally perceived to be under the control of primary voters and caucus‐goers, with party organizations themselves largely powerless to steer outcomes. However, parties are highly active in the background, often switching contests between primaries and caucuses or vice versa in order to influence the nomination. Despite the popular narrative of parties becoming more internally democratic and abandoning caucuses, we find numerous instances of states moving from primaries to caucuses. We examine state party switches between caucuses and primaries between 1980 and 2024, testing various theories of party change. This approach yields few systematic conclusions. Therefore, we shift to examining contemporaneous coverage of state party switches using an inductive qualitative approach, revealing a complex and dynamic nomination system and a variety of reasons why state parties choose one form of contest over another. These findings catch state parties in the act of trying to control nomination contests in surprisingly overt ways.

Fault tolerant control of uncertain hydraulic system against actuator fault based on redesign Lyapunov approach

The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. This paper proposes the design of fault tolerant control for a class of uncertain nonlinear systems with actuator faults based on Lyapunov redesign principle. First, an assumption is introduced to design the control of the nominal system. Then, a new control law has been introduced to handle the difficulty caused by actuator failures. It is shown that the actuator faults can be completely compensated by the proposed nonlinear controller. Finally, the method will be applied to a hydraulic system to show its effectiveness.

Event-Triggered Mechanism-Based Discrete-Time Nash Equilibrium Seeking for Graphic Game With Outlier-Resistant ESO.

In this article, we consider a discrete-time Nash equilibrium (NE) seeking problem for graphic game subject to disturbances. For the first-order dynamics, the discrete-time outlier-resistant extended state observer (ESO)-based game strategy is proposed to enable the players to estimate the disturbances under effect of anomaly measurements and then compensate them. An event-triggered mechanism is applied between adjacent players to reduce the frequency of communication. The convergence of the outlier-resistant ESO and control strategy is presented. Moreover, the upper bound of ϵ -NE solution deviating from the unique point of nominal system is given analytically. Then, the addressed issues are extended to high-order game systems. The NE seeking-based control strategy for each player is designed such that the equilibrium point converges to the ϵ -NE which is also analytically calculated. Finally, in order to verify the effectiveness of the proposed game strategy, an example of satellite system is given.

ADP-based online compensation hierarchical sliding-mode control for partially unknown switched nonlinear systems with actuator failures

This article investigates an adaptive dynamic programming-based online compensation hierarchical sliding-mode control problem for a class of partially unknown switched nonlinear systems with actuator failures and uncertain perturbations under an identifier-critic neural networks architecture. Firstly, by introducing a cost function related to hierarchical sliding-mode surfaces for the nominal system, the original control problem is equivalently converted into an optimal control problem. To obtain this optimal control policy, the Hamilton–Jacobi–Bellman equation is solved through an adaptive dynamic programming method. Compared with conventional adaptive dynamic programming methods, the identifier-critic network architecture not only overcomes the limitation on the unknown internal dynamic but also eliminates the approximation error arising from the actor network. The weights in the critic network are tuned via the gradient descent approach and the experience replay technology, such that the persistence of excitation condition can be relaxed. Then, a compensation term containing hierarchical sliding-mode surfaces is used to offset uncertain actuator failures without the fault detection and isolation unit. Based on the Lyapunov stability theory, all states of the closed-loop nonlinear system are stable in the sense of uniformly ultimately boundedness. Finally, numerical and practical examples are given to demonstrate the effectiveness of our presented online compensation control strategy.

Robust control design of uncertain nonlinear systems: a self-compensating and self-tuning approach

ABSTRACT The problem of robust stabilisation is considered for a class of uncertain nonlinear systems with linear control term. It is not required that the unforced nominal (nonlinear) system has to be stable and/or has to be known, which means that its Lyapunov function need not be known and/or found for designing a stabilising control scheme to compensate the effect of uncertainty on the systems like some traditional control design approaches. For such a class of uncertain nonlinear systems, a design approach, called a self-compensating and self-tuning one, is presented whereby some robust state feedback control schemes can be easily synthesised. The proposed design approach can result in a linear state feedback control scheme with a time-varying control gain for such a class of uncertain nonlinear systems, which implies the simplicity of the design approach and control results. In addition, the system uncertainty is also not required to have to satisfy the matching conditions.

Mean-square exponential stabilization of mixed-autonomy traffic PDE system

Control of mixed-autonomy traffic where Human-driven Vehicles (HVs) and Autonomous Vehicles (AVs) coexist on the road has gained increasing attention over the recent decades. This paper addresses the boundary stabilization problem for mixed traffic on freeways. The traffic dynamics are described by uncertain coupled hyperbolic partial differential equations (PDEs) with Markov jumping parameters, which aim to address the distinctive driving strategies between AVs and HVs. Considering that the spacing policies of AVs vary in mixed traffic, the stochastic impact area of AVs is governed by a continuous Markov chain. The interactions between HVs and AVs such as overtaking or lane changing are mainly induced by impact areas. Using backstepping design, we develop a full-state feedback boundary control law to stabilize the deterministic system (nominal system). Applying Lyapunov analysis, we demonstrate that the nominal backstepping control law is able to stabilize the traffic system with Markov jumping parameters, provided the nominal parameters are sufficiently close to the stochastic ones on average. The mean-square exponential stability conditions are derived, and the results are validated by numerical simulations.

Model predictive control of switched nonlinear systems using online machine learning

This work introduces an online learning-based model predictive control (MPC) approach for the modeling and control of switched nonlinear systems with scheduled mode transitions. Initially, recurrent neural network (RNN) models are constructed offline, utilizing sufficient historical operational data to capture the nominal system dynamics for each mode. Subsequently, we employ real-time process data to develop online learning RNN models, aiming to approximate the dynamics of switched nonlinear systems in the presence of of bounded disturbances. In cases where the initial RNN model is unavailable for a specific switching mode due to very limited historical data, we use real-time data from closed-loop operations under a proportional–integral (PI) controller to build online learning RNN models. To evaluate the predictive performance of online learning RNNs, a theoretical analysis on their generalization error bound is developed using statistical machine learning theory. Additionally, considering the presence or absence of initial RNN models, two MPC schemes are developed. These schemes employ RNNs as prediction models to stabilize switched nonlinear systems, ensuring closed-loop stability by accounting for the generalization error bound derived for online learning RNNs. Finally, the effectiveness of the proposed MPC schemes is demonstrated through a nonlinear process example with two switching modes.

A novel wideband control scheme for uncertain multi-mass systems and its application to drivetrain benches

In multi-mass systems, torsional vibration is a common and annoying phenomenon. Effective vibration suppression and robustness to wide-range parameter variations are essential for a sound motion system. However, most control methods focus on the primary resonance mode, and the high-order resonance modes are not actively treated in the control design, resulting in the control bandwidth not being high enough and limiting the control performance. This paper proposes a novel two-stage design scheme to realize a wideband control to improve control performance. First, a hybrid uncertainty model is tailored for multi-mass systems, which uses an equivalent and uncertain spring constant to describe the variation of the primary mode and a dynamic uncertainty to cover the other resonance modes. This hybrid model strikes a better balance between the model conservatism and the feasibility of a less conservative design. Then, the passivity of the parameter uncertainty is utilized to conduct a phase compensation on the nominal system. After the phase compensation, all uncertainties are converted into norm-bounded ones, and the robust performance design is carried out. This method is applied to vehicle drivetrain benches, and its superiority is validated through simulation comparisons and experiments on two typical types of drivetrain benches.

Optimal synchronization with [formula omitted]-gain performance: An adaptive dynamic programming approach

This paper studies an optimal synchronous control protocol design for nonlinear multi-agent systems under partially known dynamics and uncertain external disturbance. Under some mild assumptions, Hamilton–Jacobi–Isaacs equation is derived by the performance index function and system dynamics, which serves as an equivalent formulation. Distributed policy iteration adaptive dynamic programming is developed to obtain the numerical solution to the Hamilton–Jacobi–Isaacs equation. Three theoretical results are given about the proposed algorithm. First, the iterative variables is proved to converge to the solution to Hamilton–Jacobi–Isaacs equation. Second, the L2-gain performance of the closed loop system is achieved. As a special case, the origin of the nominal system is asymptotically stable. Third, the obtained control protocol constitutes an Nash equilibrium solution. Neural network-based implementation is designed following the main results. Finally, two numerical examples are provided to verify the effectiveness of the proposed method.

Discrete-time sliding mode control with inverse hyperbolic sine reaching law

Discrete-time sliding mode control (DTSMC) is a popular control strategy used in applications like drones, aerospace, and automotive due to its robustness against parameter uncertainties and external disturbances. One of the crucial components of DTSMC is the reaching law, which governs the motion of the system towards the sliding surface. In this paper, a novel reaching law based on the inverse hyperbolic sine function is proposed. Initially, we examine the unperturbed (nominal) system case, followed by a subsequent scenario involving unidentified disturbances i.e. for the perturbed system. It is observed that the proposed reaching law not only decreases the control effort but also results in a smoother control input characterized by reduced chattering within a low quasi-sliding band. The simulation results show that the proposed reaching law outperforms the existing reaching law (seminal work of Gao et al.) in terms of both lower control effort and quasi-sliding mode band. Additionally, the proposed reaching law is compared with a similar class of reaching law i.e. with the hyperbolic tangent reaching law and the inverse tangent reaching law. The comparison results demonstrate superior performance in terms of robustness, further demonstrating the effectiveness of the proposed reaching law.

Load Frequency Control Strategy of Interconnected Power System Based on Tube DMPC

Solar thermal power generation shares technical characteristics with traditional thermal power generation. This enables rapid adjustment of turbine generator output to meet the demands of the power grid load for frequency modulation. However, fluctuations in light intensity lead to variations in interconnected power system parameters, posing challenges for load frequency control (LFC). In this study, we propose a Robust Distributed Model Predictive Control (RDMPC) method. This method achieves system trajectory tracking by solving the nominal system optimization problem. It also flexibly adjusts the weights of different Tube models to determine the optimal control law using the standard Tube online combination with various gain values. Additionally, we incorporate the states of adjacent areas into the feedback control law to achieve effective coordination between these areas. Using MATLAB/Simulink, we simulated the power system in two areas. Compared to standard Tube DMPC, our proposed algorithm effectively mitigates the impact of light intensity, enhances adjustment speed, reduces frequency fluctuation, and demonstrates superior control effectiveness.