General Control Theory Research Articles

Optimization-based planning of speech articulation using general Tau Theory

This paper presents a model of speech articulation planning and generation based on General Tau Theory and Optimal Control Theory. Because General Tau Theory assumes that articulatory targets are always reached, the model accounts for speech variation via context-dependent articulatory targets. Targets are chosen via the optimization of a composite objective function. This function models three different task requirements: maximal intelligibility, minimal articulatory effort and minimal utterance duration. The paper shows that systematic phonetic variability can be reproduced by adjusting the weights assigned to each task requirement. Weights can be adjusted globally to simulate different speech styles, and can be adjusted locally to simulate different levels of prosodic prominence. The solution of the optimization procedure contains Tau equation parameter values for each articulatory movement, namely position of the articulator at the movement offset, movement duration, and a parameter which relates to the shape of the movement’s velocity profile. The paper presents simulations which illustrate the ability of the model to predict or reproduce several well-known characteristics of speech. These phenomena include close-to-symmetric velocity profiles for articulatory movement, variation related to speech rate, centralization of unstressed vowels, lengthening of stressed vowels, lenition of unstressed lingual stop consonants, and coarticulation of stop consonants.

Value Estimation versus Effort Mobilization: A General Dissociation between Ventromedial and Dorsomedial Prefrontal Cortex.

Deciding on a course of action requires both an accurate estimation of option values and the right amount of effort invested in deliberation to reach sufficient confidence in the final choice. In a previous study, we have provided evidence, across a series of judgment and choice tasks, for a dissociation between the ventromedial prefrontal cortex (vmPFC), which would represent option values, and the dorsomedial prefrontal cortex (dmPFC), which would represent the duration of deliberation. Here, we first replicate this dissociation and extend it to the case of an instrumental learning task, in which 24 human volunteers (13 women) choose between options associated with probabilistic gains and losses. According to fMRI data recorded during decision-making, vmPFC activity reflects the sum of option values generated by a reinforcement learning model and dmPFC activity the deliberation time. To further generalize the role of the dmPFC in mobilizing effort, we then analyze fMRI data recorded in the same participants while they prepare to perform motor and cognitive tasks (squeezing a handgrip or making numerical comparisons) to maximize gains or minimize losses. In both cases, dmPFC activity is associated with the output of an effort regulation model, and not with response time. Taken together, these results strengthen a general theory of behavioral control that implicates the vmPFC in the estimation of option values and the dmPFC in the energization of relevant motor and cognitive processes.

Religion and cognitive control: An event-coding approach

Religion is playing an important role in our lives, be it from a personal perspective as member of a particular congregation or as an agnostic living among believers. What impact has religion on our decision-making and action? Two kinds of impact have been considered: religious goals are likely to constrain and color our behavior, but religion may also strengthen cognitive control in a more generic sense. While evidence supports both considerations, it remains a mystery how that works, that is, which mechanisms underlie the impact of religion on our decisions and action control. Here I suggest a preliminary mechanistic model accounting for this impact. It is based on the Theory of Event Coding (TEC), a general theory of human perception, attention, and action control, and the assumptions that goals are represented in a distributed fashion (as selection criteria) and that their impact is moderated by metacontrol, the current control style that varies between persistence and flexibility. The model is parsimonious (i.e., not religion-specific) and mechanistically transparent, and thus provides a solid basis for more systematic experimentation and theorizing.

Me, myself and I: A general theory of non-Markovian time-inconsistent stochastic control for sophisticated agents

We develop a theory for continuous-time non-Markovian stochastic control problems which are inherently time-inconsistent. Their distinguishing feature is that the classical Bellman optimality principle no longer holds. Our formulation is cast within the framework of a controlled non-Markovian forward stochastic differential equation, and a general objective functional setting. We adopt a game-theoretic approach to study such problems, meaning that we seek for sub-game perfect Nash equilibrium points. As a first novelty of this work, we introduce and motivate a refinement of the definition of equilibrium that allows us to establish a direct and rigorous proof of an extended dynamic programming principle, in the same spirit as in the classical theory. This in turn allows us to introduce a system consisting of an infinite family of backward stochastic differential equations analogous to the classical HJB equation. We prove that this system is fundamental, in the sense that its well-posedness is both necessary and sufficient to characterise the value function and equilibria. As a final step we provide an existence and uniqueness result. Some examples and extensions of our results are also presented.

The Industry 4.0 technological and information processes cyber-modelling

Cyber-modelling is the information models simulation process describing in a mathematical and formal logic languages (phenomenon models) how cyber-physical systems interaction mechanisms are united with different control laws and parameter values. The equation complexity represented in different levels of cyber-physical production systems hierarchy and non-equations of algebra, logic, end-subtraction, vector and matrices form in a discreet and uninterrupted times are defined with an aggregated number in the industrial automatics element control loop. The cyber-modelling is done for statistic and dynamic processes and equipment states being monitored in a virtual environment fixating actual in a time interval technological data. The cyber-modelling is done with integrated calculation equipment systems with parallel physical production processes of item manufacturing. The model time faster than physical processes let prognosticate the corrections modifying control signals and phase variables of cyber-physical systems united in an assembly conveyor. The cyber-modelling advantage is an expanded number of cycles to optimize the technological processes, which are calculated with integrated calculation systems using consecutive approximation method. They describe the cyber-modelling technology and propose the information models based on phenomenon cyber-physical production processes descriptions with general control theory terms, calculations and connection for hierarchy controlling structures.

The Me-File: An Event-Coding Approach to Self-Representation.

Numerous authors have taken it for granted that people represent themselves or even have something like “a self”, but the underlying mechanisms remain a mystery. How do people represent themselves? Here I propose that they do so not any differently from how they represent other individuals, events, and objects: by binding codes representing the sensory consequences of being oneself into a Me-File, that is, into an event file integrating all the codes resulting from the behaving me. This amounts to a Humean bundle-self theory of selfhood, and I will explain how recent extensions of the Theory of Event Coding, a general theory of human perception and action control, provide all the necessary ingredients for specifying the mechanisms underlying such a theory. The Me-File concept is likely to provide a useful mechanistic basis for more specific and more theoretically productive experimentation, as well as for the construction of artificial agents with human-like selves.

SYSTEMATIC APPROACH TO WORK SAFETY MANAGEMENT IN THE WORKPLACE

Occupational safety management in our country no longer meets modern requirements for occupational safety in the workplace and needs to be improved, in particular through the introduction of a risk-oriented approach to the assessment of production factors. The use of risk-oriented approach system to safety management in the workplace is substantiated in this work, and it is the primary link in the management system of labor protection and its optimal (comfortable) organization significantly affects the production environment, safety and staff productivity. A structural and logical model of the incident at the workplace is proposed and possible dangerous events, the development of which in space and time can lead to its implementation are identified. Dangerous events can be caused by both - the actions of the employer and the employee, as well as external factors. All considered dangerous events are random in nature, so methods of general theory of random process control, simulation and Boolean algebra are used for their analysis. According to this model, workplace safety management involves identifying the factors that are most likely to be present in the workplace and justifying measures to reduce the frequency of their occurrence and increase the level of safety. It is shown that the use of a systemic risk-oriented approach to safety management in the workplace will allow to identify the factors that are most likely to cause accidents and to develop appropriate measures to eliminate them. In a market economy, an important point in occupational safety management at all levels is to resolve the compromise between the economic feasibility of economic activity and social responsibility of the state in a way that reduces production risk, namely - maintaining human-centric economic development. Finding such a compromise is difficult and problematic, as it is difficult to compare in commensurate units the economic performance of economic activities with social losses due to accidents and occupational diseases at work. In the conditions of decentralization, when the role of supervisory bodies over the state of labor protection is reduced, it is very important to form elements of labor protection culture in employees and managers. Improving public and cultural education on occupational safety remains a priority of our country's public policy, in particular through higher education, which trains highly qualified workers and senior managers who are personally responsible for occupational safety at each workplace.

A map of control for cold atmospheric plasma jets: From physical mechanisms to optimizations

The study of cold atmospheric plasma (CAP) began about a decade ago. Currently, multiple applications of CAP have been discovered including biomedicine, nanomaterials, agriculture, and water purifications. At the current stage of these research fields, it is obvious that the next move will be CAP optimization for each specific application. For example, in the field of plasma-based cancer treatment, due to the different responses of cell lines, CAP can activate different biological pathways in different cells, i.e., to be selective. One of the most commonly used CAP types is the cold atmospheric plasma jet (CAPJ). However, without a full understanding of CAPJ physics, it is impossible to optimize the plasma for every application condition. Moreover, since each research team is equipped with its own CAPJ generator, the hardware behaviors vary significantly across researchers. Therefore, a complete big picture of CAPJ control and parameters is a critical milestone for future CAPJ optimization in these research fields. This Review provides a summary of how CAPJ parameters can be manipulated with the control inputs and hardware design to extend that the chemical compositions can be modified by the gas flow rate, discharge waveform, target properties, and local environment. Based on the control map summarized in this work, CAPJ users can easily optimize their device for a certain specific purpose, such as maximizing OH and H2O2 for cancer treatment or maximizing O3 and ultraviolet for sterilization. Therefore, this study sheds light on the general theory of CAPJ control and can be a basis for future optimization of low-temperature plasma devices. Consideration of the plasma control based on machine learning methods has been receiving interest recently and certainly will become a future hot topic.

Servo Control of On-/Off-drive-type Tracked Vehicle Using Input Time Adjustment

On-/off-drive-type tracked vehicles are machines used for agricultural and snow vehicles. The kinematics model of this vehicle is a nonlinear system (called a driftless system), for that reason which general linear control theory cannot be used. One method to solve this problem is to use conversion to a time-state control form, which considers one of the state variables as a time axis. This conversion allows us to make the model a linear system. In addition, a converting input law in which the continuous-valued inputs obtained by state feedback are converted into discrete-valued inputs, is used for discrete-valued input systems control. However, when the above-mentioned conversion input law is applied to a system with a time-state control form, the theoretical conditions cannot be satisfied and errors may occur. This problem not only leads to theoretical discrepancies but also causes large response degradation due to excessive storage of errors in a servo system that includes an integrator. Therefore, in this study, we propose a method to reduce the theoretical discrepancies and prevent response degradation by adjusting the input time for on-/off-drive-type tracked vehicle control, using a time-state control form. We applied the proposed method to a linear tracking control using a servo system and confirmed its effectiveness through numerical simulations and experiments.

ПУТИ ПОВЫШЕНИЯ КАЧЕСТВА ТЕХНИЧЕСКОГО ОБСЛУЖИВАНИЯ И ТЕКУЩЕГО РЕМОНТА ЛЕСОВОЗНЫХ АВТОМОБИЛЕЙ

The article discusses ways to improve the quality of maintenance and maintenance of forest vehicles. Product quality is a controlled object that can be adjusted on the basis of the principles of general control theory, sequentially establishing quality planning tasks, organizing the actions of the actuator with ensuring the execution of these tasks, comparing the actual value of the obtained result with the planned task, implementing direct and reverse connections and possibilities of influencing the actuator in case of deviations of actual quality values from the planned task.
 The goal of quality management is to create products of a quality level that meets certain needs and demands of the consumer, meets the established requirements.
 Quality management is an organic component of the overall enterprise management system. All employees of the enterprise, including quality service personnel, participate in quality management and assurance.
 The principles of operating quality systems at maintenance and repair enterprises (customer orientation; leadership of heads; Involvement of employees, process and system approaches to quality management, continuous improvement of the system, decision-making based on information monitoring) and factors affecting the quality of works (spare parts for units; timeliness of maintenance; quality of technical diagnosing; Qualification and motivation of employees).

A Maximin Optimal Online Power Control Policy for Energy Harvesting Communications

A general theory of online power control for discrete-time battery limited energy harvesting communications is developed, which leads to, among other things, an explicit characterization of a maximin optimal policy. This policy only requires the knowledge of the (effective) mean of the energy arrival process and maximizes the minimum asymptotic expected average reward (with the minimization taken over all energy arrival distributions of a given (effective) mean). Moreover, it is universally near optimal and has a strictly better worst-case performance as well as a strictly improved lower multiplicative factor in comparison with the fixed fraction policy proposed by Shaviv and \"{O}zg\"{u}r when the objective is to maximize the throughput over an additive white Gaussian noise channel. The competitiveness of this maximin optimal policy is also demonstrated via numerical examples.

DYNAMIC PROBLEM OF FORMATION OF SECURITIES PORTFOLIO UNDER UNCERTAINTY CONDITIONS

The analysis of known methods for solving the problem of forming a portfolio of securities in the face of uncertainty is carried out. Traditionally, the problem is solved under the assumption that for each type of asset, the values of the main statistical characteristics of the random value of their profitability (mathematical expectation and variance) are known. At the same time, the variance of portfolio returns, which is minimized, is used as a criterion for portfolio optimization. Two alternative approaches to solving the formulated problem are proposed. The first of them provides a decision on the criterion of the probability that the random total portfolio return will not be lower than the given. It is assumed that the random return for each type of asset is distributed normally and the statistical characteristics of the respective densities are known. The original problem is reduced to the problem of maximizing the quadratic fractional criterion in the presence of linear constraints. To solve this non-standard optimization problem, a special iterative algorithm is proposed that implements the procedure for sequential improvement of the plan. The method converges and the computational procedure for obtaining a solution can be stopped by any of the standard criteria. The second approach considers the possibility of solving the problem under the assumption that the distribution densities of random asset returns are not known, however, based on the results of preliminary statistical processing of the initial data, estimates of the values of the main numerical characteristics for each of the assets are obtained. To solve the problem, a new mathematical apparatus is used – continuous linear programming, which is a generalization of ordinary linear programming to the case when the task variables are continuous. This method, in the considered problem, is based on solving an auxiliary problem: finding the worst-case distribution density of a random total portfolio return at which this total return does not reach an acceptable threshold with maximum probability. Now the main minimax problem is being solved: the formation of the best portfolio in the worst conditions. The resulting computational scheme leads to the problem of quadratic mathematical programming in the presence of linear constraints. Next, a method is proposed for solving the problem of forming a portfolio of securities, taking into account the real dynamics of the value of assets. The problem that arises in this case is formulated and solved in terms of the general theory of control, using the Riccati equation.

General Theory of Skyhook Control and its Application to Semi-Active Suspension Control Strategy Design

A novel general theory of skyhook control is proposed and applied to the semi-active suspension control strategy design to improve the performance of the vehicle suspension system. Based on this theory, the mechanical impedance model of the general theory of skyhook suspension is established. To design the suspension structure, the effect of the skyhook element and its parameters on suspension is analyzed. Then, adaptive fish swarm algorithm based on nonlinear dynamic visual field is used to optimize the parameters of the general theory of skyhook control. To realize the general theory of skyhook control and verify it, a novel controllable inerter is designed and utilized into the semi-active suspension system. The simulation results demonstrate that the semi-active suspension with a general theory of skyhook control can enhance the suspension performance. Finally, the robustness of the general theory of skyhook control under different spring stiffness and sprung mass is researched. The results indicate that the suspension with the general theory of skyhook control has superior performance and robustness compared with the traditional skyhook damper controlled suspension and passive suspension.

Selected problems of automatic obstacle avoiding

The paper presents selected problems concerning the concept of automatic controlling of motor vehicle motion in case of sudden appearance of an obstacle. If the vehicle cannot be brought to a halt before hitting the obstacle and the adjacent lane is clear, circumvention of the obstacle is the only way to avoid a collision. In the concept of the vehicle control system, elements of general control theory and simplified models of longitudinal and lateral vehicle dynamics have been used. The vehicle controlling process consists of two stages: braking and then changing the lane at a speed determined by the braking stage. The first stage is implemented with using standard mechatronic systems that automatize the braking process, while the second stage requires the use of a special controller coupled with the steering system. The controller generates a “bang-bang” reference signal and corrects it by means of regulating systems that minimize the deviations of the actual (measured) signals describing vehicle’s trajectory from the reference signal. The control algorithm developed has been based on very simplified and, thanks to that, efficient reference models. The algorithm was validated by simulation tests, where a model of a medium-size truck was used as the virtual controlled object. In the model (3D, nonlinear, MBS type, experimentally verified), a very detailed description of vehicle motion, even in boundary conditions, can be taken into account. The paper presents fragments of the research work, including unpublished results of computational tests.

Multidisciplinary and Historical Perspectives for Developing Intelligent and Resource-Efficient Systems

As communication and computation systems become more complex and target at higher performance, the fundamental limits of nature can be expected to constrain their development and optimization. This calls for intelligent use of basic resources, that is, materials, energy, information, time, frequency, and space. We present a multidisciplinary and historical review on the body of knowledge that can be applied in researching, such as intelligent and resource-efficient systems. We review general system theory, decision theory, control theory, computer science, and communication theory. While multidisciplinarity has been recognized as important, there are no earlier reviews covering all these five disciplines. Based on the review, we build a chronology of intelligent systems and identify connections between the disciplines. Optimization, decision-making, open- and closed-loop control, hierarchy, and degree of centralization turn out to be recurring themes in these disciplines, which have converged to similar solutions that are based on remote control, automation, autonomy, and self-organization. We use future wireless networks as an example to illustrate the open questions and how they can be addressed by applying multidisciplinary knowledge. This paper can help researchers to use knowledge outside their own field and avoid repeating the work done already. The resulting consolidated view can speed up research and is especially important when the fundamental limits of nature are approached and new insights are required to overcome the challenges. The general, long-standing problem to be tackled is multiobjective optimization with autonomous and distributed decision-making in an uncertain, dynamic, and nonlinear environment where the objectives are mutually conflicting.

Dynamics and variational inequalities

A terminal control problem with linear dynamics and a boundary condition given implicitly in the form of a solution of a variational inequality is considered. In the general control theory, this problem belongs to the class of stabilization problems. A saddle-point method of the extragradient type is proposed for its solution. The method is proved to converge with respect to all components of the solution, i.e., with respect to controls, phase and adjoint trajectories, and the finite-dimensional variables of the terminal problem.

Speed Control Method of Electric Vehicle for Improving Passenger Ride Quality

This paper proposes the new speed control method of electric vehicles by generating the longitudinal speed pattern for improving the ride comfort against the longitudinal acceleration/deceleration. Since the longitudinal acceleration/deceleration of EVs causes the discomfort of passengers, reducing such bad effect of acceleration/deceleration acting on passengers is very important for not only the ride comfort of passengers but also vehicle running safety. The proposed method is applying the general optimal control theory and it generates the speed pattern for improving the passenger ride quality based on evaluating the variations of acceleration and the jerk which is time derivative of the acceleration. The effectiveness of the present method is demonstrated through numerical experiments compared with some conventional methods.

General theory of feedback control of a nuclear spin ensemble in quantum dots

We present a microscopic theory of the nonequilibrium nuclear spin dynamics driven by the electron and/or hole under continuous wave pumping in a quantum dot. We show the correlated dynamics of the nuclear spin ensemble and the electron and/or hole under optical excitation as a quantum feedback loop and investigate the dynamics of the many nuclear spins as a nonlinear collective motion. This gives rise to three observable effects: (i) hysteresis, (ii) locking (avoidance) of the pump absorption strength to (from) the natural resonance, and (iii) suppression (amplification) of the fluctuation of weakly polarized nuclear spins, leading to prolonged (shortened) electron spin coherence time. A single nonlinear feedback function as a "measurement" of the nuclear field operator in the quantum feedback loop is constructed which determines the different outcomes of the three effects listed above depending on the feedback being negative or positive. The general theory also helps to put in perspective the wide range of existing theories on the problem of a single electron spin in a nuclear spin bath.

Suicide as Social Control1

Suicide may be moralistic in nature—a response to conduct the perpetrator defines as deviant. Moralistic suicide can be explained with a general theory of social control. Donald Black’s theories of social control explain the handling of grievances with their social structure—or geometry—as defined by the social characteristics and relationships of those involved in a conflict. Here I draw on Black’s paradigm of pure sociology and theories of social control to identify the social structure of moralistic suicide. For example, moralistic suicide varies directly with social closeness and is greater in an upward direction than in a downward direction. This theory is simple, general, testable, and explains variation not addressed by previous theories of suicide.

Nonequilibrium thermodynamics of feedback control

We establish a general theory of feedback control on classical stochastic thermodynamic systems and generalize nonequilibrium equalities such as the fluctuation theorem and the Jarzynski equality in the presence of feedback control with multiple measurements. Our results are generalizations of the previous relevant works to the situations with general measurements and multiple heat baths. The obtained equalities involve additional terms that characterize the information obtained by measurements or the efficacy of feedback control. A generalized Szilard engine and a feedback-controlled ratchet are shown to satisfy the derived equalities.